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10.1101/2021.01.05.20248590 | Evaluation of at-home methods for N95 filtering facepiece respirator decontamination | N95 filtering facepiece respirators (FFRs) are essential for the protection of healthcare professionals and other high-risk groups against Coronavirus Disease of 2019 (COVID-19). In response to shortages in FFRs during the ongoing COVID-19 pandemic, the Food and Drug Administration issued an Emergency Use Authorization permitting FFR decontamination and reuse. However, although industrial decontamination services are available at some large institutions, FFR decontamination is not widely accessible.
To be effective, FFR decontamination must 1) inactivate the virus; 2) preserve FFR integrity, specifically fit and filtering capability; and 3) be non-toxic and safe. Here we identify and test at-home heat-based methods for FFR decontamination that meet these requirements using common household appliances. Our results identify potential protocols for simple and accessible FFR decontamination, while also highlighting unsuitable methods that may jeopardize FFR integrity.
One sentence summarySurvey of at-home methods for N95 respirator decontamination using heat and evaluation of their effects on N95 respirator integrity. | public and global health |
10.1101/2021.01.05.20248590 | Evaluation of at-home methods for N95 filtering facepiece respirator decontamination | N95 filtering facepiece respirators (FFRs) are essential for the protection of healthcare professionals and other high-risk groups against Coronavirus Disease of 2019 (COVID-19). In response to shortages in FFRs during the ongoing COVID-19 pandemic, the Food and Drug Administration issued an Emergency Use Authorization permitting FFR decontamination and reuse. However, although industrial decontamination services are available at some large institutions, FFR decontamination is not widely accessible.
To be effective, FFR decontamination must 1) inactivate the virus; 2) preserve FFR integrity, specifically fit and filtering capability; and 3) be non-toxic and safe. Here we identify and test at-home heat-based methods for FFR decontamination that meet these requirements using common household appliances. Our results identify potential protocols for simple and accessible FFR decontamination, while also highlighting unsuitable methods that may jeopardize FFR integrity.
One sentence summarySurvey of at-home methods for N95 respirator decontamination using heat and evaluation of their effects on N95 respirator integrity. | public and global health |
10.1101/2021.01.06.20249032 | Expression levels of HLA-DRB and HLA-DQ are associated with MHC Class II haplotypes in healthy individuals and rheumatoid arthritis patients | HLA-DRB1 alleles have been associated with several autoimmune diseases. In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), HLA-DRB1 shared epitope (SE) alleles are the major genetic risk factors. In order to investigate whether expression of different alleles of major histocompatibility complex (MHC) Class II genes influence functions of immune cells, we investigated transcriptomic profiles of a variety of immune cells from healthy individuals carrying different HLA-DRB1 alleles. Sequencing libraries from peripheral blood mononuclear cells, CD4+ T cells, CD8+ T cells, and CD14+ monocytes of 32 genetically pre-selected healthy female individuals were generated, sequenced and reads were aligned to the standard reference. For the MHC region, reads were mapped to available MHC reference haplotypes and AltHapAlignR was used to estimate gene expression. Using this method, HLA-DRB and HLA-DQ were found to be differentially expressed in different immune cells of healthy individuals as well as in whole blood samples of RA patients carrying HLA-DRB1 SE-positive versus SE-negative alleles. In contrast, no genes outside the MHC region were differentially expressed between individuals carrying HLA-DRB1 SE-positive and SE-negative alleles. Existing methods for HLA-DR allele-specific protein expression were evaluated but were not mature enough to provide appropriate complementary information at the protein level. Altogether, our findings suggest that immune effects associated with different allelic forms of HLA-DR and HLA-DQ may be associated not only with differences in the structure of these proteins, but also with differences in their expression levels. | rheumatology |
10.1101/2020.12.31.20248928 | Prediction of individuals at high-risk of chronic kidney disease during treatment with lithium for bipolar disorder | BackgroundLithium is the most effective treatment in bipolar disorder. Its use is limited by concerns about risk of chronic kidney disease (CKD). We aimed to develop a model to predict risk of CKD following lithium treatment initiation, by identifying individuals with a high-risk trajectory of renal function.
MethodsWe used United Kingdom Clinical Practice Research Datalink (CPRD) electronic heath records (EHRs) from 2000-2018. CPRD Aurum for prediction model development and CPRD Gold for external validation. We used elastic net to generate a prediction model from potential features. We performed discrimination and calibration assessments in an external validation data set.
We included all patients aged [≥]16 with bipolar disorder prescribed lithium. To be included patients had to have [≥]1 year of follow-up before lithium initiation, [≥]3 estimated glomerular filtration rate (eGFR) measures after lithium initiation (to be able to determine a trajectory) and a normal ([≥]60 mL/min/1.73m2) eGFR at lithium initiation (baseline). In the Aurum development cohort 1609 fulfilled these criteria. The Gold external validation cohort included 934 patients.
We included 44 potential baseline features in the prediction model, including sociodemographic, mental and physical heath and drug treatment characteristics. We compared a full model with the 3-variable five-year kidney failure risk equation (KFRE) and a 3-variable elastic net model.
We used group-based trajectory modelling to identify latent trajectory groups for eGFR. We were interested in the group with deteriorating renal function (the high-risk group).
FindingsThe high-risk group included 191 (11.87%) of the Aurum cohort and 137 (14.67%) of the Gold cohort, of these 168 (87.96%) and 117 (85.40%) respectively developed CKD 3a or more severe during follow-up. The model, developed in Aurum, had a ROC area of 0.879 (95%CI 0.853-0.904) in the Gold external validation data set. At the empirical optimal cut-point defined in the development dataset, the model had a sensitivity of 0. 91 (95%CI 0.84-0.97) and a specificity of 0.74 (95% CI 0.67-0.82). However, a 3-variable elastic net model (including only age, sex and baseline eGFR) performed similarly well (ROC area 0.888; 95%CI 0.864-0.912), as did the KFRE (ROC area 0.870; 95%CI 0.841-0.898).
ConclusionsIndividuals at high-risk of a poor trajectory of renal function can be identified before initiation of lithium treatment by a simple equation including age, sex and baseline eGFR. We did not identify strong predicters of renal impairment specific to lithium treated patients. | nephrology |
10.1101/2021.01.06.21249338 | Neurophysiological and brain structural markers of cognitive frailty differs from Alzheimer's disease | With increasing life span, there is growing importance of understanding the mechanisms of successful cognitive ageing. In contrast, cognitive frailty has been proposed to be a precursor to Alzheimers disease. Here we test the hypothesis that cognitively frail adults represent a branch of healthy ageing, distinct from latent dementia. We used electro-magnetoencephalography and magnetic resonance imaging to investigate the structural and neurophysiological features of cognitive frailty in relation to healthy aging, and clinical presentations of mild cognitive impairment and Alzheimers disease. Cognitive performance of the cognitively frail group was similar to those with mild cognitive impairment. We used a novel cross-modal oddball task to induce mismatch responses to unexpected stimuli. Both controls and cognitively frail showed stronger mismatch responses and larger temporal grey matter volume, compared to people with mild cognitive impairment and Alzheimers disease. Our results suggest that cognitively frail represents a spectrum of normal ageing rather than incipient or undiagnosed Alzheimers disease. Lower cognitive reserve, hearing impairment and medical comorbidity might contribute to the aetiology of cognitive impairment. | neurology |
10.1101/2021.01.06.20248743 | Meta-Analysis of Adenoviral p53 Gene Therapy Clinical Trials in Recurrent Head and Neck Squamous Cell Carcinoma | BackgroundWe conducted a meta-analysis of previous adenoviral p53 (Ad-p53) treatment data in recurrent head and neck squamous cell carcinoma (HNSCC) patients to identify optimal Ad-p53 treatment methods for future clinical trials.
MethodsThe meta-analysis involved recurrent HNSCC patients treated with Ad-p53 for whom p53 genotyping and immunohistochemistry tumor biomarker studies had been performed (n = 70). Ad-p53 tumor treatment responses defined by RECIST 1.1 criteria were correlated with Ad-p53 dose and tumor p53 biomarkers. Gene expression profiles induced by Ad-p53 treatment were evaluated using the Nanostring IO 360 panel.
ResultsAd-p53 dose based upon the injected tumor volume had a critical effect on tumor responses. All responders had received Ad-p53 doses greater than 7 x 1010 viral particles/cm3 of tumor volume. There was a statistically significant difference in tumor responses between patients treated with greater than 7 x 1010 viral particles/cm3 compared to patients treated at lower Ad-p53 doses (Tumor Response 31% (9/29) for Ad-p53 > 7 x 1010 viral particles/cm3 versus 0% (0/25) for Ad-p53 < 7 x 1010 viral particles/cm3; p = 0.0023). All responders were found to have favorable p53 biomarker profiles defined by less than 20% p53 positive tumor cells by immunohistochemistry (IHC), wild type p53 gene sequence or p53 deletions, truncations, or frame-shift mutations without functional p53 tetramerization domains. Preliminary gene expression profiling results revealed that Ad-p53 treatment increased Type I Interferon signaling, decreased TGF-beta and beta-catenin signaling resulting in an increased CD8+ T cell signature which are associated with increased responses to immune checkpoint blockade.
ConclusionsOur findings have important implications for future p53 targeted cancer treatments and identify fundamental principles to guide Ad-p53 gene therapy. We discovered that previous Ad-p53 clinical trials were negatively impacted by the inclusion of patients with unfavorable p53 biomarker profiles and by under dosing of Ad-p53 treatment. Future Ad-p53 clinical trials should have favorable p53 biomarker profiles inclusion criteria and Ad-p53 dosing above 7 x 1010 viral particles/cm3 of injected tumor volume. Preliminary gene expression profiling identified p53 mechanisms of action associated with responses to immune checkpoint blockade supporting evaluation of Ad-p53 in combination with immune checkpoint inhibitors. | oncology |
10.1101/2021.01.07.21249390 | Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19 - Preliminary report | BackgroundThe efficacy of interleukin-6 receptor antagonists in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear.
MethodsWe evaluated tocilizumab and sarilumab in an ongoing international, multifactorial, adaptive platform trial. Adult patients with Covid-19, within 24 hours of commencing organ support in an intensive care unit, were randomized to receive either tocilizumab (8mg/kg) or sarilumab (400mg) or standard care (control). The primary outcome was an ordinal scale combining in-hospital mortality (assigned -1) and days free of organ support to day 21. The trial uses a Bayesian statistical model with pre-defined triggers to declare superiority, efficacy, equivalence or futility.
ResultsTocilizumab and sarilumab both met the pre-defined triggers for efficacy. At the time of full analysis 353 patients had been assigned to tocilizumab, 48 to sarilumab and 402 to control. Median organ support-free days were 10 (interquartile range [IQR] -1, 16), 11 (IQR 0, 16) and 0 (IQR -1, 15) for tocilizumab, sarilumab and control, respectively. Relative to control, median adjusted odds ratios were 1.64 (95% credible intervals [CrI] 1.25, 2.14) for tocilizumab and 1.76 (95%CrI 1.17, 2.91) for sarilumab, yielding >99.9% and 99.5% posterior probabilities of superiority compared with control. Hospital mortality was 28.0% (98/350) for tocilizumab, 22.2% (10/45) for sarilumab and 35.8% (142/397) for control. All secondary outcomes and analyses supported efficacy of these IL-6 receptor antagonists.
ConclusionsIn critically ill patients with Covid-19 receiving organ support in intensive care, treatment with the IL-6 receptor antagonists, tocilizumab and sarilumab, improved outcome, including survival. (ClinicalTrials.gov number: NCT02735707) | intensive care and critical care medicine |
10.1101/2021.01.07.21249390 | Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19 - Preliminary report | BackgroundThe efficacy of interleukin-6 receptor antagonists in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear.
MethodsWe evaluated tocilizumab and sarilumab in an ongoing international, multifactorial, adaptive platform trial. Adult patients with Covid-19, within 24 hours of commencing organ support in an intensive care unit, were randomized to receive either tocilizumab (8mg/kg) or sarilumab (400mg) or standard care (control). The primary outcome was an ordinal scale combining in-hospital mortality (assigned -1) and days free of organ support to day 21. The trial uses a Bayesian statistical model with pre-defined triggers to declare superiority, efficacy, equivalence or futility.
ResultsTocilizumab and sarilumab both met the pre-defined triggers for efficacy. At the time of full analysis 353 patients had been assigned to tocilizumab, 48 to sarilumab and 402 to control. Median organ support-free days were 10 (interquartile range [IQR] -1, 16), 11 (IQR 0, 16) and 0 (IQR -1, 15) for tocilizumab, sarilumab and control, respectively. Relative to control, median adjusted odds ratios were 1.64 (95% credible intervals [CrI] 1.25, 2.14) for tocilizumab and 1.76 (95%CrI 1.17, 2.91) for sarilumab, yielding >99.9% and 99.5% posterior probabilities of superiority compared with control. Hospital mortality was 28.0% (98/350) for tocilizumab, 22.2% (10/45) for sarilumab and 35.8% (142/397) for control. All secondary outcomes and analyses supported efficacy of these IL-6 receptor antagonists.
ConclusionsIn critically ill patients with Covid-19 receiving organ support in intensive care, treatment with the IL-6 receptor antagonists, tocilizumab and sarilumab, improved outcome, including survival. (ClinicalTrials.gov number: NCT02735707) | intensive care and critical care medicine |
10.1101/2021.01.06.21249344 | Combination of blood biomarkers and stroke scales improves identification of large vessel occlusions | Background and PurposeAcute ischemic stroke caused by large vessel occlusions (LVO) is a major contributor to stroke deaths and disabilities; however, identification for emergency treatment is challenging.
AimsTo evaluate the diagnostic accuracy of a panel of biomarkers for LVO prediction.
Methods170 patients with suspected stroke were recruited retrospectively at one hospital. We analysed the plasma levels of D-dimer, OPN, OPG, GFAP, vWF, and ADAMTS13 in LVO vs non-LVO. Diagnostic performance was estimated by using blood biomarkers alone or in combination with NIHSS-derived stroke severity scales.
ResultsOur patient cohort comprised 20% stroke mimics, 11% transient ischemic attack, 11% hemorrhagic stroke, 15% LVO ischemic stroke, 28% non-LVO ischemic stroke, and 15% ischemic stroke with unknown LVO status. Multivariable analysis found that the optimal set of blood biomarkers for LVO prediction was D-dimer (OR 15.4, 95% CI 4.9 to 57.6; p-value<0.001) and GFAP (OR 0.83, 95% CI 0.90 to 0.99; p-value=0.03). The combination of D-dimer and GFAP with stroke scales significantly improved LVO prediction, compared to the stroke scales alone (p-value<0.001). The combination of biomarkers with constructed FAST-ED or EMSA scales achieved an AUC of 95% (95% CI 91-100%) or 93% (CI 95% 89-97%), a sensitivity of 91% (95% CI 71-98%) or 86 (95% CI 66-97%), and a specificity of 95% (95% CI 89-98%) or 94% (95% CI 88-98%), for LVO prediction, respectively.
ConclusionsThe combination of D-dimer, GFAP, and stroke scales could provide a simple and highly accurate tool for identifying LVO patients. | neurology |
10.1101/2021.01.06.21249344 | Combination of blood biomarkers and stroke scales improves identification of large vessel occlusions | Background and PurposeAcute ischemic stroke caused by large vessel occlusions (LVO) is a major contributor to stroke deaths and disabilities; however, identification for emergency treatment is challenging.
AimsTo evaluate the diagnostic accuracy of a panel of biomarkers for LVO prediction.
Methods170 patients with suspected stroke were recruited retrospectively at one hospital. We analysed the plasma levels of D-dimer, OPN, OPG, GFAP, vWF, and ADAMTS13 in LVO vs non-LVO. Diagnostic performance was estimated by using blood biomarkers alone or in combination with NIHSS-derived stroke severity scales.
ResultsOur patient cohort comprised 20% stroke mimics, 11% transient ischemic attack, 11% hemorrhagic stroke, 15% LVO ischemic stroke, 28% non-LVO ischemic stroke, and 15% ischemic stroke with unknown LVO status. Multivariable analysis found that the optimal set of blood biomarkers for LVO prediction was D-dimer (OR 15.4, 95% CI 4.9 to 57.6; p-value<0.001) and GFAP (OR 0.83, 95% CI 0.90 to 0.99; p-value=0.03). The combination of D-dimer and GFAP with stroke scales significantly improved LVO prediction, compared to the stroke scales alone (p-value<0.001). The combination of biomarkers with constructed FAST-ED or EMSA scales achieved an AUC of 95% (95% CI 91-100%) or 93% (CI 95% 89-97%), a sensitivity of 91% (95% CI 71-98%) or 86 (95% CI 66-97%), and a specificity of 95% (95% CI 89-98%) or 94% (95% CI 88-98%), for LVO prediction, respectively.
ConclusionsThe combination of D-dimer, GFAP, and stroke scales could provide a simple and highly accurate tool for identifying LVO patients. | neurology |
10.1101/2021.01.05.21249278 | Quality Control Metrics for Whole Blood Transcriptome Analysis in the Parkinson's Progression Markers Initiative (PPMI) | The Michael J. Fox Foundations Parkinsons Progression Markers Initiative (PPMI) is an observational study to comprehensively evaluate Parkinsons disease (PD) patients using imaging, biologic sampling, clinical and behavioural assessments to identify biomarkers of PD progression. As part of this study, we obtained 4,756 whole blood samples from 1,570 subjects at baseline, 0.5, 1, 2, and 3 years from enrollment in the study. We isolated RNA and performed whole transcriptome sequencing in this longitudinal cohort. Here, we describe and quantify technical variability associated with this dataset through the use of pooled reference samples, including plate distribution, RNA quality, and outliers. This large, uniformly processed dataset is available to researchers at https://www.ppmi-info.org. | genetic and genomic medicine |
10.1101/2021.01.02.20248961 | Prioritization of putatively detrimental variants in euploid miscarriages | Miscarriage is the spontaneous termination of a pregnancy before 24 weeks of gestation. We studied the genome of euploid miscarried embryos from mothers in the range of healthy adult individuals to understand genetic susceptibility to miscarriage not caused by chromosomal aneuploidies. We developed GP, a pipeline that we used to prioritize 439 unique variants in 399 genes, including genes known to be associated with miscarriages. Among the prioritized genes we found STAG2 coding for the cohesin complex subunit, for which inactivation in mouse is lethal, and TLE4 a target of Notch and Wnt, physically interacting with a region on chromosome 9 associated to miscarriages. | genetic and genomic medicine |
10.1101/2021.01.02.20248961 | Prioritization of putatively detrimental variants in euploid miscarriages | Miscarriage is the spontaneous termination of a pregnancy before 24 weeks of gestation. We studied the genome of euploid miscarried embryos from mothers in the range of healthy adult individuals to understand genetic susceptibility to miscarriage not caused by chromosomal aneuploidies. We developed GP, a pipeline that we used to prioritize 439 unique variants in 399 genes, including genes known to be associated with miscarriages. Among the prioritized genes we found STAG2 coding for the cohesin complex subunit, for which inactivation in mouse is lethal, and TLE4 a target of Notch and Wnt, physically interacting with a region on chromosome 9 associated to miscarriages. | genetic and genomic medicine |
10.1101/2021.01.06.21249350 | Automatic Gender Detection in Twitter Profiles for Health-related Cohort Studies | ObjectiveBiomedical research involving social media (SM) data is gradually moving from population-level to targeted, cohort-level data analysis. Though crucial for biomedical studies, SM users demographic information (e.g., gender) is often not explicitly known from profiles. Here we present an automatic gender classification system for SM and we illustrate how gender information can be incorporated into a SM-based health-related study.
Materials and MethodsWe used two large Twitter datasets: (i) public, gender-labeled users (Dataset-1), and (ii) users who have self-reported nonmedical use of prescription medications (Dataset-2). Dataset-1 was used to train and evaluate the gender detection pipeline. We experimented with machine-learning algorithms including support vector machines (SVMs) and deep-learning models, and released packages including M3. We considered users information including profile and tweets for classification. We also developed a meta-classifier ensemble that strategically uses the predicted scores from the classifiers. We applied the best-performing pipeline to Dataset-2 to assess the systems utility.
Results and DiscussionWe collected 67,181 and 176,683 users for Dataset-1 and Dataset-2, respectively. A meta-classifier involving SVM and M3 performed the best (Dataset-1 accuracy: 94.4% [95%-CI: 94.0%-94.8%]; Dataset-2: 94.4% [95%-CI: 92.0%-96.6%]. Including automatically-classified information in the analyses of Dataset-2 revealed gender-specific trends-- proportions of females closely resemble data from the National Survey of Drug Use and Health 2018 (tranquilizers: 0.50 vs. 0.50; stimulants: 0.50 vs. 0.45), and the overdose Emergency Room Visit due to Opioids by CDC (pain relievers: 0.38 vs. 0.37).
ConclusionOur publicly-available, automated gender detection pipeline may aid cohort-specific social media data analyses (https://bitbucket.org/sarkerlab/gender-detection-for-public). | health informatics |
10.1101/2021.01.04.20237578 | Zorro versus Covid-19: fighting the pandemic with face masks | To confront the global Covid-19 pandemic and reduce the spread of the virus, we need to better understand if face mask use is effective to contain the outbreak and investigate the potential drivers in favor of mask adoption. It is highly questionable since there is no consensus among the general public despite official recommendations. For the first time, we conduct a panel econometric exercise to assess the dynamic impact of face mask use on both infected cases and fatalities at a global scale. We reveal a negative impact of mask wearing on fatality rates and on the Covid-19 number of infected cases. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. We also document the increasing adoption of mask use over time. We find that population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. Surprisingly, government effectiveness and income level (GDP) have an unexpected influence. However, strict government policies against Covid-19 have the most significant effect on mask use. Therefore, the most effective way of increasing the level of mask wearing is to enforce strict laws on the wearing of masks. | health policy |
10.1101/2021.01.06.21249282 | COVID-19 Rapid Antigen Test at hospital admission associated to the knowledge of individual risk factors allow overcoming the difficulty of managing suspected patients in hospitals | Early diagnosis of SARS-CoV-2 is essential to limiting the spread of the virus and managing infected patients during hospitalization. The sensitivity of RT-qPCR is contested by the fact that it is time-consuming, executed by trained technicians in proper environment for material extraction. Here, we evaluated the first SARS-CoV-2 antigen test recommended by the World Health Organization at September, 2020 as an alternative for immediate diagnosis of symptomatic and suspected patients at a hospital in Brazil during the epidemic peak. All patients were submitted to RT-qPCR and rapid antigen test using nasopharyngeal swabs rigorously collected at the same time. Demographics, baseline comorbidities, symptoms and outcomes were considered. Prediction analysis revealed that previous stroke, chronic obstructive pulmonary disease, desaturation and tachypnea were the most relevant determinants of the death of COVID-19 patients. Comparison between the rapid antigen test and RT-qPCR revealed an overall PPV of 97%, extended to 100% when performed between 4 and 15 days of symptoms, with an accuracy of 90-91% from days 1 to 7 and a Substantial agreement. The rapid antigen test presented no inconclusive result. Among the discordant results and RT-qPCR inconclusives, 72% presented bilateral multifocal ground-glass opacities on imaging and other exams alterations. The median time to obtain RT-qPCR results was 83.6 hours, against 15 minutes for the rapid test, precious time for deciding on patient isolation and management. Knowledge of the risk factors and a rapid diagnosis upon patient admission is critical to reduce mortality of COVID-19 patients, hospital internal costs and in-hospital transmission. | infectious diseases |
10.1101/2021.01.06.21249280 | Mobilefuge: A low-cost, portable, open source, 3D-printed centrifuge that can be used for purification of saliva samples for SARS-CoV2 detection | One of the best ways to contain the spread of COVID-19 is frequent testing of as many people as possible and timely isolation of uninfected personnel from infected personnel. However, the cost of massive testing is affordable in many countries. The existing technologies might not be scalable to offer affordable testing for millions of people. To address this issue, novel testing methods based on Loop-Mediated Isothermal Amplification (LAMP) were proposed that are more sensitive, require less reagents and can work with saliva samples instead of more tedious nasal swabs. As a result, LAMP based protocols can make it possible to drive the cost down to one dollar per test. These LAMP based methods require a centrifuge device, mostly for separation of viral particles from reaction inhibitors in saliva samples. However, centrifuge is neither accessible nor affordable in many resource limited settings, especially during this pandemic situation when normal supply chains are heavily disrupted. To overcome these challenges, we invented a low-cost centrifuge that can be useful for carrying out low-cost LAMP based detection of SARS-Cov2 virus in saliva. The 3D printed centrifuge (Mobilefuge) is portable, robust, stable, safe, easy to build and operate. The Mobilefuge doesnt require soldering or programming skills and can be built without any specialised equipment, yet practical enough for high throughput use. More importantly, Mobilefuge can be powered from widely available USB ports, including mobile phones and associated power supplies. This allows the Mobilefuge to be used even in off-grid and resource limited settings. We believe that our invention will aid the efforts to contain the spread of COVID-19 by lowering the costs of testing equipment. Apart from the COVID-19 testing, the Mobilefuge can have applications in the field of biomedical research and diagnostics. | infectious diseases |
10.1101/2020.12.28.20248874 | Evaluation of vertical transmission of SARS-CoV-2 in utero: nine pregnant women and their newborns | BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mainly transmitted by droplets and close contact, has caused a pandemic worldwide as of November 2020. According to the current case reports and cohort studies, the symptoms of pregnant women infected with SARS-CoV-2 were similar to normal adults and may cause a series of adverse consequences of pregnancy (placental abruption, fetal distress, epilepsy during pregnancy, etc.). However, whether SARS-CoV-2 can be transmitted to the fetus through the placental barrier is still a focus of debate.
MethodsIn this study, in order to find out whether SARS-CoV-2 infect fetus through placental barrier, we performed qualitative detection of virus structural protein (spike protein and nucleoprotein) and targeted receptor protein (ACE2, CD147 and GRP78) expression on the placental tissue of seven pregnant women diagnosed with COVID-19 through immunohistochemistry. Amniotic fluid, neonatal throat, anal swab and breastmilk samples were collected immediately in the operating room for verification after delivery, which were all tested for SARS-CoV-2 by reverse transcriptionpolymerase chain reaction (RT-PCR).
ResultsThe result showed that CD147 was expressed on the basal side of the chorionic trophoblast cell membrane and ACE2 was expressed on the maternal side, while GRP78 was strongly expressed in the cell membrane and cytoplasm. The RT-PCR results of Amniotic fluid, neonatal throat, anal swab and breastmilk samples were all negative.
ConclusionsWe believed that despite the detection of viral structural proteins in the placenta, SARS-CoV-2 cannot be transmitted to infants due to the presence of the placental barrier.
SummaryOur results showed that, excluding environmental pollution after birth and vaginal infection during childbirth, SARS-CoV-2 was less likely to be transmitted vertically in utero. | infectious diseases |
10.1101/2020.12.30.20248277 | Utilization of Whole Genome Sequencing to Understand SARS-CoV-2 Transmission Dynamics in Long-Term Care Facilities, Correctional Facilities and Meat Processing Plants in Minnesota, March - June 2020 | Congregate settings and high-density workplaces have endured a disproportionate impact from COVID-19. In order to provide further understanding of the transmission patterns of SARS-CoV-2 in these settings, whole genome sequencing (WGS) was performed on samples obtained from 8 selected outbreaks in Minnesota from March - June, 2020. WGS and phylogenetic analysis was conducted on 319 samples, constituting 14.4% of the 2,222 total SARS-CoV-2-positive individuals associated with these outbreaks. Among the sequenced specimens, three LTCFs and both correctional facilities had spread associated with a single genetic sequence. A fourth LTCF had outbreak cases associated with two distinct sequences. In contrast, cases associated with outbreaks in the two meat processing plants represented multiple SARS-CoV-2 sequences. These results suggest that a single introduction of SARS-CoV-2 into a facility can result in a widespread outbreak, and early identification and cohorting of cases, along with continued vigilance with infection prevention and control measures is imperative. | infectious diseases |
10.1101/2021.01.05.21249190 | Host genome analysis of structural variations by Optical Genome Mapping provides clinically valuable insights into genes implicated in critical immune, viral infection, and viral replication pathways in patients with severe COVID-19. | BackgroundThe varied clinical manifestations and outcomes in patients with SARS-CoV-2 infections implicate a role of host-genetics in the predisposition to disease severity. This is supported by evidence that is now emerging, where initial reports identify common risk factors and rare genetic variants associated with high risk for severe/ life-threatening COVID-19. Impressive global efforts have focused on either identifying common genetic factors utilizing short-read sequencing data in Genome-Wide Association Studies (GWAS) or whole-exome and genome studies to interrogate the human genome at the level of detecting single nucleotide variants (SNVs) and short indels. However, these studies lack the sensitivity to accurately detect several classes of variants, especially large structural variants (SVs) including copy number variants (CNVs), which account for a substantial proportion of variation among individuals. Thus, we investigated the host genomes of individuals with severe/life-threatening COVID-19 at the level of large SVs (500bp-Mb level) to identify events that might provide insight into the inter-individual clinical variability in clinical course and outcomes of COVID-19 patients.
MethodsOptical genome mapping using Bionanos Saphyr(R) system was performed on thirty-seven severely ill COVID-19 patients admitted to intensive care units (ICU). To extract candidate SVs, three distinct analyses were undertaken. First, an unbiased whole-genome analysis of SVs was performed to identify rare/unique genic SVs in these patients that did not appear in population datasets to determine candidate loci as decisive predisposing factors associated with severe COVID-19. Second, common SVs with a population frequency filter was interrogated for possible association with severe COVID-19 based on literature surveys. Third, genome-wide SV enrichment in severely ill patients versus the general population was investigated by calculating odds ratios to identify top-ranked genes/loci. Candidate SVs were confirmed using qPCR and an independent bioinformatics tool (FaNDOM).
ResultsOur patient-centric investigation identified 11 SVs involving 38 genes implicated in three key host-viral interaction pathways: (1) innate immunity and inflammatory response, (2) airway resistance to pathogens, and (3) viral replication, spread, and RNA editing. These included seven rare/unique SVs (not present in the control dataset), identified in 24.3% (9/37) of patients, impacting up to 31 genes, of which STK26 and DPP4 are the most promising candidates. A duplication partially overlapping STK26 was corroborated with data showing upregulation of this gene in severely ill patients. Further, using a population frequency filter of less than 20% in the Bionano control dataset, four SVs involving seven genes were identified in 56.7% (21/37) of patients.
ConclusionThis study is the first to systematically assess and highlight SVs potential role in the pathogenesis of COVID-19 severity. The genes implicated here identify novel SVs, especially STK26, and extend previous reports involving innate immunity and type I interferon response in the pathogenesis of COVID-19. Our study also shows that optical genome mapping can be a powerful tool to identify large SVs impacting disease outcomes with split survival and add valuable genomic information to the existing sequencing-based technology databases to understand the inter-individual variability associated with SARS-CoV-2 infections and COVID-19 mortality. | infectious diseases |
10.1101/2021.01.04.20248897 | IL-2 and IFN- are biomarkers of SARS-CoV-2 specific cellular response in whole blood stimulation assays | A proper description of the immune response to SARS-CoV-2 will be critical for the assessment of protection elicited after both infection and vaccination. Uncoupled T and B cell responses have been described in acute and convalescent patients and exposed individuals. We assessed the potential usefulness of whole blood stimulation assays to identify functional cellular immune responses to SARS-CoV-2. Blood from COVID-19 recovered individuals (5 months after infection) and negative subjects was stimulated for 24 hours with HLA predicted peptide "megapools" of the Spike and Nucleoprotein, or the mixture of them. After stimulation, cytokines were quantified using a beads-based multiplex assay. Interleukin-2 and IFN-{gamma} were found to be specific biomarkers of SARS-CoV-2 cellular response. Using the Spike and Nucleoprotein mixture, 91.3% of COVID-19 recovered individuals presented an IL-2 stimulation index over the cut-off, while 82.6% showed IFN-{gamma}. All the negative individuals presented an IL-2 response under the cut-off, while 5.3% of these subjects presented positive IFN-{gamma} stimulation indexes. Moreover, IL-2 production correlated with IgG levels for Spike 1, RBD, and Nucleocapsid. In conclusion, we demonstrate the potential of whole blood stimulation assays and the quantification of IL-2 and IFN-{gamma} for the analysis of SARS-CoV-2 functional cellular responses. | infectious diseases |
10.1101/2021.01.06.21249334 | An Electronic Health Record Compatible Model to Predict Personalized Treatment Effects from the Diabetes Prevention Program: A Cross-Evidence Synthesis Approach Using Clinical Trial and Real World Data | BackgroundAn intensive lifestyle modification program or metformin pharmacotherapy reduced the risk of developing diabetes in patients at high risk, but are not widely used in the 88 million American adults with prediabetes.
ObjectiveDevelop an electronic health record (EHR)-based risk tool that provides point-of-care estimates of diabetes risk to support targeting interventions to patients most likely to benefit.
DesignCross-design synthesis: risk prediction model developed and validated in large observational database, treatment effect estimates from risk-based reanalysis of clinical trial data.
SettingOutpatient clinics in US.
PatientsRisk model development cohort: 1.1 million patients with prediabetes from the OptumLabs Data Warehouse (OLDW); validation cohort: distinct sample of 1.1 million patients in OLDW. Randomized clinical trial cohort: 3081 people from the Diabetes Prevention Program (DPP) study.
InterventionsRandomization in the DPP: 1) an intensive program of lifestyle modification; 2) standard lifestyle recommendations plus 850 mg metformin twice daily; or 3) standard lifestyle recommendations plus placebo twice daily.
ResultsEleven variables reliably obtainable from the EHR were used to predict diabetes risk. This model validated well in the OLDW (c-statistic = 0.76; observed 3-year diabetes rate was 1.8% in lowest-risk quarter and 19.6% in highest-risk quarter). In the DPP, the hazard ratio for lifestyle modification was constant across all levels of risk (HR = 0.43, 95% CI 0.35 - 0.53); while the HR for metformin was highly risk-dependent (HR HR = 1.1 [95% CI: 0.61 - 2.0] in the lowest-risk quarter vs. HR=0.45 [95% CI: 0.35 0.59] in the highest risk quarter). Fifty-three percent of the benefits of population-wide dissemination of the DPP lifestyle modification, and 76% of the benefits of population-wide metformin therapy can be obtained targeting the highest risk quarter of patients.
LimitationsDifferences in variable definitions and in missingness across observational and trial settings may introduce estimation error in risk-based treatment effects.
ConclusionAn EHR-compatible risk model might support targeted diabetes prevention to more efficiently realize the benefits of the DPP interventions. | endocrinology |
10.1101/2021.01.06.21249272 | Integrated Vaccination and Non-Pharmaceutical Interventions based Strategies in Ontario, Canada, as a Case Study: a Mathematical Modeling Study | BackgroundRecently, two "Coronavirus disease 2019" (COVID-19) vaccine products have been authorized in Canada. It is of crucial importance to model an integrated/combined package of non-pharmaceutical (physical/social distancing) and pharmaceutical (immunization) public health control measures.
MethodsA modified epidemiological, compartmental SIR model was utilized and fit to the cumulative COVID-19 case data for the province of Ontario, Canada, from September 8, 2020 to December 8, 2020. Different vaccine roll-out strategies were simulated until 75 percent of the population is vaccinated, including a no-vaccination scenario. We compete these vaccination strategies with relaxation of non-pharmaceutical interventions. Non-pharmaceutical interventions were supposed to remain enforced and began to be relaxed on either January 31, March 31, or May 1, 2021.
ResultsBased on projections from the data and long-term extrapolation of scenarios, relaxing the public health measures implemented by re-opening too early would cause any benefits of vaccination to be lost by increasing case numbers, increasing the effective reproduction number above 1 and thus increasing the risk of localized outbreaks. If relaxation is, instead, delayed and 75 percent of the Ontarian population gets vaccinated by the end of the year, re-opening can occur with very little risk.
InterpretationRelaxing non-pharmaceutical interventions by re-opening and vaccine deployment is a careful balancing act. Our combination of model projections from data and simulation of different strategies and scenarios, can equip local public health decision- and policy-makers with projections concerning the COVID-19 epidemiological trend, helping them in the decision-making process. | epidemiology |
10.1101/2021.01.06.21249349 | Identifying silent COVID-19 infections among children is critical for controlling the pandemic | ImportanceA significant proportion of COVID-19 transmission occurs silently during the pre-symptomatic and asymptomatic stages of infection. Children, while being important drivers of silent transmission, are not included in the current COVID-19 vaccination campaigns.
ObjectiveTo investigate the benefits of identifying silent infections among children as a proxy for their vaccination.
DesignThis study used an age-structured disease transmission model, parameterized with census data and estimates from published literature, to simulate the synergistic effect of interventions in reducing attack rates over the course of one year.
SettingA synthetic population representative of the United States (US) demographics.
ParticipantsSix age groups of 0-4, 5-10, 11-18, 19-49, 50-64, 65+ years based on US census data.
InterventionsIn addition to the isolation of symptomatic cases within 24 hours of symptom onset, vaccination of adults was implemented to reach a 40%-60% coverage over the course of one year with an efficacy of 95% against symptomatic and severe COVID-19.
Main Outcomes and MeasuresThe combinations of proportion and speed for detecting silent infections among children which would suppress future attack rates below 5%.
ResultsIn the base-case scenarios with an effective reproduction number Re = 1.2, a targeted approach that identifies 11% and 14% of silent infections among children within 2 or 3 days post-infection, respectively, would bring attack rates under 5% with 40% vaccination coverage of adults. If silent infections among children remained undetected, achieving the same attack rates would require an unrealistically high vaccination coverage (at least 81%) of this age group, in addition to 40% vaccination coverage of adults. The effect of identifying silent infections was robust in sensitivity analyses with respect to vaccine efficacy against infection and reduced susceptibility of children to infection.
Conclusions and RelevanceIn this simulation modeling study of a synthetic US population, in the absence of vaccine availability for children, a targeted approach to rapidly identify silent COVID-19 infections in this age group was estimated to significantly mitigate disease burden. Without measures to interrupt transmission chains from silent infections, vaccination of adults is unlikely to contain the outbreaks in the near term.
Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the effect of a targeted strategy for identification of silent COVID-19 infections among children in the absence of their vaccination?
FindingsIn this simulation modeling study, it was found that identifying 10-20% of silent infections among children within three days post-infection would bring attack rates below 5% if only adults were vaccinated. If silent infections among children remained undetected, achieving the same attack rate would require an unrealistically high vaccination coverage (over 80%) of this age group, in addition to vaccination of adults.
MeaningRapid identification of silent infections among children can achieve comparable effects as would their vaccination. | epidemiology |
10.1101/2021.01.06.21249349 | Simulated identification of silent COVID-19 infections among children and estimated future infection rates with vaccination | ImportanceA significant proportion of COVID-19 transmission occurs silently during the pre-symptomatic and asymptomatic stages of infection. Children, while being important drivers of silent transmission, are not included in the current COVID-19 vaccination campaigns.
ObjectiveTo investigate the benefits of identifying silent infections among children as a proxy for their vaccination.
DesignThis study used an age-structured disease transmission model, parameterized with census data and estimates from published literature, to simulate the synergistic effect of interventions in reducing attack rates over the course of one year.
SettingA synthetic population representative of the United States (US) demographics.
ParticipantsSix age groups of 0-4, 5-10, 11-18, 19-49, 50-64, 65+ years based on US census data.
InterventionsIn addition to the isolation of symptomatic cases within 24 hours of symptom onset, vaccination of adults was implemented to reach a 40%-60% coverage over the course of one year with an efficacy of 95% against symptomatic and severe COVID-19.
Main Outcomes and MeasuresThe combinations of proportion and speed for detecting silent infections among children which would suppress future attack rates below 5%.
ResultsIn the base-case scenarios with an effective reproduction number Re = 1.2, a targeted approach that identifies 11% and 14% of silent infections among children within 2 or 3 days post-infection, respectively, would bring attack rates under 5% with 40% vaccination coverage of adults. If silent infections among children remained undetected, achieving the same attack rates would require an unrealistically high vaccination coverage (at least 81%) of this age group, in addition to 40% vaccination coverage of adults. The effect of identifying silent infections was robust in sensitivity analyses with respect to vaccine efficacy against infection and reduced susceptibility of children to infection.
Conclusions and RelevanceIn this simulation modeling study of a synthetic US population, in the absence of vaccine availability for children, a targeted approach to rapidly identify silent COVID-19 infections in this age group was estimated to significantly mitigate disease burden. Without measures to interrupt transmission chains from silent infections, vaccination of adults is unlikely to contain the outbreaks in the near term.
Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the effect of a targeted strategy for identification of silent COVID-19 infections among children in the absence of their vaccination?
FindingsIn this simulation modeling study, it was found that identifying 10-20% of silent infections among children within three days post-infection would bring attack rates below 5% if only adults were vaccinated. If silent infections among children remained undetected, achieving the same attack rate would require an unrealistically high vaccination coverage (over 80%) of this age group, in addition to vaccination of adults.
MeaningRapid identification of silent infections among children can achieve comparable effects as would their vaccination. | epidemiology |
10.1101/2021.01.07.21249281 | Association between resting-state functional brain connectivity and gene expression is altered in autism spectrum disorder | Gene expression covaries with brain activity as measured by resting state functional MRI. However, it is unclear how genomic differences driven by disease state can affect this relationship. Here, we integrate brain gene expression datasets of neurotypical controls and autistic (ASD) patients with regionally matched brain activity measurements from fMRI datasets. We identify genes linked with brain activity whose association is disrupted in ASD patients. We identified a subset of genes that showed a differential developmental trajectory in ASD patients compared with controls. These genes are enriched in voltage-gated ion channels and inhibitory neurons, pointing to excitation-inhibition imbalance in ASD. We further assessed differences at the regional level showing that the primary visual cortex is the most affected region in ASD patients. Our results link disrupted brain expression patterns of individuals with ASD to brain activity and show developmental, cell type, and regional enrichment of activity linked genes. | genetic and genomic medicine |
10.1101/2021.01.06.21249352 | OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19 | BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data.
ObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples.
MethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020.
ResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as "no change" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline.
ConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback. | health systems and quality improvement |
10.1101/2021.01.06.21249352 | OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19 | BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data.
ObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples.
MethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020.
ResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as "no change" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline.
ConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback. | health systems and quality improvement |
10.1101/2021.01.06.20249091 | Epidemiological and Clinical Characteristics, and Virologic Features of COVID-19 Patients in Kazakhstan: a Nation-Wide, Retrospective, Cohort Study. | BackgroundThe earliest coronavirus disease-2019 (COVID-19) cases in Central Asia were announced in March 2020 by Kazakhstan. Despite the implementation of aggressive measures to curb infection spread, gaps remain in the understanding of the clinical and epidemiologic features of the regional pandemic.
MethodsWe did a retrospective, observational cohort study of patients with laboratory-confirmed COVID-19 in Kazakhstan between February and April 2020. We compared demographic, clinical, laboratory and radiological data of patients with different COVID-19 severities on admission. Univariable and multivariable logistic regression was used to assess factors associated with disease severity and death. Whole-genome SARS-CoV-2 analysis was performed in 53 patients without a recent history of international travel.
FindingsOf the 1072 patients with laboratory-confirmed COVID-19 in March-April 2020, the median age was 36 years (IQR 24-50) and 484 (45%) were male. On admission, 683 (64%) participants had mild, 341 (32%) moderate, and 47 (4%) severe-to-critical COVID-19 manifestation; 20 deaths (1.87%) were reported at study exit. Multivariable regression indicated increasing odds of severe disease associated with older age (odds ratio 1.05, 95% CI 1.03-1.07, per year increase; p<0.001), the presence of comorbidities (2.13, 95% CI 1.07-4.23; p<0.031) and elevated white blood cell count (WBC, 1.14, 95% CI 1.01-1.28; p<0.032) on admission, while older age (1.09, 95% CI 1.06-1.12, per year increase; p<0.001) and male sex (5.97, 95% CI 1.95-18.32; p<0.002) were associated with increased odds of death. The Kazakhstan SARS-CoV-2 isolates grouped into seven distinct lineages O/B.4.1, S/A.2, S/B.1.1, G/B.1, GH/B.1.255, GH/B.1.3 and GR/B.1.1.10.
InterpretationOlder age, comorbidities, increased WBC count, and male sex were risk factors for COVID-19 disease severity and mortality in Kazakhstan. The broad SARS-CoV-2 diversity suggests multiple importations and community-level amplification, likely predating the declaration of state emergency. Continuous epidemiologic and genomic surveillance may be critical for a better understanding of the regional COVID-19 dynamics. | infectious diseases |
10.1101/2021.01.06.21249345 | Clinical Validation of a Novel T-cell Receptor Sequencing Assay for Identification of Recent or Prior SARS-CoV-2 Infection | BackgroundWhile diagnostic, therapeutic, and vaccine development in the COVID-19 pandemic has proceeded at unprecedented speed and scale, critical gaps remain in our understanding of the immune response to SARS-CoV-2. Current diagnostic strategies, including serology, have numerous limitations in addressing these gaps. Here we describe clinical performance of T- Detect COVID, the first reported assay to determine recent or prior SARS-CoV-2 infection based on T-cell receptor (TCR) sequencing and immune repertoire profiling from whole blood samples.
MethodsMethods for high-throughput immunosequencing of the TCR{beta} gene from blood specimens have been described1. We developed a statistical classifier showing high specificity for identifying prior SARS-CoV-2 infection2, utilizing >4,000 SARS-CoV-2-associated TCR sequences from 784 cases and 2,447 controls across 5 independent cohorts. The T-Detect COVID Assay comprises immunosequencing and classifier application to yield a qualitative positive or negative result. Several retrospective and prospective cohorts were enrolled to assess assay performance including primary and secondary Positive Percent Agreement (PPA; N=205, N=77); primary and secondary Negative Percent Agreement (NPA; N=87, N=79); PPA compared to serology (N=55); and pathogen cross-reactivity (N=38).
ResultsT-Detect COVID demonstrated high PPA in subjects with prior PCR-confirmed SARS-CoV-2 infection (97.1% 15+ days from diagnosis; 94.5% 15+ days from symptom onset), high NPA ([~]100%) in presumed or confirmed SARS-CoV-2 negative cases, equivalent or higher PPA than two commercial EUA serology tests, and no evidence of pathogen cross-reactivity.
ConclusionT-Detect COVID is a novel T-cell immunosequencing assay demonstrating high clinical performance to identify recent or prior SARS-CoV-2 infection from standard blood samples. This assay can provide critical insights on the SARS-CoV-2 immune response, with potential implications for clinical management, risk stratification, surveillance, assessing protective immunity, and understanding long-term sequelae. | infectious diseases |
10.1101/2021.01.06.20249009 | SARS-CoV-2 patient self-testing with an antigen-detecting rapid test: a head-to-head comparison with professional testing | BackgroundAntigen-detecting rapid diagnostic tests (Ag-RDTs) have been widely recommended as a complement to RT-PCR. Considering the possibility of nasal self-sampling and the ease-of-use in performing the test, self-testing may be an option.
Methods and FindingsWe performed a manufacturer-independent, prospective diagnostic accuracy study of nasal mid-turbinate self-sampling and self-testing when using a WHO-listed SARS-CoV-2 Ag-RDT. Symptomatic participants suspected to have COVID-19 received written and illustrated instructions. Procedures were observed without intervention. For comparison, Ag-RDTs with nasopharyngeal sampling were professionally performed. Estimates of agreement, sensitivity, and specificity relative to RT-PCR on a combined oro-/nasopharyngeal sample were calculated. Feasibility was evaluated by observer and participant questionnaires.
Among 146 symptomatic adults, 40 (27.4%) were RT-PCR-positive for SARS-CoV-2. Sensitivity with self-testing was 82.5% (33/40 RT-PCR positives detected; 95% CI 68.1-91.3), and 85.0% (34/40; 95% CI 70.9-92.9) with professional testing. The positive percent agreement between self-testing and professional testing on Ag-RDT was 91.4% (95% CI 77.6-97.0), and negative percent agreement 99.1% (95% CI 95.0-100). At high viral load (>7.0 log10 SARS-CoV-2 RNA copies/ml), sensitivity was 96.6% (28/29; 95% CI 82.8-99.8) for both self- and professional testing. Deviations in sampling and testing (incomplete self-sampling or extraction procedure, or imprecise volume applied on the test device) were observed in 25 out of the 40 PCR-positives. Participants were rather young (mean age 35 years) and educated (59.6% with higher education degree). Most participants (80.9%) considered the Ag-RDT as rather easy to perform.
ConclusionsAmbulatory participants suspected for SARS-CoV-2 infection were able to reliably perform the Ag-RDT and test themselves. Procedural errors might be reduced by refinement of the Ag-RDTs for self-testing, such as modified instructions for use or product design/procedures. Self-testing may result in more wide-spread and more frequent testing. Paired with the appropriate information and education of the general public about the benefits and risks, self-testing may therefore have significant impact on the pandemic. | infectious diseases |
10.1101/2021.01.06.20248927 | Explaining Deep Neural Networks for Knowledge Discovery in Electrocardiogram Analysis | Deep learning-based tools may annotate and interpret medical tests more quickly, consistently, and accurately than medical doctors. However, as medical doctors remain ultimately responsible for clinical decision-making, any deep learning-based prediction must necessarily be accompanied by an explanation that can be interpreted by a human. In this study, we present an approach, called ECGradCAM, which uses attention maps to explain the reasoning behind AI decision-making and how interpreting these explanations can be used to discover new medical knowledge. Attention maps are visualizations of how a deep learning network makes, which may be used in the clinic to aid diagnosis, and in research to identify novel features and characteristics of diagnostic medical tests. Here, we showcase the use of ECGradCAM attention maps using a novel deep learning model capable of measuring both amplitudes and intervals in 12-lead electrocardiograms. | cardiovascular medicine |
10.1101/2021.01.07.21249353 | Inherent random fluctuations in COVID-19 outbreaks may explain rapid growth of new mutated virus variants | A new virus variant of SARS-COV-2 has had a profound impact on society while governments have taken action to limit its impacts by enforcing lockdowns and limiting spread from the UK to other countries. Variants with mutations in the virus genome are likely to occur, but do not always associate to significant changes in the biology of the virus, or the disease. For the variant VOC 202012/01 (also referred to as B.1.1.7), however, preliminary reports indicate it may be more transmissible. Here we use a simulation model calibrated to the inherent random fluctuating transmission pattern of COVID-19 to investigate what the probability may be for detecting more transmissible virus variants post facto. We find that post facto identification of successful virus variants of SARS-COV-2 are likely to exhibit growth rates that are substantially larger than the average growth rate. This finding has implications for interpreting growth rate and transmissibility of new virus variants. | epidemiology |
10.1101/2021.01.06.21249365 | Modeling the effect of vaccination strategies in an Excel spreadsheet: The rate of vaccination, and not only the vaccination coverage, is a determinant for containing COVID-19 in urban areas | We have investigated the importance of the rate of vaccination to contain COVID-19 in urban areas. We used an extremely simple epidemiological model that is amenable to implementation in an Excel spreadsheet and includes the demographics of social distancing, efficacy of massive testing and quarantine, and coverage and rate of vaccination as the main parameters to model the progression of COVID-19 pandemics in densely populated urban areas. Our model predicts that effective containment of pandemic progression in densely populated cities would be more effectively achieved by vaccination campaigns that consider the fast distribution and application of vaccines (i.e., 50% coverage in 6 months) while social distancing measures are still in place. Our results suggest that the rate of vaccination is more important than the overall vaccination coverage for containing COVID-19. In addition, our modeling indicates that widespread testing and quarantining of infected subjects would greatly benefit the success of vaccination campaigns. We envision this simple model as a friendly, readily accessible, and cost-effective tool for assisting health officials and local governments in the rational design/planning of vaccination strategies. | epidemiology |
10.1101/2021.01.06.21249365 | Modeling the effect of vaccination strategies in an Excel spreadsheet: The rate of vaccination, and not only the vaccination coverage, is a determinant for containing COVID-19 in urban areas | We have investigated the importance of the rate of vaccination to contain COVID-19 in urban areas. We used an extremely simple epidemiological model that is amenable to implementation in an Excel spreadsheet and includes the demographics of social distancing, efficacy of massive testing and quarantine, and coverage and rate of vaccination as the main parameters to model the progression of COVID-19 pandemics in densely populated urban areas. Our model predicts that effective containment of pandemic progression in densely populated cities would be more effectively achieved by vaccination campaigns that consider the fast distribution and application of vaccines (i.e., 50% coverage in 6 months) while social distancing measures are still in place. Our results suggest that the rate of vaccination is more important than the overall vaccination coverage for containing COVID-19. In addition, our modeling indicates that widespread testing and quarantining of infected subjects would greatly benefit the success of vaccination campaigns. We envision this simple model as a friendly, readily accessible, and cost-effective tool for assisting health officials and local governments in the rational design/planning of vaccination strategies. | epidemiology |
10.1101/2021.01.06.21249364 | Early Vocal Development in Tuberous Sclerosis Complex | ObjectiveTo determine whether entry into the canonical stage, canonical babbling ratios (CBR) and the level of volubility (vocal measures) are delayed in infants with Tuberous Sclerosis Complex (TSC), we completed human coding of their vocalizations at 12 months and compared the results to typically developing infants with no clinical features (TD/NCF).
MethodsWe randomly selected videos from 40 infants with TSC from the TACERN database. All 78 videos were coded in real-time in AACT (Action Analysis, Coding and Training).
ResultsEntry into the canonical stage was delayed in the great majority of the infants with TSC. The CBR for the TD/NCF infants was significantly higher than for the infants with TSC (TD/NCF mean = .346, SE = .19; TSC mean = .117, SE = .023). Volubility level in infants with TSC was less than half that of TD/NCF infants (TD/NCF mean = 9.82, SE = 5.78; TSC mean = 3.99, SE = 2.16). CBR and volubility were also lower in TSC infants than in TD/NCF infants recorded all-day at home.
ConclusionsEntry into the canonical stage was delayed, while canonical babbling ratios and volubility were low in infants with TSC. Assessing prediction of neurodevelopmental outcome using these vocal measures in combination with non-vocal measures will be the focus of planned studies in this high-risk population. | pediatrics |
10.1101/2021.01.07.21249377 | Parental feeding and childhood genetic risk for obesity: Exploring hypothetical interventions with causal inference methods | Parental feeding behaviors are common intervention targets for childhood obesity, but often only deliver small changes. Childhood BMI is partly driven by genetic effects, and the extent to which parental feeding interventions can mediate child genetic liability is not known. Here we aim to examine how potential interventions on parental feeding behaviors can mitigate some of the association between child genetic liability and BMI in early adolescence, using causal inference based methods. Data were from the Avon Longitudinal Study of Parents and Children and we quantified the interventional disparity measure of child genetic risk for BMI (PRS-BMI) on objectively BMI at 12 years, if we were to intervene on parental feeding styles measured when children were 10-11 years (n=4,248). Results are presented as Adjusted Total Association (Adj-Ta) between genetic liability and BMI at 12 years, versus the Interventional Disparity Measure Direct Effect (IDM-DE), which represents the association, that would remain, had we intervened on the parental feeding. For children with the top quintile of genetic liability, an intervention shifting parental feeding to the levels of children with lowest genetic risk, resulted in a difference of 0.81 kg/m2 in BMI at 12y (Adj-Ta= 3.27, 95%CI: 3.04, 3.49; versus IDM-DE=2.46, 95%CI: 2.24, 2.67). Findings suggest that parental feeding interventions have the potential to buffer some of the genetic liability for childhood obesity. Further, we highlight a novel way to analyze potential interventions for health conditions only using secondary data analyses, by combining methodology from statistical genetics and social epidemiology. | pediatrics |
10.1101/2021.01.06.21249368 | Optimal design for phase 2 studies of SARS-CoV-2 antiviral drugs | A consensus methodology for pharmacometric assessment of candidate SARS-CoV-2 antiviral drugs would be useful for comparing trial results and improving trial design. The time to viral clearance, assessed by serial qPCR of nasopharyngeal swab samples, has been the most widely reported measure of virological response in clinical trials, but it has not been compared formally with other metrics, notably model-based estimates of the rate of viral clearance. We analysed prospectively gathered viral clearance profiles from 280 infection episodes in vaccinated and unvaccinated individuals. We fitted different phenomenological pharmacodynamic models (single exponential decay, bi-exponential, penalised splines) and found that the clearance rate, estimated from a mixed effects single exponential decay model, is a robust pharmacodynamic summary of viral clearance. The rate of viral clearance, estimated from viral densities during the first week following peak viral load, provides increased statistical power (reduced type 2 error) compared with time to clearance. We recommend that pharmacometric antiviral assessments should be conducted in early illness with serial qPCR samples taken over one week. | pharmacology and therapeutics |
10.1101/2021.01.06.21249368 | Optimal design for phase 2 studies of SARS-CoV-2 antiviral drugs | A consensus methodology for pharmacometric assessment of candidate SARS-CoV-2 antiviral drugs would be useful for comparing trial results and improving trial design. The time to viral clearance, assessed by serial qPCR of nasopharyngeal swab samples, has been the most widely reported measure of virological response in clinical trials, but it has not been compared formally with other metrics, notably model-based estimates of the rate of viral clearance. We analysed prospectively gathered viral clearance profiles from 280 infection episodes in vaccinated and unvaccinated individuals. We fitted different phenomenological pharmacodynamic models (single exponential decay, bi-exponential, penalised splines) and found that the clearance rate, estimated from a mixed effects single exponential decay model, is a robust pharmacodynamic summary of viral clearance. The rate of viral clearance, estimated from viral densities during the first week following peak viral load, provides increased statistical power (reduced type 2 error) compared with time to clearance. We recommend that pharmacometric antiviral assessments should be conducted in early illness with serial qPCR samples taken over one week. | pharmacology and therapeutics |
10.1101/2021.01.06.21249368 | Characterising SARS-CoV-2 viral clearance kinetics to improve the design of antiviral pharmacometric studies | A consensus methodology for pharmacometric assessment of candidate SARS-CoV-2 antiviral drugs would be useful for comparing trial results and improving trial design. The time to viral clearance, assessed by serial qPCR of nasopharyngeal swab samples, has been the most widely reported measure of virological response in clinical trials, but it has not been compared formally with other metrics, notably model-based estimates of the rate of viral clearance. We analysed prospectively gathered viral clearance profiles from 280 infection episodes in vaccinated and unvaccinated individuals. We fitted different phenomenological pharmacodynamic models (single exponential decay, bi-exponential, penalised splines) and found that the clearance rate, estimated from a mixed effects single exponential decay model, is a robust pharmacodynamic summary of viral clearance. The rate of viral clearance, estimated from viral densities during the first week following peak viral load, provides increased statistical power (reduced type 2 error) compared with time to clearance. We recommend that pharmacometric antiviral assessments should be conducted in early illness with serial qPCR samples taken over one week. | pharmacology and therapeutics |
10.1101/2021.01.06.21249354 | Blood omega-3 fatty acids and death from COVID-19: A Pilot Study | Very-long chain omega-3 fatty acids (EPA and DHA) have anti-inflammatory properties that may help reduce morbidity and mortality from COVID-19 infection. We conducted a pilot study in 100 patients to test the hypothesis that RBC EPA+DHA levels (the Omega-3 Index, O3I) would be inversely associated with risk for death by analyzing the O3I in banked blood samples drawn at hospital admission. To have adequate power (>80%) in this pilot study, we pre-specified a significance level of 0.10. Fourteen patients died, one of 25 in quartile 4 (Q4) (O3I [≥]5.7%) and 13 of 75 in Q1-3. After adjusting for age and sex, the odds ratio for death in patients with an O3I in Q4 vs Q1-3 was 0.25, p=0.07. Thus, we have suggestive evidence that the risk for death from COVID-19 was lower in those with the highest O3I levels. These preliminary findings need to be confirmed in larger studies. | nutrition |
10.1101/2021.01.06.21249118 | Knowledge, attitude, and practices regarding COVID-19: A study on workers from a food industry in Bangladesh. | While people around the world are terrified of the global pandemic coronavirus disease 2019 (COVID-19) and are dying for a permanent solution, undertaking preventive safety measures are said to be the most effective way to stay away from it. Peoples adherences to these measures are broadly dependent on their knowledge, attitude, and practices (KAP). People working in the food industries must be extra cautious during this time because they are in close proximity to consumable items. The present study was designed to evaluate food handlers knowledge, attitude, and practices regarding COVID-19 in different food industries in Bangladesh. A number of 400 food handlers from 15 food industries took part in this online-based study. The information was collected from the participants through a questionnaire prepared in Google form. With a correct response rate of about 90% on average (knowledge 89.7%, attitude 93%, practices 88.2%), the participants showed an acceptable of KAP regarding COVID-19. Education and working experiences had a significant association with the total KAP scores (p < 0.05). The findings may assist public health professionals and practitioners in developing targeted strategies for implementing such studies in other industrial sectors and taking appropriate measures based on the KAP studies. | occupational and environmental health |
10.1101/2021.01.06.21249118 | Knowledge, attitude, and practices regarding COVID-19: A study on food handlers in a joint venture food industry in Dhaka, Bangladesh. | While people around the world are terrified of the global pandemic coronavirus disease 2019 (COVID-19) and are dying for a permanent solution, undertaking preventive safety measures are said to be the most effective way to stay away from it. Peoples adherences to these measures are broadly dependent on their knowledge, attitude, and practices (KAP). People working in the food industries must be extra cautious during this time because they are in close proximity to consumable items. The present study was designed to evaluate food handlers knowledge, attitude, and practices regarding COVID-19 in different food industries in Bangladesh. A number of 400 food handlers from 15 food industries took part in this online-based study. The information was collected from the participants through a questionnaire prepared in Google form. With a correct response rate of about 90% on average (knowledge 89.7%, attitude 93%, practices 88.2%), the participants showed an acceptable of KAP regarding COVID-19. Education and working experiences had a significant association with the total KAP scores (p < 0.05). The findings may assist public health professionals and practitioners in developing targeted strategies for implementing such studies in other industrial sectors and taking appropriate measures based on the KAP studies. | occupational and environmental health |
10.1101/2021.01.06.21249118 | Current state of COVID-19 knowledge, attitude, practices, and associated factors among Bangladeshi food handlers from various food industries. | While people around the world are terrified of the global pandemic coronavirus disease 2019 (COVID-19) and are dying for a permanent solution, undertaking preventive safety measures are said to be the most effective way to stay away from it. Peoples adherences to these measures are broadly dependent on their knowledge, attitude, and practices (KAP). People working in the food industries must be extra cautious during this time because they are in close proximity to consumable items. The present study was designed to evaluate food handlers knowledge, attitude, and practices regarding COVID-19 in different food industries in Bangladesh. A number of 400 food handlers from 15 food industries took part in this online-based study. The information was collected from the participants through a questionnaire prepared in Google form. With a correct response rate of about 90% on average (knowledge 89.7%, attitude 93%, practices 88.2%), the participants showed an acceptable of KAP regarding COVID-19. Education and working experiences had a significant association with the total KAP scores (p < 0.05). The findings may assist public health professionals and practitioners in developing targeted strategies for implementing such studies in other industrial sectors and taking appropriate measures based on the KAP studies. | occupational and environmental health |
10.1101/2021.01.06.21249185 | Folate (MTHFR C677T and MTRR A66G) gene polymorphisms and risk of prostate cancer: a case-control study with an updated meta-analysis | IntroductionMethylenetetrahydrofolate reductase (MTHFR) and methionine synthase reductase (MTRR) are the key enzymes of the folate pathway, which involved in the DNA methylation. DNA methylation may affect the stability and integrity of DNA, that supposed to play a pivotal role in carcinogenesis. So, we aimed to investigate the association of MTHFR C677T and MTRR A66G gene polymorphisms with susceptibility to prostate cancer in North Indian population. We also performed meta-analyses of published literatures on these polymorphisms to evaluate their association with prostate cancer.
MethodsWe genotyped MTHFR C677T and MTRR A66G gene polymorphisms in 147 prostate cancer cases and 147 healthy controls using PCR-RFLP methods. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated for risk estimation. For meta-analysis different databases were searched and all statistical analysis were performed using Open Meta-Analyst software.
ResultsThe present case control study revealed that the T allele (OR= 1.67; 95% CI: 0.99-2.84, p= 0.05), CT genotype (OR= 1.92; 95% CI: 1.06-3.48, p= 0.02), and dominant (TT+CT) model (OR= 1.85; 95% CI: 1.05-3.30, p= 0.03) of MTHFR C677T gene polymorphism and G allele (OR= 1.92; 95% CI: 1.35-2.73, p= 0.0002) of MTRR A66G gene polymorphism were significantly associated with prostate cancer susceptibility. Meta-analyses of MTHFR C677T and MTRR A66G gene polymorphisms showed no significant association between these polymorphisms and prostate cancer risk in overall or in subgroup meta-analysis stratified by ethnicity.
ConclusionMTHFR C677T and MTRR A66G gene polymorphisms seem to play a significant role in prostate cancer susceptibility in North Indian population, while results of meta-analysis revealed no association between MTHFR C677T and MTRR A66G gene polymorphisms and prostate cancer susceptibility. | oncology |
10.1101/2021.01.06.21249303 | Socioeconomic Disparities in the Effects of Pollution on Spread of Covid-19: Evidence from US Counties | This paper explores disparities in the effect of pollution on confirmed cases of Covid-19 based on counties socioeconomic and demographic characteristics. Using data on all US counties on a daily basis over the year 2020 and applying a rich panel data fixed effect model, we document that: 1) there are discernible social and demographic disparities in the spread of Covid-19. Blacks, low educated, and poorer people are at higher risks of being infected by the new disease. 2) The criteria pollutants including Ozone, CO, PM10, and PM2.5 have the potential to accelerate the outbreak of the novel coronavirus. 3) The disadvantaged population is more vulnerable to the effects of pollution on the spread of coronavirus. Specifically, the effects of pollution on confirmed cases become larger for blacks, low educated, and counties with lower average wages in 2019. | health economics |
10.1101/2021.01.07.21249366 | Quarantine fatigue thins fat-tailed coronavirus impacts in U.S. cities by making epidemics inevitable | We use detailed location data to show that contacts between individuals in most U.S. cities and counties are fat tailed, suggesting that the fat tails documented in a small number of superspreading clusters are widespread. We integrate these results into a stochastic compartmental model to show that COVID-19 cases were also fat tailed for many U.S. cities for several weeks in the spring and summer. Due to epidemiological thresholds, fat-tailed cases would have been more prevalent if not for the gradual increase in contact rates throughout the summer that made outbreaks more certain. | infectious diseases |
10.1101/2021.01.07.21249366 | Quarantine fatigue thins fat-tailed coronavirus impacts in U.S. cities by making epidemics inevitable | We use detailed location data to show that contacts between individuals in most U.S. cities and counties are fat tailed, suggesting that the fat tails documented in a small number of superspreading clusters are widespread. We integrate these results into a stochastic compartmental model to show that COVID-19 cases were also fat tailed for many U.S. cities for several weeks in the spring and summer. Due to epidemiological thresholds, fat-tailed cases would have been more prevalent if not for the gradual increase in contact rates throughout the summer that made outbreaks more certain. | infectious diseases |
10.1101/2021.01.06.20248960 | Impact of B.1.1.7 variant mutations on antibody recognition of linear SARS-CoV-2 epitopes | In 579 COVID patients samples collected between March and July of 2020, we examined the effects of non-synonymous mutations harbored by the circulating B.1.1.7 strain on linear antibody epitope signal for spike glycoprotein and nucleoprotein. At the antigen level, the mutations only substantially reduced signal in 0.5% of the population. Although some epitope mutations reduce measured signal in up to 6% of the population, these are not the dominant epitopes for their antigens. Given dominant epitope patterns observed, our data suggest that the mutations would not result in immune evasion of linear epitopes for a large majority of these COVID patients. | infectious diseases |
10.1101/2021.01.07.21249116 | Multi-organ complement deposition in COVID-19 patients | BackgroundIncreased levels of circulating complement activation products have been reported in COVID-19 patients, but only limited information is available on complement involvement at tissue level. The mechanisms and pathways of local complement activation remain unclear.
MethodsWe performed immunofluorescence analyses of autopsy specimens of lungs, kidney and liver from nine COVID-19 patients who died of acute respiratory failure. Snap-frozen samples embedded in OCT were stained with antibodies against complement components and activation products, IgG and spike protein of SARS-CoV-2.
FindingsLung deposits of C1q, C4, C3 and C5b-9 were localized in the capillaries of the interalveolar septa and on alveolar cells. IgG displayed a similar even distribution, suggesting classical pathway activation. The spike protein is a potential target of IgG, but its uneven distribution suggests that other viral and tissue molecules may be targeted by IgG. Factor B deposits were also seen in COVID-19 lungs and are consistent with activation of the alternative pathway, whereas MBL and MASP-2 were hardly detectable. Analysis of kidney and liver specimens mirrored findings observed in the lung. Complement deposits were seen on tubules and vessels of the kidney with only mild C5b-9 staining in glomeruli, and on hepatic artery and portal vein of the liver.
InterpretationComplement deposits in different organs of deceased COVID-19 patients caused by activation of the classical and alternative pathways support the multi-organ nature of the disease.
FundingGrants from the Italian Ministry of Health (COVID-2020-12371808) to PLM and National Institutes of Health HL150146 to NP are gratefully acknowledged. | allergy and immunology |
10.1101/2021.01.06.20249026 | Recurrent dissemination of SARS-CoV-2 through the Uruguayan-Brazilian border | BackgroundUruguay is one of the few countries in the Americas that successfully contained the COVID-19 epidemic during the first half of 2020. Nevertheless, the intensive human mobility across the dry border with Brazil is a major challenge for public health authorities. We aimed to investigate the origin of SARS-CoV-2 strains detected in Uruguayan localities bordering Brazil as well as to measure the viral flux across this [~]1,100 km uninterrupted dry frontier.
MethodsUsing complete SARS-CoV-2 genomes from the Uruguayan-Brazilian bordering region and phylogeographic analyses, we inferred the virus dissemination frequency between Brazil and Uruguay and characterized local outbreak dynamics during the first months (May-July) of the pandemic.
FindingsPhylogenetic analyses revealed multiple introductions of SARS-CoV-2 Brazilian lineages B.1.1.28 and B.1.1.33 into Uruguayan localities at the bordering region. The most probable sources of viral strains introduced to Uruguay were the Southeast Brazilian region and the state of Rio Grande do Sul. Some of the viral strains introduced in Uruguayan border localities between early May and mid-July were able to locally spread and originated the first outbreaks detected outside the metropolitan region. The viral lineages responsible for Uruguayan suburban outbreaks were defined by a set of between four and 11 mutations (synonymous and non-synonymous) respect to the ancestral B.1.1.28 and B.1.1.33 viruses that arose in Brazil, supporting the notion of a rapid genetic differentiation between SARS-CoV-2 subpopulations spreading in South America.
InterpretationAlthough Uruguayan borders have remained essentially closed to non-Uruguayan citizens, the inevitable flow of people across the dry border with Brazil allowed the repeated entry of the virus into Uruguay and the subsequent emergence of local outbreaks in Uruguayan border localities. Implementation of coordinated bi-national surveillance systems are crucial to achieve an efficient control of the SARS-CoV-2 spread across this kind of highly permeable borderland regions around the world.
Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSince the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative agent of coronavirus disease 19 (COVID-19), was first detected in South America on February 26, 2020, it has rapidly spread through the region, causing nearly 350,000 deaths by December, 2020. In contrast to most American countries, Uruguay avoided an early exponential growth of SARS-CoV-2 cases and during the first six months of the pandemic it registered the lowest incidence of SARS-CoV-2 cases and deaths among South American countries. The intensive cross-border human mobility through the [~]1,100 km uninterrupted dry frontier between Uruguay and Brazil, might poses a major challenge for long-term control of the epidemic in Uruguay. Previous genomic studies conducted in Uruguay have analyzed sequences mostly sampled at the capital city, Montevideo, and detected prevalent SARS-CoV-2 lineages different from those described in Brazil, thus finding no evidence of frequent viral exchanges between these countries.
Added value of this studyHere we present the first genomic study of SARS-CoV-2 strains detected in different Uruguayan and Brazilian localities along the bordering region. The samples analyzed include 30% (n = 59) of all laboratory confirmed SARS-CoV-2 cases from Uruguayan departments at the Brazilian border between March and July, 2020, as well as 68 SARS-CoV-2 sequences from individuals diagnosed in the southernmost Brazilian state of Rio Grande do Sul between March and August, 2020. We demonstrate that SARS-CoV-2 viral lineages that widely spread in the Southeastern Brazilian region (B.1.1.28 and B.1.1.33) were also responsible for most viral infections in Rio Grande do Sul and neighboring Uruguayan localities. We further uncover that major outbreaks detected in Uruguayan localities bordering Brazil in May and June, 2020, were originated from two independent introduction events of the Brazilian SARS-CoV-2 lineage B.1.1.33, unlike previous outbreaks in the Uruguayan metropolitan region that were seeded by European SARS-CoV-2 lineages.
Implications of all the available evidenceOur findings confirm that although Uruguayan borders have remained essentially closed to non-Uruguayan citizens, dissemination of SARS-CoV-2 across the Uruguayan-Brazilian frontier was not fully suppressed and had the potential to ignite local transmission chains in Uruguay. These findings also highlight the relevance of implementing bi-national public health cooperation workforces combining epidemiologic and genomic data to monitor the viral spread throughout this kind of highly permeable dry frontiers around the world. | epidemiology |
10.1101/2021.01.06.21249357 | Assessment of fractional anisotropy outcomes in combat sport athletes with mild traumatic brain injury | AO_SCPLOWBSTRACTC_SCPLOWThe practice of combat sports increases the risk of suffering white matter injuries. That is why, it is required the early damage detection to determine to what extent the athlete may be active preserving their performance and health status. The integrity of the white matter can be quantitatively characterized in diffusion tensor images, using fractional anisotropy. This study aims at characterizing the fractional anisotropy of white matter injuries in combat athletes that are exposed to repetitive trauma and also, to detect changes in fractional anisotropy between cerebral hemispheres with and without lesions. It is proposed a global and structural analysis of the hemispheres, as well as the selection of ROI in the lesions. 14 athletes, from Boxing, Karate and Taekwondo sports, participated. The sample was divided into two groups of seven subjects each: Injured (23.428{+/-}4.157 years old) and Healthy (24.285{+/-}5.023 years old) paired by sport denomination. Diffusion tensor images were used to obtain FA values in the analysis of the hemispheres and lesions. Global and structural analysis of the hemispheres did not detect the presence of white matter lesions; however, the use of ROI selection permitted maximum approximation of the injuries location. It also improved the breakdown of FA values as it allows a local analysis of the lesion. As an additional result, there were found ROIs values, FAmed = 0.454{+/-}0.062, which exceed the average fractional anisotropy of the white matter. The cohesion of acute and chronic phase lesions were found in the same subject. The apparently contradictory results in FA values are related to the stage of the lesions. | sports medicine |
10.1101/2021.01.07.21249381 | Comparing the age and sex trajectories of SARS-CoV-2 morbidity with other respiratory pathogens points to potential immune mechanisms. | Comparing age and sex differences in SARS-CoV-2 hospitalization and mortality with influenza and other health outcomes opens the way to generating hypotheses as to the underlying mechanisms, building on the extraordinary advances in immunology and physiology that have occurred over the last year. Notable departures in health outcomes starting around puberty suggest that burdens associated with influenza and other causes are reduced relative to the two emergent coronaviruses over much of adult life. Two possible hypotheses could explain this: protective adaptive immunity for influenza and other infections, or greater sensitivity to immunosenescence in the coronaviruses. Comparison of sex differences suggest an important role for adaptive immunity; but immunosenescence might also be relevant, if males experience faster immunosenescence. Involvement of the renin-angiotensin-system in SARS-CoV-2 infection might drive high sensitivity to disruptions of homeostasis. Overall, these results highlight the long tail of vulnerability in the age profile relevant to the emergent coronaviruses, which more transmissible variants have the potential to uncover at the younger end of the scale, and aging populations will expose at the other end of the scale. | infectious diseases |
10.1101/2021.01.07.21249121 | Generalized Prediction of Shock in Intensive Care Units using Deep Learning | Early prediction of hemodynamic shock in the ICU can save lives. Several studies have leveraged a combination of vitals, lab investigations, and clinical data to construct early warning systems for shock. However, these have a limited potential of generalization to diverse settings due to reliance on non-real-time data. Monitoring data from vitals can provide an early real-time prediction of Hemodynamic shock which can precede the clinical diagnosis to guide early therapy decisions. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups (adult and pediatric), ICU-types, and geographies. We trained, validated, and tested a shock prediction model on the publicly available eICU dataset on 208 ICUs across the United States. Data from 156 hospitals passed the eligibility criteria for cohort building. These were split hospital-wise in a five-fold training-validation-test set. External validation of the model was done on a pediatric ICU in New Delhi and MIMIC-III database with more than 0.23 million and one million patient-hours vitals data, respectively. Our models identified 92% of all the shock events more than 8 hours in advance with AUROC of 86 %(SD= 1.4) and AUPRC of 93% (SD =1.2) on the eICU testing set. An AUROC of 87 % (SD =1.8), AUPRC 92 % (SD=1.6) were obtained in external validation on the MIMIC-III cohort. The New Delhi Pediatric SafeICU data achieved an AUROC of 87 % (SD =4) AUPRC 91% (SD=3), despite being completely different geography and age group. In this first, we demonstrate a generalizable model for predicting shock, and algorithms are publicly available as a pre-configured Docker environment at https://github.com/tavlab-iiitd/ShoQPred. | intensive care and critical care medicine |
10.1101/2021.01.07.21249121 | Generalized Prediction of Shock in Intensive Care Units using Deep Learning | Early prediction of hemodynamic shock in the ICU can save lives. Several studies have leveraged a combination of vitals, lab investigations, and clinical data to construct early warning systems for shock. However, these have a limited potential of generalization to diverse settings due to reliance on non-real-time data. Monitoring data from vitals can provide an early real-time prediction of Hemodynamic shock which can precede the clinical diagnosis to guide early therapy decisions. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups (adult and pediatric), ICU-types, and geographies. We trained, validated, and tested a shock prediction model on the publicly available eICU dataset on 208 ICUs across the United States. Data from 156 hospitals passed the eligibility criteria for cohort building. These were split hospital-wise in a five-fold training-validation-test set. External validation of the model was done on a pediatric ICU in New Delhi and MIMIC-III database with more than 0.23 million and one million patient-hours vitals data, respectively. Our models identified 92% of all the shock events more than 8 hours in advance with AUROC of 86 %(SD= 1.4) and AUPRC of 93% (SD =1.2) on the eICU testing set. An AUROC of 87 % (SD =1.8), AUPRC 92 % (SD=1.6) were obtained in external validation on the MIMIC-III cohort. The New Delhi Pediatric SafeICU data achieved an AUROC of 87 % (SD =4) AUPRC 91% (SD=3), despite being completely different geography and age group. In this first, we demonstrate a generalizable model for predicting shock, and algorithms are publicly available as a pre-configured Docker environment at https://github.com/tavlab-iiitd/ShoQPred. | intensive care and critical care medicine |
10.1101/2021.01.07.21249121 | Generalized Prediction of Hemodynamic Shock in Intensive Care Units | Early prediction of hemodynamic shock in the ICU can save lives. Several studies have leveraged a combination of vitals, lab investigations, and clinical data to construct early warning systems for shock. However, these have a limited potential of generalization to diverse settings due to reliance on non-real-time data. Monitoring data from vitals can provide an early real-time prediction of Hemodynamic shock which can precede the clinical diagnosis to guide early therapy decisions. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups (adult and pediatric), ICU-types, and geographies. We trained, validated, and tested a shock prediction model on the publicly available eICU dataset on 208 ICUs across the United States. Data from 156 hospitals passed the eligibility criteria for cohort building. These were split hospital-wise in a five-fold training-validation-test set. External validation of the model was done on a pediatric ICU in New Delhi and MIMIC-III database with more than 0.23 million and one million patient-hours vitals data, respectively. Our models identified 92% of all the shock events more than 8 hours in advance with AUROC of 86 %(SD= 1.4) and AUPRC of 93% (SD =1.2) on the eICU testing set. An AUROC of 87 % (SD =1.8), AUPRC 92 % (SD=1.6) were obtained in external validation on the MIMIC-III cohort. The New Delhi Pediatric SafeICU data achieved an AUROC of 87 % (SD =4) AUPRC 91% (SD=3), despite being completely different geography and age group. In this first, we demonstrate a generalizable model for predicting shock, and algorithms are publicly available as a pre-configured Docker environment at https://github.com/tavlab-iiitd/ShoQPred. | intensive care and critical care medicine |
10.1101/2021.01.07.21249121 | Generalized Prediction of Hemodynamic Shock in Intensive Care Units | Early prediction of hemodynamic shock in the ICU can save lives. Several studies have leveraged a combination of vitals, lab investigations, and clinical data to construct early warning systems for shock. However, these have a limited potential of generalization to diverse settings due to reliance on non-real-time data. Monitoring data from vitals can provide an early real-time prediction of Hemodynamic shock which can precede the clinical diagnosis to guide early therapy decisions. Generalization across age and geographical context is an unaddressed challenge. In this retrospective observational study, we built real-time shock prediction models generalized across age groups (adult and pediatric), ICU-types, and geographies. We trained, validated, and tested a shock prediction model on the publicly available eICU dataset on 208 ICUs across the United States. Data from 156 hospitals passed the eligibility criteria for cohort building. These were split hospital-wise in a five-fold training-validation-test set. External validation of the model was done on a pediatric ICU in New Delhi and MIMIC-III database with more than 0.23 million and one million patient-hours vitals data, respectively. Our models identified 92% of all the shock events more than 8 hours in advance with AUROC of 86 %(SD= 1.4) and AUPRC of 93% (SD =1.2) on the eICU testing set. An AUROC of 87 % (SD =1.8), AUPRC 92 % (SD=1.6) were obtained in external validation on the MIMIC-III cohort. The New Delhi Pediatric SafeICU data achieved an AUROC of 87 % (SD =4) AUPRC 91% (SD=3), despite being completely different geography and age group. In this first, we demonstrate a generalizable model for predicting shock, and algorithms are publicly available as a pre-configured Docker environment at https://github.com/tavlab-iiitd/ShoQPred. | intensive care and critical care medicine |
10.1101/2021.01.05.20248921 | A Multiple Linear Regression Analysis of Rural-Urban COVID-19 Risk Disparities in Texas | As the number of COVID-19 cases in the U.S. rises, the differential impact of the pandemic in urban and rural regions becomes more pronounced, and the major factors relating to this difference remain unclear. Using the 254 counties of Texas as units of analysis, we utilized multiple linear regression to investigate the influence of 83 county-level predictor variables including race demographics, age demographics, healthcare and financial status, and prevalence of and mortality rate from COVID-19 risk factors on the incidence rate and case fatality rate from COVID-19 in Texas on September 15, 2020. Here, we report that urban counties experience, on average, 41.1% higher incidence rates from COVID-19 than rural counties and 34.7% lower case fatality rates. Through comparisons between our models, we found that this difference was largely attributable to four major predictor variables: namely, the proportion of elderly residents, African American residents, and Hispanic residents, and the presence of large nursing homes. According to our models, counties with high incidence rates of COVID-19 are predicted to have high proportions of African American residents and Hispanic residents coupled with low proportions of elderly residents. Furthermore, we found that counties with the highest case fatality rates are predicted to have high proportions of elderly residents, obese residents, and Hispanic residents, coupled with low proportions of residents ages 20-39 and residents who report smoking cigarettes. In our study, major variables and their effects on COVID-19 risk are quantified, highlighting the most vulnerable populations and regions of Texas. | epidemiology |
10.1101/2021.01.07.21249394 | A two-phase stochastic dynamic model for COVID-19 mid-term policy recommendations in Greece: a pathway towards mass vaccination | From November 7th, 2020, Greece adopted a second nationwide lockdown policy to mitigate the transmission of SARS-CoV-2 (the first took place from March 23rd till May 4th, 2020), just as the second wave of COVID-19 was advancing, as did other European countries. In the light of the very promising voluntary mass vaccination, which will start in January 2021, it is of utmost importance for the country to plan to complement vaccination with mid-term Non-Pharmaceutical Interventions (NPIs). The objective is to minimize human losses and to limit social and economic costs. In this paper a two-phase stochastic dynamic network compartmental model (a pre-vaccination SEIR until February 15th, 2021 and a post-vaccination SVEIR from February 15th, 2021 to June 30th, 2021) is developed. Three scenarios are assessed in the first phase: (a) a baseline scenario, which lifts the national lockdown and all NPIs on January 2021, (b) a "semi-lockdown" scenario with school opening, partial retail sector operation, universal mask wearing and social distancing/teleworking on January 2021 and (c) a "rolling lockdown" scenario combining a partial lifting of measures in January 2021 followed by a third imposed nationwide lockdown in February 2021. In the second phase three scenarios with different vaccination rates are assessed. Publicly available data along with some preliminary first results of the SHARE COVID-19 survey conducted in Greece are used as input. The results regarding the first phase indicate that the "semi-lockdown" scenario outperforms the third lockdown scenario (5.7% less expected fatalities), whereas in the second phase it is of great importance to ensure a sufficient vaccine supply and high vaccination rates. | epidemiology |
10.1101/2021.01.07.20248623 | Nuclear Morphometry is a superior Prognostic Predictor in comparison to Histological grading in Renal cell Carcinoma: A Retrospective Clinico-pathological study | BackgroundRenal cell carcinoma (RCC) comprises of a spectrum of clinico-pathologically distinct entities thereby making it difficult to accurately predict the clinical outcome. Though many predictive factors have been described in literature, tumor stage and nuclear grade have been established to consistently correlate with the tumor behaviour. However, tumors in the same stage have shown to behave differently. Similarly subjectivity and lack of reproducibility in nuclear grade mandates use of more objective parameters such as digital nuclear morphometry which could provide consistent and more reliable results in predicting prognosis. The study was conducted with the main objective of comparing the histological grade and the nuclear morphometric variables in RCC for predicting the clinical outcome.
Material and methodsA total of 219 cases of renal tumors in adults were retrieved retrospectively from the archives of pathology department in Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow and their clinical, gross and microscopic features were noted. Nuclear grading was done in 181 cases of clear cell and papillary RCC of which computer-assisted morphometry for various nuclear parameters was done in 100 cases where a follow-up data of at least 3 years was available. Nuclear grade and morphometric parameters were correlated statistically with the clinical outcome of the patients.
ResultsHistological nuclear grade did not show statistically significant correlation with progression free survival (PFS). Higher values of mean nuclear area, mean nuclear circumference, mean nuclear major diameter and mean nuclear minor diameter were significant predictors of PFS with a strong inverse correlation.
ConclusionNuclear morphometry is a more reliable predictor of clinical outcome in patients of RCC when compared to histological grade and should be included in predictive model with other clinical and pathological parameters to accurately determine tumor behaviour. | pathology |
10.1101/2021.01.07.21249418 | Center-Based Experiences Implementing Strategies to Reduce Risk of Horizontal Transmission of SARS-Cov-2: Potential for Compromise of Neonatal Microbiome Assemblage | Perinatal transmission of COVID-19 is poorly understood and many neonatal intensive care units (NICU) policies minimize mother-infant contact to prevent transmission. We present our units approach and ways it may impact neonatal microbiome acquisition. We attended COVID-19 positive mothers deliveries from March-August 2020. Delayed cord clamping and skin-to-skin were avoided and infants were admitted to the NICU. No parents visits were allowed and discharge was arranged with COVID-19 negative family members. Maternal breast milk was restricted in the NICU. All twenty-one infants tested negative at 24 and 48 hours and had average hospital stays of nine days. 40% of mothers expressed breastmilk and 60% of infants were discharged with COVID-19 negative caregivers. Extended hospital stays, no skin-to-skin contact, limited maternal milk use, and discharge to caregivers outside primary residences, potentially affect the neonatal microbiome. Future studies are warranted to explore how ours and other centers similar policies influence this outcome. | pediatrics |
10.1101/2021.01.07.21249418 | Center-Based Experiences Implementing Strategies to Reduce Risk of Horizontal Transmission of SARS-Cov-2: Potential for Compromise of Neonatal Microbiome Assemblage | Perinatal transmission of COVID-19 is poorly understood and many neonatal intensive care units (NICU) policies minimize mother-infant contact to prevent transmission. We present our units approach and ways it may impact neonatal microbiome acquisition. We attended COVID-19 positive mothers deliveries from March-August 2020. Delayed cord clamping and skin-to-skin were avoided and infants were admitted to the NICU. No parents visits were allowed and discharge was arranged with COVID-19 negative family members. Maternal breast milk was restricted in the NICU. All twenty-one infants tested negative at 24 and 48 hours and had average hospital stays of nine days. 40% of mothers expressed breastmilk and 60% of infants were discharged with COVID-19 negative caregivers. Extended hospital stays, no skin-to-skin contact, limited maternal milk use, and discharge to caregivers outside primary residences, potentially affect the neonatal microbiome. Future studies are warranted to explore how ours and other centers similar policies influence this outcome. | pediatrics |
10.1101/2021.01.08.21249434 | Comparison of algorithm-based versus single-item phenotyping measures of depression and anxiety disorders in the GLAD Study cohort | BackgroundUnderstanding and improving outcomes for people with anxiety or depression often requires large studies. To increase participation and reduce costs, such research is typically unable to utilise "gold-standard" methods to ascertain diagnoses, instead relying on remote, self-report measures.
AimsTo assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.
MethodParticipants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018-2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate algorithm-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed single-item diagnoses. "Any anxiety" included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohens kappa, McNemars chi-squared, sensitivity, and specificity.
ResultsAgreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with single-item GAD did not receive an algorithm-based diagnosis. In contrast, algorithm-based diagnoses of the phobic disorders were more common than single-item diagnoses.
ConclusionsAgreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, single-item diagnoses classified most participants as having GAD, whereas algorithm-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required. | psychiatry and clinical psychology |
10.1101/2021.01.08.21249434 | Comparison of algorithm-based versus single-item phenotyping measures of depression and anxiety disorders in the GLAD Study cohort | BackgroundUnderstanding and improving outcomes for people with anxiety or depression often requires large studies. To increase participation and reduce costs, such research is typically unable to utilise "gold-standard" methods to ascertain diagnoses, instead relying on remote, self-report measures.
AimsTo assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.
MethodParticipants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018-2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate algorithm-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed single-item diagnoses. "Any anxiety" included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohens kappa, McNemars chi-squared, sensitivity, and specificity.
ResultsAgreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with single-item GAD did not receive an algorithm-based diagnosis. In contrast, algorithm-based diagnoses of the phobic disorders were more common than single-item diagnoses.
ConclusionsAgreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, single-item diagnoses classified most participants as having GAD, whereas algorithm-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required. | psychiatry and clinical psychology |
10.1101/2021.01.08.21249434 | Comparison of algorithm-based versus single-item diagnostic measures of anxiety and depression disorders in the GLAD and COPING cohorts | BackgroundUnderstanding and improving outcomes for people with anxiety or depression often requires large studies. To increase participation and reduce costs, such research is typically unable to utilise "gold-standard" methods to ascertain diagnoses, instead relying on remote, self-report measures.
AimsTo assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.
MethodParticipants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018-2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate algorithm-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed single-item diagnoses. "Any anxiety" included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohens kappa, McNemars chi-squared, sensitivity, and specificity.
ResultsAgreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with single-item GAD did not receive an algorithm-based diagnosis. In contrast, algorithm-based diagnoses of the phobic disorders were more common than single-item diagnoses.
ConclusionsAgreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, single-item diagnoses classified most participants as having GAD, whereas algorithm-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required. | psychiatry and clinical psychology |
10.1101/2021.01.07.21249389 | Computational modelling of EEG and fMRI paradigms reveals a consistent loss of pyramidal cell synaptic gain in schizophrenia | Diminished synaptic gain - the sensitivity of postsynaptic responses to neural inputs - may be a fundamental synaptic pathology in schizophrenia. Evidence for this is indirect, however. Furthermore, it is unclear whether pyramidal cells or interneurons (or both) are affected, or how these deficits relate to symptoms. Participants with schizophrenia (Scz, n=108), their relatives (n=57), and controls (n=107) underwent three electroencephalography paradigms - resting, mismatch negativity, and 40 Hz auditory steady-state response - and resting functional magnetic resonance imaging. Dynamic causal modelling was used to quantify synaptic connectivity in cortical microcircuits. Across all four paradigms, characteristic Scz data features were best explained by models with greater self-inhibition (decreased synaptic gain), in pyramidal cells. Furthermore, disinhibition in auditory areas predicted abnormal auditory perception (and positive symptoms) in Scz, in three paradigms. Thus, psychotic symptoms of Scz may result from a downregulation of inhibitory interneurons that may compensate for diminished postsynaptic gain in pyramidal cells. | psychiatry and clinical psychology |
10.1101/2021.01.07.21249383 | Quantifying non-communicable diseases' burden in Egypt using State-Space model | The study aimed to model and quantify the health burden induced by four non-communicable diseases in Egypt, the first to be conducted in the context of a less developing county. The study used the State-Space model and adopted two Bayesian methods: Particle Filter and Particle Independent Metropolis-Hastings to model and estimate the NCDs health burden trajectories. We drew on time-series data of the International Health Metric Evaluation, CAPMASs Annual Bulletin of Health Services Statistics, the World Bank, and WHO data. Both Bayesian methods showed that the burden trajectories are on the rise. Most of the findings agreed with our assumptions and are in line with the literature. Previous year burden strongly predicts the burden of the current year. High prevalence of the risk factors, disease prevalence, and the diseases severity level all increase illness burden. Years of life lost due to death has high loadings in most of the diseases. Contrary to the study assumption, results found a negative relationship between disease burden and health services utilization which can be attributed to the lack of full health insurance coverage and the pattern of health care seeking behavior in Egypt. Our study highlights that Particle Independent Metropolis-Hastings is sufficient in estimating the parameters of the study model, in the case of time-constant parameters. The study recommends using state Space models with Bayesian estimation approaches with time-series data in public health and epidemiology research. | public and global health |
10.1101/2021.01.07.21249323 | A Novel Abnormality Annotation Database for COVID-19 Affected Frontal Lung X-rays | PurposeTo advance the usage of CXRs as a viable solution for efficient COVID-19 diagnostics by providing large-scale annotations of the abnormalities in frontal CXRs in BIMCV-COVID19+ database, and to provide a robust evaluation mechanism to facilitate its usage.
Materials and MethodsWe provide the abnormality annotations in frontal CXRs by creating bounding boxes. The frontal CXRs are a part of the existing BIMCV-COVID19+ database. We also define four different protocols for robust evaluation of semantic segmentation and classification algorithms. Finally, we benchmark the defined protocols and report the results using popular deep learning models as a part of this study.
ResultsFor semantic segmentation, Mask-RCNN performs the best among all the models with a DICE score of 0.43 {+/-} 0.01. For classification, we observe that MobileNetv2 yields the best results for 2-class and 3-class classification. We also observe that deep models report a lower performance for classifying other classes apart from the COVID class.
ConclusionBy making the annotated data and protocols available to the scientific community, we aim to advance the usage of CXRs as a viable solution for efficient COVID-19 diagnostics. This large-scale data will be useful for ML algorithms and can be used for learning radiological patterns observed in COVID-19 patients. Further, the protocols will facilitate ML practitioners for unified large-scale evaluation of their algorithms.
Data Availability StatementThe data associated with this work is available here : Radiologists Annotations on COVID-19+ X-rays https://osf.io/b35xu/ via @OSFramework and http://covbase4all.igib.res.in/. | radiology and imaging |
10.1101/2021.01.07.21249323 | A Novel Abnormality Annotation Database for COVID-19 Affected Frontal Lung X-rays | PurposeTo advance the usage of CXRs as a viable solution for efficient COVID-19 diagnostics by providing large-scale annotations of the abnormalities in frontal CXRs in BIMCV-COVID19+ database, and to provide a robust evaluation mechanism to facilitate its usage.
Materials and MethodsWe provide the abnormality annotations in frontal CXRs by creating bounding boxes. The frontal CXRs are a part of the existing BIMCV-COVID19+ database. We also define four different protocols for robust evaluation of semantic segmentation and classification algorithms. Finally, we benchmark the defined protocols and report the results using popular deep learning models as a part of this study.
ResultsFor semantic segmentation, Mask-RCNN performs the best among all the models with a DICE score of 0.43 {+/-} 0.01. For classification, we observe that MobileNetv2 yields the best results for 2-class and 3-class classification. We also observe that deep models report a lower performance for classifying other classes apart from the COVID class.
ConclusionBy making the annotated data and protocols available to the scientific community, we aim to advance the usage of CXRs as a viable solution for efficient COVID-19 diagnostics. This large-scale data will be useful for ML algorithms and can be used for learning radiological patterns observed in COVID-19 patients. Further, the protocols will facilitate ML practitioners for unified large-scale evaluation of their algorithms.
Data Availability StatementThe data associated with this work is available here : Radiologists Annotations on COVID-19+ X-rays https://osf.io/b35xu/ via @OSFramework and http://covbase4all.igib.res.in/. | radiology and imaging |
10.1101/2021.01.07.21249407 | Findings from Cardiovascular Evaluation of NCAA Division I Collegiate Student-Athletes after Asymptomatic or Mildly Symptomatic SARS-CoV-2 Infection | ObjectivesThe risk of myocardial damage after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been controversial. There is an urgent need for data to support the appropriate level of cardiovascular screening for safe return-to-play. The purpose of this study is to report the incidence of abnormal cardiovascular findings in National Collegiate Athletic Association (NCAA) Division I student-athletes with a history of SARS-CoV-2 infection.
MethodsThis is a case series of student-athletes at a single NCAA Division I institution who tested positive for SARS-CoV-2 by polymerase chain reaction (PCR) or antibody testing (IgG) from 4/15/2020 to 10/31/2020. From 452 athletes who were screened, 5,124 PCR and 452 antibody tests were completed. Student-athletes were followed through 12/31/2020 (median 104 days, range 64-182 days). Cardiac work-up included clinical evaluation, troponin level, electrocardiogram (ECG), and echocardiogram. Additional work-up was ordered as clinically indicated.
Results55 student-athletes tested positive for SARS-CoV-2. Of these, 38 (69%) had symptoms of Coronavirus Disease (COVID-19), 14 (26%) had a positive IgG test, and 41 (74%) had a positive PCR test. Eight abnormal cardiovascular screening evaluations necessitated further testing including cardiac magnetic resonance imaging (cMRI). Two athletes received new cardiac diagnoses, one probable early cardiomyopathy and one pericarditis, while the remaining six had normal cardiac MRIs.
ConclusionThese data support recent publications which recommend the de-escalation of cardiovascular testing for athletes who have recovered from asymptomatic or mildly symptomatic SARS-CoV-2 infection. Continued follow-up of these athletes for sequelae of SARS-CoV-2 is critical. | sports medicine |
10.1101/2021.01.07.21249396 | Mutations that confer resistance to broadly-neutralizing antibodies define HIV-1 variants of transmitting mothers from that of non-transmitting mothers | Despite considerable reduction of mother-to-child transmission (MTCT) of HIV through use of maternal and infant antiretroviral therapy (ART), over 150,000 infants continue to become infected with HIV annually, falling far short of the World Health Organization goal of reaching <20,000 annual pediatric HIV cases worldwide by 2020. Prior to the widespread use of ART in the setting of pregnancy, over half of infants born to HIV-infected mothers were protected against HIV acquisition. Yet, the role of maternal immune factors in this protection against vertical transmission is still unclear, hampering the development of synergistic strategies to further reduce MTCT. It has been established that infant transmitted/founder (T/F) viruses are often resistant to maternal plasma, yet it is unknown if the neutralization resistance profile of circulating viruses predicts the maternal risk of transmission to her infant. In this study, we amplified HIV-1 envelope genes (env) by single genome amplification and produced representative Env variants from plasma of 19 non-transmitting mothers from the U.S. Women Infant Transmission Study (WITS), enrolled in the pre-ART era. Maternal HIV Env variants from non-transmitting mothers had similar sensitivity to autologous plasma as observed for non-transmitting variants from transmitting mothers. In contrast, infant variants were on average 30% less sensitive to paired plasma neutralization compared to non-transmitted maternal variants from both transmitting and non-transmitting mothers (p=0.015). Importantly, a signature sequence analysis revealed that motifs enriched in env sequences from transmitting mothers were associated with broadly neutralizing antibody (bnAb) resistance. Altogether, our findings suggest that circulating maternal virus resistance to bnAb-mediated neutralization, but not autologous plasma neutralization, near the time of delivery, predicts increased MTCT risk. These results caution that enhancement of maternal plasma neutralization through passive or active vaccination during pregnancy could drive the evolution of variants fit for vertical transmission.
Author SummaryDespite widespread, effective use of ART among HIV infected pregnant women, new pediatric HIV infections increase by about 150,000 every year. Thus, alternative strategies will be required to reduce MTCT and eliminate pediatric HIV infections. Interestingly, in the absence of ART, less than half of HIV-infected pregnant women will transmit HIV, suggesting natural immune protection of infants from virus acquisition. To understand the impact of maternal plasma autologous virus neutralization responses on MTCT, we compared the plasma and bnAb neutralization sensitivity of the circulating viral population present at the time of delivery in untreated, HIV-infected transmitting and non-transmitting mothers. While there was no significant difference in the ability of transmitting and non-transmitting women to neutralize their own circulating virus strains, specific genetic motifs enriched in variants from transmitting mothers were associated with resistance to bnAbs, suggesting that acquired bnAb resistance is a common feature of vertically-transmitted variants. This work suggests that enhancement of plasma neutralization responses in HIV-infected mothers through passive or active vaccination could further drive selection of variants that couldbe vertically transmitted, and cautions the use of passive bnAbs for HIV-1 prophylaxis or therapy during pregnancy. | hiv aids |
10.1101/2021.01.07.21249393 | Ultrasensitive detection of p24 in plasma samples from people with primary and chronic HIV-1 infection | HIV-1 Gag p24 has long been identified as an informative biomarker of HIV replication, disease progression and therapeutic efficacy, but the lower sensitivity of immunoassays in comparison to molecular tests and the interference with antibodies in chronic HIV infection limits its application for clinical monitoring. The development of ultrasensitive protein detection technologies may help overcoming these limitations. Here we evaluated whether immune-complex dissociation combined with ultrasensitive digital ELISA Simoa technology could be used to quantify p24 in plasma samples from people with HIV-1 infection. We found that, among different immune-complex dissociation methods, only acid-mediated dissociation was compatible with ultrasensitive p24 quantification by digital ELISA, strongly enhancing p24 detection at different stages of HIV-1 infection. We show that ultrasensitive p24 levels correlated positively with plasma HIV-RNA and HIV-DNA and negatively with CD4+ T cells in the samples from people with primary and chronic HIV-1 infection. In addition, p24 levels also correlated with plasma D-dimers and IFN levels. P24 levels sharply decreased to undetectable levels after initiation of combined antiretroviral treatment (cART). However, we identified a group of people who, 48 weeks after cART initiation, had detectable p24 levels despite having undetectable viral loads. These people had different virologic and immunologic baseline characteristics when compared with people who had undetectable p24 after cART. These results demonstrate that ultrasensitive p24 analysis provides an efficient and robust mean to monitor p24 antigen in plasma samples from people with HIV-1 infection, including during antiretroviral treatment, and may provide complementary information to other commonly used biomarkers.
ImportanceThe introduction of combined antiretroviral treatment has transformed HIV-1 infection in a manageable condition. In this context, there is a need for additional biomarkers to monitor HIV-1 residual disease or the outcome of new interventions, such as in the case of HIV cure strategies. The p24 antigen has a long half-live outside viral particles and it is therefore a very promising marker to monitor episodes of viral replication or transient activation of the viral reservoir. However, the formation of immune-complexes with anti-p24 antibodies difficult its quantification beyond acute HIV-1 infection. We show here that, upon immune-complex dissociation, new technologies allow the ultrasensitive p24 quantification in plasma samples throughout HIV-1 infection, at levels close to that of viral RNA and DNA determinations. Our results further indicate that ultrasensitive p24 quantification may have added value when used in combination with other classic clinical biomarkers. | hiv aids |
10.1101/2021.01.07.21249409 | Analysis of Intervention Effectiveness Using Early Outbreak Transmission Dynamics to Guide Future Pandemic Management and Decision-Making in Kuwait | Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction number during the initial outbreak wave. Herein we use a modified susceptible-exposed-asymptomatic-infectious-removed (SEAIR) transmission model to estimate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait. We fit case data from the first 96 days in the model to estimate the basic reproduction number and used Google mobility data to refine community contact matrices. The SEAIR modelled scenarios allow for the analysis of various interventions to determine their effectiveness. The model can help inform future pandemic wave management, not only in Kuwait but for other countries as well. | infectious diseases |
10.1101/2021.01.07.21249406 | High prevalence of long-term psychophysical olfactory dysfunction in patients with COVID-19 | This study prospectively assessed the long-term prevalence of self-reported and psychophysically measured olfactory dysfunction in subjects with mild-to-moderate COVID-19. Self-reported smell or taste impairment was prospectively evaluated by SNOT-22 at diagnosis, 4-week, 8-week, and 6-month. At 6 months from the diagnosis, psychophysical evaluation of olfactory function was also performed using the 34-item culturally adapted University of Pennsylvania Smell Identification Test (CA-UPSIT). 145 completed both the 6-month subjective and psychophysical olfactory evaluation. According to CA-UPSIT, 87 subjects (60.0%) exhibited some smell dysfunction, with 54 (37.2) being mildly microsmic, 16 (11.0%) moderately microsmic, 7 (4.8%) severely microsmic, and 10 patients (6.9%) being anosmic. At the time CA-UPSIT was administered, a weak correlation was observed between the self-reported alteration of sense of smell or taste and olfactory test scores (Spearmans r=-0.26). Among 112 patients who self-reported normal sense of smell at last follow-up, CA-UPSIT revealed normal smell in 46 (41.1%), mild microsmia in 46 (41.1%), moderate microsmia in 11 (9.8%), severe microsmia in 3 (2.3%), and anosmia in 6 (5.4%) patients; however, of those patients self-reporting normal smell but who were found to have hypofunction on testing, 62 out of 66 had self-reported reduction in sense of smell or taste at an earlier time point. Despite most patients report a subjectively normal sense of smell, we observed a high percentage of persistent smell dysfunction at 6 months from the diagnosis of SARS-CoV-2 infection, with 11.7% of patients being anosmic or severely microsmic. These data highlight a significant long-term rate of smell alteration in patients with previous SARS-CoV-2 infection. | infectious diseases |
10.1101/2021.01.07.21249410 | Increased Risk of Autopsy-Proven Pneumonia with Sex, Season and Neurodegenerative Disease | There has been a markedly renewed interest in factors associated with pneumonia, a leading cause of death worldwide, due to its frequent concurrence with pandemics of influenza and Covid-19 disease. Reported predisposing factors to both bacterial pneumonia and pandemic viral lower respiratory infections are wintertime occurrence, older age, obesity, pre-existing cardiopulmonary conditions and diabetes. Also implicated are age-related neurodegenerative diseases that cause parkinsonism and dementia. We investigated the prevalence of autopsy-proven pneumonia in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), a longitudinal clinicopathological study, between the years 2006 and 2019 and before the beginning of the Covid-19 pandemic. Of 691 subjects dying at advanced ages (mean 83.4), pneumonia was diagnosed postmortem in 343 (49.6%). There were 185 subjects without dementia or parkinsonism while clinicopathological diagnoses for the other subjects included 319 with Alzheimers disease dementia, 127 with idiopathic Parkinsons disease, 72 with dementia with Lewy bodies, 49 with progressive supranuclear palsy and 78 with vascular dementia. Subjects with one or more of these neurodegenerative diseases all had higher pneumonia rates, ranging between 50 and 61%, as compared to those without dementia or parkinsonism (40%). In multivariable logistic regression models, male sex and a non-summer death both had independent contributions (ORs of 1.67 and 1.53) towards the presence of pneumonia at autopsy while the absence of parkinsonism or dementia was a significant negative predictor of pneumonia (OR 0.54). Male sex, dementia and parkinsonism may also be risk factors for Covid-19 pneumonia. The apolipoprotein E4 allele, as well as obesity, chronic obstructive pulmonary disease, diabetes, hypertension, congestive heart failure, cardiomegaly and cigarette smoking history, were not significantly associated with pneumonia, in contradistinction to what has been reported for Covid-19 disease. | infectious diseases |
10.1101/2021.01.08.21249426 | Ultrasensitive RNA biosensors for SARS-CoV-2 detection in a simple color and luminescence assay | The COVID-19 pandemic underlines the need for versatile diagnostic strategies. Here, we have designed and developed toehold RNA-based sensors for direct and ultrasensitive SARS-CoV-2 RNA detection. In our assay, isothermal amplification of a fragment of SARS-CoV-2 RNA coupled with activation of our biosensors leads to a conformational switch in the sensor. This leads to translation of a reporter-protein e.g. LacZ or Nano-lantern that is easily detected using color/luminescence. This response can be visualized by the human eye, or a simple cell phone camera as well as quantified using a spectrophotometer/luminometer. By optimizing RNA-amplification and biosensor-design, we have generated a highly-sensitive diagnostic assay; with sensitivity down to attomolar (100 copies of) SARS-CoV-2 RNA. Finally, this PHAsed NASBA-Translation Optical Method (PHANTOM) efficiently detects the presence of viral RNA in human patient samples, with clear distinction from samples designated negative for the virus. The biosensor response correlates well with Ct values from RT-qPCR tests and thus presents a powerful and easily accessible strategy for detecting Covid infection. | infectious diseases |
10.1101/2021.01.08.21249426 | Ultrasensitive RNA biosensors for SARS-CoV-2 detection in a simple color and luminescence assay | The COVID-19 pandemic underlines the need for versatile diagnostic strategies. Here, we have designed and developed toehold RNA-based sensors for direct and ultrasensitive SARS-CoV-2 RNA detection. In our assay, isothermal amplification of a fragment of SARS-CoV-2 RNA coupled with activation of our biosensors leads to a conformational switch in the sensor. This leads to translation of a reporter-protein e.g. LacZ or Nano-lantern that is easily detected using color/luminescence. This response can be visualized by the human eye, or a simple cell phone camera as well as quantified using a spectrophotometer/luminometer. By optimizing RNA-amplification and biosensor-design, we have generated a highly-sensitive diagnostic assay; with sensitivity down to attomolar (100 copies of) SARS-CoV-2 RNA. Finally, this PHAsed NASBA-Translation Optical Method (PHANTOM) efficiently detects the presence of viral RNA in human patient samples, with clear distinction from samples designated negative for the virus. The biosensor response correlates well with Ct values from RT-qPCR tests and thus presents a powerful and easily accessible strategy for detecting Covid infection. | infectious diseases |
10.1101/2021.01.08.21249426 | Engineered RNA biosensors enable ultrasensitive SARS-CoV-2 detection in a simple color and luminescence assay | The COVID-19 pandemic underlines the need for versatile diagnostic strategies. Here, we have designed and developed toehold RNA-based sensors for direct and ultrasensitive SARS-CoV-2 RNA detection. In our assay, isothermal amplification of a fragment of SARS-CoV-2 RNA coupled with activation of our biosensors leads to a conformational switch in the sensor. This leads to translation of a reporter-protein e.g. LacZ or Nano-lantern that is easily detected using color/luminescence. This response can be visualized by the human eye, or a simple cell phone camera as well as quantified using a spectrophotometer/luminometer. By optimizing RNA-amplification and biosensor-design, we have generated a highly-sensitive diagnostic assay; with sensitivity down to attomolar (100 copies of) SARS-CoV-2 RNA. Finally, this PHAsed NASBA-Translation Optical Method (PHANTOM) efficiently detects the presence of viral RNA in human patient samples, with clear distinction from samples designated negative for the virus. The biosensor response correlates well with Ct values from RT-qPCR tests and thus presents a powerful and easily accessible strategy for detecting Covid infection. | infectious diseases |
10.1101/2021.01.07.21249392 | Predicting severity of Covid-19 using standard laboratory parameters | BackgroundMore than 1.6 million people have already deceased due to a COVID-19 infection making it a major public health concern. A prediction of severe courses can enhance treatment quality and thus lower fatality and morbidity rates. The use of laboratory parameters has recently been established for a prediction. However, laboratory parameters have rarely been used in combination to predict severe outcomes.
MethodWe used a retrospective case-control design to analyze risk factors derived from laboratory parameters. Patients treated for COVID-19 at an hospital in Krefeld, Germany, from March to May 2020 were included (n =42). Patients were classified into two categories based on their outcome (Mild course vs. treatment in intensive care unit). Laboratory parameters were compared across severity categories using non-parametric statistic. Identified laboratory parameters were used in a logistic regression model. The model was replicated using a) clinical standardized parameters b) aggregated factors derived from a factor analysis.
ResultsPatients in intensive care unit showed elevated ALT, CRP and LDH levels, a higher leukocyte and neutrophile count, a higher neutrophile ratio and a lowered lymphocyte ratio. We were able to classify 95.1% of all cases correctly (96.6% of mild and 91.7% of severe cases, p<.001).
ConclusionA number of routinely collected laboratory parameters is associated with a severe outcome of COVID-19. The combination of these parameters provides a powerful tool in predicting severity and can enhance treatment effectiveness. | intensive care and critical care medicine |
10.1101/2021.01.07.21249360 | A Processed EEG based Brain Anesthetic Resistance Index Predicts Postoperative Delirium in Older Adults: A Dual Center Study | BackgroundSome older adults show exaggerated responses to drugs that act on the brain, such as increased delirium risk in response to anticholinergic drugs. The brains response to anesthetic drugs is often measured clinically by processed electroencephalogram (EEG) indices. Thus, we developed a processed EEG based-measure of the brains neurophysiologic resistance to anesthetic dose-related changes, and hypothesized that it would predict postoperative delirium.
MethodsWe defined the Duke Anesthesia Resistance Scale (DARS) as the average BIS index divided by the quantity 2.5 minus the average age-adjusted end-tidal MAC (aaMAC) inhaled anesthetic fraction. The relationship between DARS and postoperative delirium was analyzed in derivation (Duke; N=69), validation (Mt Sinai; N=70), and combined estimation cohorts (N=139) of older surgical patients (age [≥]65). In the derivation cohort, we identified a threshold relationship between DARS and for delirium and identified an optimal cut point for prediction.
ResultsIn the derivation cohort, the optimal DARS threshold for predicting delirium was 27.0. The delirium rate was 11/49 (22.5%) vs 11/20 (55.0%) and 7/57 (12.3%) vs 6/13 (46.2%) for those with DARS [≥] 27 vs those with DARS < 27 in the derivation and validation cohorts respectively. In the combined estimation cohort, multivariable analysis found a significant association of DARS <27.0 with postoperative delirium (OR=4.7; 95% CI: 1.87, 12.0; p=0.001). In the derivation cohort, the DARS had an AUC of 0.63 with sensitivity of 50%, specificity of 81%, positive predictive value of 0.55, and negative predictive value of 0.78. The DARS remained a significant predictor of delirium after accounting for opioid, midazolam, propofol, non-depolarizing neuromuscular blocker, phenylephrine and ketamine dosage, and for nitrous oxide and epidural usage.
ConclusionsThese results suggest than an intraoperative processed EEG-based measure of lower brain anesthetic resistance (i.e. DARS <27) could be used in older surgical patients as an independent predictor of postoperative delirium risk. | anesthesia |
10.1101/2021.01.07.21249415 | Causal Mediation Analysis with Multiple Causally Ordered and Non-ordered Mediators based on Summarized Genetic Data | Causal mediation analysis aims to investigate the mechanism linking an exposure and an outcome. Dealing with the impact of unobserved confounders among the exposure, mediator and outcome has always been an issue of great concern. Moreover, when multiple mediators exist, this causal pathway intertwines with other causal pathways, making it more difficult to estimate of path-specific effects (PSEs). In this article, we propose a method (PSE-MR) to identify and estimate PSEs of an exposure on an outcome through multiple causally ordered and non-ordered mediators using Mendelian Randomization, when there are unmeasured confounders among the exposure, mediators and outcome. Additionally, PSE-MR can be used when pleiotropy exists, and can be implemented using only summarized genetic data. We also conducted simulations to evaluate the finite sample performances of our proposed estimators in different scenarios. The results show that the causal estimates of PSEs are almost unbiased with good coverage and Type I error properties. We illustrate the utility of our method through a study of exploring the mediation effects of lipids in the causal pathways from body mass index to cardiovascular disease.
Author summaryA new method (PSE-MR) is proposed to identify and estimate PSEs of an exposure on an outcome through multiple causally ordered and non-ordered mediators using summarized genetic data, when there are unmeasured confounders among the exposure, mediators and outcome. Lipids play important roles in the causal pathways from body mass index to cardiovascular disease | epidemiology |
10.1101/2021.01.07.21249419 | Competing Health Risks Associated with the COVID-19 Pandemic and Response: A Scoping Review | BackgroundCOVID-19 has rapidly emerged as a global public health threat with infections recorded in nearly every country. Responses to COVID-19 have varied in intensity and breadth, but generally have included domestic and international travel limitations, closure of non-essential businesses, and repurposing of health services. While these interventions have focused on testing, treatment, and mitigation of COVID-19, there have been reports of interruptions to diagnostic, prevention, and treatment services for other public health threats.
ObjectivesWe conducted a scoping review to characterize the early impact of COVID-19 on HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition.
MethodsA scoping literature review was completed using searches of PubMed and preprint servers (medRxiv/bioRxiv) from January 1st to October 31st, 2020, using Medical Subject Headings (MeSH) terms related to SARS-CoV-2 or COVID-19 and HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Empiric studies reporting original data collection or mathematical models were included, and available data synthesized by region. Studies were excluded if they were not written in English.
ResultsA total of 1604 published papers and 205 preprints met inclusion criteria, including 8.2% (132/1604) of published studies and 10.2% (21/205) of preprints: 7.3% (68/931) on HIV, 7.1% (24/339) on tuberculosis, 11.6% (26/224) on malaria, 7.8% (13/166) on sexual and reproductive health, and 9.8% (13/132) on malnutrition. Thematic results were similar across competing health risks, with substantial indirect effects of the COVID-19 pandemic and response on diagnostic, prevention, and treatment services for HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition.
DiscussionCOVID-19 emerged in the context of existing public health threats that result in millions of deaths every year. Thus, effectively responding to COVID-19 while minimizing the negative impacts of COVID-19 necessitates innovation and integration of existing programs that are often siloed across health systems. Inequities have been a consistent driver of existing health threats; COVID-19 has worsened disparities, reinforcing the need for programs that address structural risks. The data reviewed here suggest that effective strengthening of health systems should include investment and planning focused on ensuring the continuity of care for both rapidly emergent and existing public health threats. | epidemiology |
10.1101/2021.01.07.21249419 | Competing Health Risks Associated with the COVID-19 Pandemic and Early Response: A Scoping Review | BackgroundCOVID-19 has rapidly emerged as a global public health threat with infections recorded in nearly every country. Responses to COVID-19 have varied in intensity and breadth, but generally have included domestic and international travel limitations, closure of non-essential businesses, and repurposing of health services. While these interventions have focused on testing, treatment, and mitigation of COVID-19, there have been reports of interruptions to diagnostic, prevention, and treatment services for other public health threats.
ObjectivesWe conducted a scoping review to characterize the early impact of COVID-19 on HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition.
MethodsA scoping literature review was completed using searches of PubMed and preprint servers (medRxiv/bioRxiv) from January 1st to October 31st, 2020, using Medical Subject Headings (MeSH) terms related to SARS-CoV-2 or COVID-19 and HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Empiric studies reporting original data collection or mathematical models were included, and available data synthesized by region. Studies were excluded if they were not written in English.
ResultsA total of 1604 published papers and 205 preprints met inclusion criteria, including 8.2% (132/1604) of published studies and 10.2% (21/205) of preprints: 7.3% (68/931) on HIV, 7.1% (24/339) on tuberculosis, 11.6% (26/224) on malaria, 7.8% (13/166) on sexual and reproductive health, and 9.8% (13/132) on malnutrition. Thematic results were similar across competing health risks, with substantial indirect effects of the COVID-19 pandemic and response on diagnostic, prevention, and treatment services for HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition.
DiscussionCOVID-19 emerged in the context of existing public health threats that result in millions of deaths every year. Thus, effectively responding to COVID-19 while minimizing the negative impacts of COVID-19 necessitates innovation and integration of existing programs that are often siloed across health systems. Inequities have been a consistent driver of existing health threats; COVID-19 has worsened disparities, reinforcing the need for programs that address structural risks. The data reviewed here suggest that effective strengthening of health systems should include investment and planning focused on ensuring the continuity of care for both rapidly emergent and existing public health threats. | epidemiology |
10.1101/2021.01.07.21249380 | Epidemiological differences in the impact of COVID-19 vaccination in the United States and China | BackgroundThe objective of this study was to forecast the impact of COVID-19 vaccination in the United States (US) and China, two countries at different epidemic phases.
MethodsA mathematical model describing SARS-CoV-2 transmission and disease progression was used to investigate vaccine impact. Impact was assessed both for a vaccine that prevents infection (VES = 95%) and a vaccine that prevents only disease (VEP = 95%).
ResultsFor VES = 95% and gradual easing of restrictions, vaccination in the US reduced the peak incidence of infection, disease, and death by >55% and cumulative incidence by >32%, and in China by >77% and >65%, respectively. Nearly three vaccinations were needed to avert one infection in the US, but only one was needed in China. For VEP = 95%, benefits of vaccination were half those for VES = 95%. In both countries, the impact of vaccination was substantially enhanced with rapid scale-up, vaccine coverage >50%, and slower or no easing of restrictions, particularly in the US.
ConclusionsCOVID-19 vaccination can flatten, delay, and/or prevent future epidemic waves. However, vaccine impact is destined to be heterogeneous across countries because of an underlying "epidemiologic inequity" that reduces benefits for countries already at high incidence, such as the US. Despite 95% efficacy, actual vaccine impact could be meager in such countries, if vaccine scale-up is slow, acceptance of the vaccine is poor, or restrictions are eased prematurely.
One Sentence SummaryVaccine impact will be heterogeneous across countries disadvantaging countries at high incidence. This heterogeneity can be alleviated with rapid vaccination scale-up and limited easing of restrictions. | epidemiology |
10.1101/2021.01.07.21249401 | Timeliness of U.S. mortality data releases during the COVID-19 pandemic: delays are associated with electronic death registration system and elevated weekly mortality | All-cause mortality counts allow public health authorities to identify populations experiencing excess deaths from pandemics, natural disasters, and other emergencies. Delays in the completeness of mortality counts may contribute to misinformation because death counts take weeks to become accurate. We estimate the timeliness of all-cause mortality releases during the Covid-19 pandemic for the dates 3 April to 5 September 2020 by estimating the number of weekly data releases of the NCHS Fluview Mortality Surveillance System until mortality comes within 99% of the counts in the 19 March 19 2021 provisional mortality data release. States mortality counts take 5 weeks at median (interquartile range 4--7 weeks) to completion. The fastest states were Maine, New Hampshire, Vermont, New York, Utah, Idaho, and Hawaii. States that had not adopted the electronic death registration system (EDRS) were 4.8 weeks slower to achieve complete mortality counts, and each weekly death per 10^8 was associated with a 0.8 week delay. Emergency planning should improve the timeliness of mortality data by improving state vital statistics digital infrastructure. | epidemiology |
10.1101/2021.01.07.21249401 | Timeliness of U.S. mortality data releases during the COVID-19 pandemic: delays are associated with electronic death registration system and weekly mortality | All-cause mortality counts allow public health authorities to identify populations experiencing excess deaths from pandemics, natural disasters, and other emergencies. Delays in the completeness of mortality counts may contribute to misinformation because death counts take weeks to become accurate. We estimate the timeliness of all-cause mortality releases during the Covid-19 pandemic for the dates 3 April to 5 September 2020 by estimating the number of weekly data releases of the NCHS Fluview Mortality Surveillance System until mortality comes within 99% of the counts in the 19 March 19 2021 provisional mortality data release. States mortality counts take 5 weeks at median (interquartile range 4--7 weeks) to completion. The fastest states were Maine, New Hampshire, Vermont, New York, Utah, Idaho, and Hawaii. States that had not adopted the electronic death registration system (EDRS) were 4.8 weeks slower to achieve complete mortality counts, and each weekly death per 10^8 was associated with a 0.8 week delay. Emergency planning should improve the timeliness of mortality data by improving state vital statistics digital infrastructure. | epidemiology |
10.1101/2021.01.07.21249401 | Timeliness of U.S. mortality data releases during the COVID-19 pandemic: delays are associated with electronic death registration system and weekly mortality | All-cause mortality counts allow public health authorities to identify populations experiencing excess deaths from pandemics, natural disasters, and other emergencies. Delays in the completeness of mortality counts may contribute to misinformation because death counts take weeks to become accurate. We estimate the timeliness of all-cause mortality releases during the Covid-19 pandemic for the dates 3 April to 5 September 2020 by estimating the number of weekly data releases of the NCHS Fluview Mortality Surveillance System until mortality comes within 99% of the counts in the 19 March 19 2021 provisional mortality data release. States mortality counts take 5 weeks at median (interquartile range 4--7 weeks) to completion. The fastest states were Maine, New Hampshire, Vermont, New York, Utah, Idaho, and Hawaii. States that had not adopted the electronic death registration system (EDRS) were 4.8 weeks slower to achieve complete mortality counts, and each weekly death per 10^8 was associated with a 0.8 week delay. Emergency planning should improve the timeliness of mortality data by improving state vital statistics digital infrastructure. | epidemiology |
10.1101/2021.01.07.21249397 | Persistence of a pandemic in the presence of susceptibility and infectivity distributions in a population: Mathematical model | The birth and death of a pandemic can be region specific. Pandemic seems to make repeated appearance in some places which is often attributed to human neglect and seasonal change. However, difference could arise from different distributions of inherent susceptibility ({sigma}inh) and external infectivity ({iota}ext) from one population to another. These are often ignored in the theoretical treatments of an infectious disease progression. While the former is determined by the immunity of an individual towards a disease, the latter depends on the duration of exposure to the infection. Here we model the spatio-temporal propagation of a pandemic using a generalized SIR (Susceptible-Infected-Removed) model by introducing the susceptibility and infectivity distributions to comprehend their combined effects. These aspects have remained inadequately addressed till date. We consider the coupling between{sigma} inh and{iota} ext through a new critical infection parameter ({gamma}c). We find that the neglect of these distributions, as in the naive SIR model, results in an overestimation in the estimate of the herd immunity threshold. That is, the presence of the distributions could dramatically reduce the rate of spread. Additionally, we include the effects of long-range migration by seeding new infections in a region. We solve the resulting master equations by performing Kinetic Monte Carlo Cellular Automata (KMC-CA) simulations. Importantly, our simulations can reproduce the multiple infection peak scenario of a pandemic. The latent interactions between disease migration and the distributions of susceptibility and infectivity can render the progression a character vastly different from the naive SIR model. In particular, inclusion of these additional features renders the problem a character of a living percolating system where the disease cluster can survive by spatial migration. | epidemiology |
10.1101/2021.01.08.21249439 | Inflight Transmission of COVID-19 Based on Aerosol Dispersion Data | BackgroundAn issue of concern to the travelling public is the possibility of in-flight transmission of COVID-19 during long- and short-haul flights. The aviation industry maintain the probability of contracting the illness is small based on reported cases, modelling and data from aerosol dispersion experiments conducted on-board aircraft.
MethodsUsing experimentally derived aerosol dispersion data for a B777-200 aircraft and a modified version of the Wells-Riley equation we estimate inflight infection probability for a range of scenarios involving quanta generation rate and face mask efficiency. Quanta generation rates were selected based on COVID-19 events reported in the literature while mask efficiency was determined from the aerosol dispersion experiments.
ResultsThe MID-AFT cabin exhibits the highest infection probability. The calculated maximum individual infection probability (without masks) for a 2-hour flight in this section varies from 4.5% for the "Mild Scenario" to 60.2% for the "Severe Scenario" although the corresponding average infection probability varies from 0.1% to 2.5%. For a 12-hour flight, the corresponding maximum individual infection probability varies from 24.1% to 99.6% and the average infection probability varies from 0.8% to 10.8%. If all passengers wear face masks throughout the 12-hour flight, the average infection probability can be reduced by approximately 73%/32% for high/low efficiency masks. If face masks are worn by all passengers except during a one-hour meal service, the average infection probability is increased by 59%/8% compared to the situation where the mask is not removed.
ConclusionsThis analysis has demonstrated that while there is a significant reduction in aerosol concentration due to the nature of the cabin ventilation and filtration system, this does not necessarily mean that there is a low probability or risk of in-flight infection. However, mask wearing, particularly high-efficiency ones, significantly reduces this risk. | public and global health |
10.1101/2021.01.06.21249325 | Pregnancy and neonatal outcomes of COVID-19, co-reporting of common outcomes from the PAN-COVID and AAP SONPM registry | BackgroundFew large, cohort studies report data on individuals maternal, fetal, perinatal, and neonatal outcomes associated with SARS-CoV-2 infection in pregnancy. We report outcomes from a collaboration formed early during the pandemic between the investigators of two registries, the UK and global Pregnancy and Neonatal outcomes in COVID-19 (PAN-COVID) study and the US American Academy of Pediatrics Section on Neonatal Perinatal Medicine (AAP SONPM) National Perinatal COVID-19 Registry.
MethodsPAN-COVID (suspected or confirmed SARS-CoV-2 infection at any stage in pregnancy) and the AAP SONPM registry (positive maternal testing for SARS-CoV-2 from 14 days before delivery to 3 days after delivery) studies collected data on maternal, fetal, perinatal and neonatal outcomes. PAN-COVID results are presented as all inclusions and those with confirmed SARS-CoV-2 infection only.
ResultsWe report 4004 women in pregnancy affected by suspected or confirmed SARS-CoV-2 infection (1606 from PAN-COVID and 2398 from the AAP SONPM) from January 1st 2020 to July 25th 2020 (PAN-COVID) and August 8th (AAP SONPM). For obstetric outcomes in PAN-COVID and AAP SONPM, respectively, maternal death occurred in 0.5% and 0.17%, early neonatal death in 0.2% and 0.3%, and stillbirth in 0.50% and 0.65% of women. Delivery was pre-term (<37 weeks gestation) in 12% of all women in PAN-COVID, in 16.2% of those women with confirmed infection in PAN-COVID and 16.2% of women in AAP SONPM. Very preterm delivery (< 27 weeks gestation) occurred in 0.6% in PAN-COVID and 0.7% in AAP SONPM.
Neonatal SARS-CoV-2 infection was reported in 0.8% of PAN-COVID all inclusions, 2.0% in PAN-COVID confirmed infections and 1.8% in the AAP SONPM study; the proportions of babies tested were 9.5%, 20.7% and 87.2% respectively.
The proportion of SGA babies was 8.2% in PAN-COVID all inclusions, 9.7% in PAN-COVID confirmed infection and 9.6% in AAP SONPM. Gestational age adjusted mean z-scores were -0.03 for PAN-COVID and -0.18 for AAP SONPM.
ConclusionsThe findings from the UK and US SARS-CoV-2 in pregnancy registries were remarkably concordant. Pre-term delivery affected a higher proportion of women in pregnancy than expected from historical and contemporaneous national data. The proportions of women affected by stillbirth, small for gestational age infants and early neonatal death were comparable to historical and contemporaneous UK and US data. Although maternal death was uncommon, the proportion was higher than expected from UK and US population data, likely explained by under-ascertainment of women affected by milder and asymptomatic infection in pregnancy. The data presented support strong guidance for enhanced precautions to prevent SARS-COV-2 infection in pregnancy, particularly in the context of increased risks of preterm delivery and maternal mortality, and for priority vaccination of women planning pregnancy.
What is known about SARS-COV-2 infection in pregnancy and neonates?Cohort, population surveillance studies and living systematic reviews have included limited numbers of women in pregnancy affected by COVID-19 and report that most women and infants had good outcomes.
What this study addsPreterm deliveries occurred in a high proportion of women participating in these two registries in comparison to contemporaneous and historical national data in the UK and US. The majority of preterm deliveries occurred late preterm (between 32+0 and 36+6 weeks gestation).
SARS-COV-2 infection in pregnancy did not appear to be associated with a clinically significant effect on the rate of stillbirth, fetal growth, or neonatal outcomes.
Although maternal death was uncommon, the proportion was higher than expected from UK and US population data, likely explained by under-ascertainment of women affected by milder and asymptomatic infection in pregnancy. | obstetrics and gynecology |
10.1101/2021.01.06.20248468 | HeAlth System StrEngThening in four sub_Saharan African countries (ASSET) to achieve high-quality, evidence-informed surgical, maternal and newborn, and primary care: protocol for pre-implementation phase studies | ObjectivesTo achieve universal health coverage, health systems need to be strengthened to support the consistent delivery of high-quality, evidence-informed care at scale. The aim of the National Institute for Health Research (NIHR) Global Research Unit on HeAlth System StrEngThening in Sub-Saharan Africa (ASSET) is to address this need in a four-year programme spanning three healthcare platforms (primary health care for the integrated treatment of chronic conditions in adults, maternal and newborn, surgical care) involving eight work packages. This paper describes the pre-implementation phase research protocols that assess: (1) barriers to accessing care; (2) health system bottlenecks in care process and pathways; (3) quality of care, and; (4) people centredness. Findings from this research are used to engage stakeholders and to inform the selection of a set of health system strengthening interventions (HSSIs) and subsequent methodology for evaluation.
SettingsPublicly funded health systems in rural and urban areas in Ethiopia, Sierra Leone, South Africa, and Zimbabwe.
PopulationStakeholders including patients and their caregivers, community representatives, clinicians, managers, administrators, and policymakers.
Study methodologies and deliveryIn each work package, we apply a mixed-methods approach, including: literature reviews; situation analyses; cohort studies; cross-sectional surveys; ethnographic observations; semi-structured interviews, and; focus group discussions. At the end of the pre-implementation phase, findings are fed back to stakeholders in participatory theory of change workshops that are used to select/adapt an initial set of contextually relevant HSSIs. To ensure a theory-informed approach across ASSET, implementation science determinant frameworks are also applied, to help identify any additional contextual barriers and enablers and complementary HSSIs. Outputs from these activities are used to finalise underlying assumptions, potential unintended consequences, process indicators and implementation and clinical outcomes.
ConclusionsASSET places a strong emphasis of the pre-implementation phase of the programme in order to provide an in-depth and systematic diagnosis of the existing heath system functioning, needs for strengthening and active stakeholder engagement. This approach will inform the design and evaluation of the HSSIs to increase effectiveness across work packages and contexts, to better understand what works, for whom, and how.
Strengths and limitations of this studyO_LIThe National Health Institute of Research (NIHR) Global Research Unit on Health System Strengthening in sub-Saharan Africa (ASSET) is a four-year programme (2017-2021) that is closely aligned with the SDG goal of UHC, and the recommendations of the Lancet Commission for High Quality Health Systems.
C_LIO_LIThe aim of ASSET is to develop and evaluate effective and sustainable HSSIs, promoting consistent delivery of high-quality, people-centred care.
C_LIO_LIThe ASSET programme is being conducted in two phases including the diagnostic pre-implementation and piloting/rolling implementation phase.
C_LIO_LIThe purpose of this paper is to describe the methodology for the pre-implementation phase, which has the core aim of mapping comprehensive care pathways of a patients journey though the health system including the community, different providers), and health facilities, documenting what care is provided at what level of the health system and the associated health system bottlenecks.
C_LIO_LIAt the end of the pre-implementation phase of ASSET, it is hoped the common approach taken across different countries, care platforms and health conditions will facilitate cross platform learning and understanding of how differences in health systems and broader contextual influences shaped the development of the interventions.
C_LIO_LIThe overarching expectation is that by using an in-depth participatory process to engage with the stakeholders and map care pathways to and through the health system, we develop a HSS programme that can be implemented at scale that meets the needs and priorities of the local community.
C_LI | health systems and quality improvement |
10.1101/2021.01.06.21249243 | Combining science and social engagement againstCovid-19 in a Brazilian Slum | ObjectivesFor many underdeveloped countries, strategies implemented by social communities allied to scientific knowledge may be a rote to attenuate the rapid spread of Covid-19 cases and allow services to the population. This work presents a joint effort collaboration between scientists and underserved community groups from a Brazilian slum/Santa Marta in Rio de Janeiro City in the fight against Covid-19. Measurements of contamination in the air near the ground, georeferencing of data of infected people, were regressed with sanitization activities aiming at reducing the Covid-19 incidence.
MethodsWe monitored aerosol containing SARS-Cov-2 virus in outdoor ambient air using various virus collection mediums (solid, liquid, and gelatinous substrates) at different aerodynamic sizes. We implemented a local statistics survey for the Covid-19 database correlated with varying sanitization levels between April 2020 and June 2021 developed in the Santa Marta slum.
FindingsWe detected the SARS-CoV-2 virus in the air near the ground in diameters ranging from 0.25 to 0.5 {micro}m, demonstrating that there is a circulation of the virus in the slum atmosphere. We demonstrate that Covid-19 cases for the Santa Marta slum were significatively lowered with improved sanitization levels (r = -0.74).
ConclusionsDespite previous publications that discarded the use of sanitization as a relevant tool in the fight against Covid-19, our results suggest that profits can be achieved in mitigating Covid-19 in underserved community sites. Furthermore, a permanent sanitization activity may induce positive social behavior for the sake of combating Covid-19. | public and global health |
10.1101/2021.01.06.21249243 | How social engagement against Covid-19 in a Brazilian Slum helped mitigate rising statistics | ObjectivesFor many underdeveloped countries, strategies implemented by social communities allied to scientific knowledge may be a rote to attenuate the rapid spread of Covid-19 cases and allow services to the population. This work presents a joint effort collaboration between scientists and underserved community groups from a Brazilian slum/Santa Marta in Rio de Janeiro City in the fight against Covid-19. Measurements of contamination in the air near the ground, georeferencing of data of infected people, were regressed with sanitization activities aiming at reducing the Covid-19 incidence.
MethodsWe monitored aerosol containing SARS-Cov-2 virus in outdoor ambient air using various virus collection mediums (solid, liquid, and gelatinous substrates) at different aerodynamic sizes. We implemented a local statistics survey for the Covid-19 database correlated with varying sanitization levels between April 2020 and June 2021 developed in the Santa Marta slum.
FindingsWe detected the SARS-CoV-2 virus in the air near the ground in diameters ranging from 0.25 to 0.5 {micro}m, demonstrating that there is a circulation of the virus in the slum atmosphere. We demonstrate that Covid-19 cases for the Santa Marta slum were significatively lowered with improved sanitization levels (r = -0.74).
ConclusionsDespite previous publications that discarded the use of sanitization as a relevant tool in the fight against Covid-19, our results suggest that profits can be achieved in mitigating Covid-19 in underserved community sites. Furthermore, a permanent sanitization activity may induce positive social behavior for the sake of combating Covid-19. | public and global health |
10.1101/2021.01.06.21249243 | How social engagement against Covid-19 in a Brazilian Slum helped mitigate rising statistics | ObjectivesFor many underdeveloped countries, strategies implemented by social communities allied to scientific knowledge may be a rote to attenuate the rapid spread of Covid-19 cases and allow services to the population. This work presents a joint effort collaboration between scientists and underserved community groups from a Brazilian slum/Santa Marta in Rio de Janeiro City in the fight against Covid-19. Measurements of contamination in the air near the ground, georeferencing of data of infected people, were regressed with sanitization activities aiming at reducing the Covid-19 incidence.
MethodsWe monitored aerosol containing SARS-Cov-2 virus in outdoor ambient air using various virus collection mediums (solid, liquid, and gelatinous substrates) at different aerodynamic sizes. We implemented a local statistics survey for the Covid-19 database correlated with varying sanitization levels between April 2020 and June 2021 developed in the Santa Marta slum.
FindingsWe detected the SARS-CoV-2 virus in the air near the ground in diameters ranging from 0.25 to 0.5 {micro}m, demonstrating that there is a circulation of the virus in the slum atmosphere. We demonstrate that Covid-19 cases for the Santa Marta slum were significatively lowered with improved sanitization levels (r = -0.74).
ConclusionsDespite previous publications that discarded the use of sanitization as a relevant tool in the fight against Covid-19, our results suggest that profits can be achieved in mitigating Covid-19 in underserved community sites. Furthermore, a permanent sanitization activity may induce positive social behavior for the sake of combating Covid-19. | public and global health |
10.1101/2021.01.08.20248948 | The Conundrum of Giglio Island: unraveling the dynamics of an apparent resistance to COVID-19. A descriptive study | ObjectivesDespite an extensive risk of exposure to COVID-19, the residents of Giglio Island, Italy, did not develop any symptom of SARS-CoV-2. The present study aims to characterize the nature of exposure and to describe the local population dynamics underlying its apparent resistance to COVID-19.
MethodsWe conducted seroprevalence screening from April 29 to May 3, 2020 across the three main settlements on the island. We invited the adult resident population, present on the island to undergo testing by rapid serologic assay and to provide a sample of saliva for molecular validation. We monitored the participation through the official municipality residents list. Serologic testing was performed using a COVID-19 IgG/IgM rapid test while molecular analyses were carried out by Allplex 2019-nCoV Assay (Seegene).
ResultsA total of 634 residents out of 748 (84.8%) present at the time, and 89 non-residents underwent serological testing. 364 males and 359 females with a median age of 58.5 years. The serological screening identified one positive, asymptomatic subject. The Nucleic Acid Amplification Tests did not yield any positive result.
ConclusionDespite extensive exposure to SARS-CoV-2, only one new asymptomatic infection occurred in this population. This may be due to unknown protective factors or chance. On the basis of this first descriptive study, using its population as a reference model, further investigations will be conducted to characterize the summer period exposure and to test the advanced hypotheses, focusing on the evaluation of a possible cross-reactivity to SARS-CoV-2 from exposure to endemic viruses. | epidemiology |
10.1101/2021.01.08.20248710 | Association of Inflammation with Depression and Anxiety: Evidence for Symptom-Specificity and Potential Causality from UK Biobank and NESDA Cohorts | We examined whether inflammation is uniformly associated with all depressive and anxiety symptoms, and whether these associations are potentially causal. Data was from 147,478 individuals from the UK Biobank (UKB) and 2,905 from the Netherlands Study of Depression and Anxiety (NESDA). Circulating C-reactive protein (CRP) was measured in both cohorts and interleukin-6 (IL-6) in NESDA. Genetic instruments for these proteins were obtained from published GWAS and UKB. Depressive and anxiety symptoms were assessed with self-report questionnaires. In NESDA, neurovegetative (appetite, sleep, psychomotor) symptoms were disaggregated as increased vs. decreased. In joint analyses, circulating CRP was associated with depressive symptoms of depressed mood (OR=1.06, 95%CI=1.05-1.08), altered appetite (OR=1.25, 95%CI=1.23-1.28), sleep problems (OR=1.05, 95%CI=1.04-1.06), and fatigue (OR=1.12, 95%CI=1.11-1.14), and with anxiety symptoms of irritability (OR=1.06, 95%CI=1.05-1.08) and worrying control (OR=1.03, 95%CI=1.02-1.04). Further analyses in NESDA using IL-6 as exposure confirmed associations with depressive symptoms, including anhedonia (OR=1.30, 95%CI=1.12-1.52). Both CRP (OR=1.27, 95%CI=1.13-1.43) and IL-6 (OR=1.26, 95%CI=1.07-1.49) were associated with increased sleep. CRP was associated with increased appetite (OR=1.21, 95%CI=1.08-1.35) while IL-6 with decreased appetite (OR=1.45, 95%CI=1.18-1.79). In Mendelian Randomization analyses, increased risk of fatigue (estimate=0.25, SE=0.08) and sleep problems (estimate=0.19, SE=0.07) were associated with genetically-predicted higher IL-6 activity. Inflammation was associated with core depressive symptoms of low mood and anhedonia and somatic/neurovegetative symptoms of fatigue, altered sleep and appetite changes. Less consistent associations were found for anxiety. The IL-6/IL-6R pathway could be causally linked to depression. Experimental studies are required to further evaluate causality, mechanisms, and usefulness of immunotherapies for depressive symptoms. | psychiatry and clinical psychology |
10.1101/2021.01.07.20248970 | Cholinergic and lipid mediators crosstalk in Covid-19 and the impact of glucocorticoid therapy | Cytokine storms and hyperinflammation, potentially controlled by glucocorticoids, occur in COVID-19; the roles of lipid mediators and acetylcholine (ACh) and how glucocorticoid therapy affects their release in Covid-19 remain unclear. Blood and bronchoalveolar lavage (BAL) samples from SARS-CoV-2- and non-SARS-CoV-2-infected subjects were collected for metabolomic/lipidomic, cytokines, soluble CD14 (sCD14), and ACh, and CD14 and CD36-expressing monocyte/macrophage subpopulation analyses. Transcriptome reanalysis of pulmonary biopsies was performed by assessing coexpression, differential expression, and biological networks. Correlations of lipid mediators, sCD14, and ACh with glucocorticoid treatment were evaluated. This study enrolled 190 participants with Covid-19 at different disease stages, 13 hospitalized non-Covid-19 patients, and 39 healthy-participants. SARS-CoV-2 infection increased blood levels of arachidonic acid (AA), 5-HETE, 11-HETE, sCD14, and ACh but decreased monocyte CD14 and CD36 expression. 5-HETE, 11-HETE, cytokines, ACh, and neutrophils were higher in BAL than in circulation (fold-change for 5-HETE 389.0; 11-HETE 13.6; ACh 18.7, neutrophil 177.5, respectively). Only AA was higher in circulation than in BAL samples (fold-change 7.7). Results were considered significant at P<0.05, 95%CI. Transcriptome data revealed a unique gene expression profile associated with AA, 5-HETE, 11-HETE, ACh, and their receptors in Covid-19. Glucocorticoid treatment in severe/critical cases lowered ACh without impacting disease outcome. We first report that pulmonary inflammation and the worst outcomes in Covid-19 are associated with high levels of ACh and lipid mediators. Glucocorticoid therapy only reduced ACh, and we suggest that treatment may be started early, in combination with AA metabolism inhibitors, to better benefit severe/critical patients. | public and global health |
10.1101/2021.01.07.20248970 | Cholinergic and lipid mediators crosstalk in Covid-19 and the impact of glucocorticoid therapy | Cytokine storms and hyperinflammation, potentially controlled by glucocorticoids, occur in COVID-19; the roles of lipid mediators and acetylcholine (ACh) and how glucocorticoid therapy affects their release in Covid-19 remain unclear. Blood and bronchoalveolar lavage (BAL) samples from SARS-CoV-2- and non-SARS-CoV-2-infected subjects were collected for metabolomic/lipidomic, cytokines, soluble CD14 (sCD14), and ACh, and CD14 and CD36-expressing monocyte/macrophage subpopulation analyses. Transcriptome reanalysis of pulmonary biopsies was performed by assessing coexpression, differential expression, and biological networks. Correlations of lipid mediators, sCD14, and ACh with glucocorticoid treatment were evaluated. This study enrolled 190 participants with Covid-19 at different disease stages, 13 hospitalized non-Covid-19 patients, and 39 healthy-participants. SARS-CoV-2 infection increased blood levels of arachidonic acid (AA), 5-HETE, 11-HETE, sCD14, and ACh but decreased monocyte CD14 and CD36 expression. 5-HETE, 11-HETE, cytokines, ACh, and neutrophils were higher in BAL than in circulation (fold-change for 5-HETE 389.0; 11-HETE 13.6; ACh 18.7, neutrophil 177.5, respectively). Only AA was higher in circulation than in BAL samples (fold-change 7.7). Results were considered significant at P<0.05, 95%CI. Transcriptome data revealed a unique gene expression profile associated with AA, 5-HETE, 11-HETE, ACh, and their receptors in Covid-19. Glucocorticoid treatment in severe/critical cases lowered ACh without impacting disease outcome. We first report that pulmonary inflammation and the worst outcomes in Covid-19 are associated with high levels of ACh and lipid mediators. Glucocorticoid therapy only reduced ACh, and we suggest that treatment may be started early, in combination with AA metabolism inhibitors, to better benefit severe/critical patients. | public and global health |
10.1101/2021.01.08.20249041 | The incremental value of computed tomography of COVID-19 pneumonia in predicting ICU admission | RationaleTriage is crucial for patients management and estimation of the required Intensive Care Unit (ICU) beds is fundamental for Health Systems during the COVID-19 pandemic.
ObjectiveTo assess whether chest Computed Tomography (CT) of COVID-19 pneumonia has an incremental role in predicting patients admission to ICU.
MethodsWe performed volumetric and texture analysis of the areas of the affected lung in CT of 115 outpatients with COVID-19 infection presenting to the Emergency Room with dyspnea and unresponsive hypoxyemia. Admission blood laboratory including lymphocyte count, serum lactate dehydrogenase, D-dimer and C-Reactive Protein and the ratio between the arterial partial pressure of oxygen and inspired oxygen were collected. By calculating the areas under the receiver-operating characteristic curves (AUC), we compared the performance of blood laboratory-arterial gas analyses features alone and combined with the CT features in two hybrid models (Hybrid radiological and Hybrid radiomics)for predicting ICU admission. Following a machine learning approach, 63 patients were allocated to the training and 52 to the validation set.
Measurements and Main ResultsTwenty-nine (25%) of patients were admitted to ICU. The Hybrid radiological model comprising the lung %consolidation performed significantly (p=0.04) better in predicting ICU admission in the validation (AUC=0.82; 95%Confidence Interval 0.68-0.95) set than the blood laboratory-arterial gas analyses features alone (AUC=0.71; 95%Confidence Interval 0.56-0.86). A risk calculator for ICU admission was derived and is available at:https://github.com/cgplab/covidapp
ConclusionsThe volume of the consolidated lung in CT of patients with COVID-19 pneumonia has a mild but significant incremental value in predicting ICU admission. | radiology and imaging |
10.1101/2021.01.04.21249212 | Pregnancy Loss and Cardiovascular Disease: A Nationwide Cohort Study | ObjectivesTo examine how pregnancy loss influences the risk of cardiovascular disease later in life.
DesignProspective historical cohort study.
SettingDanish nationwide health registries.
ParticipantsAll Danish women with a recorded pregnancy from 1977 to 2017.
Main outcome measuresVenous thromboembolism, myocardial infarction, or ischemic stroke.
ResultsIn this two-part study, part one evaluated the 20-year absolute risk of cardiovascular disease from age 40 among 596,699 women with a full registered reproductive history. Adjusting for calendar year, diabetes, autoimmune disease, live births, and education, the absolute risk of an outcome after 0 and [≥]4 pregnancy losses, respectably was: venous thromboembolism 3.0% (95% CI 2.8 to 3.2%) and 5.0% (3.4 to 6.8%); myocardial infarction 1.5% (1.4 to 1.6%) and 2.4% (1.4 to 3.6%); ischemic stroke 2.0% (1.9 to 2.1%) and 2.6% (1.5 to 3.6%). Prior stillbirth increased the absolute risk of later venous thromboembolism by 1.1% (0.2 to 2.3%); myocardial infarction by 1.1% (0.3 to 2.0%).
In study part two, we included 966,490 women from first pregnancy in a time-dependent Cox regression model. Adjusted for confounders, each additional pregnancy loss increased the hazard ratio of venous thromboembolism 1.10 (95% CI 1.07 to 1.13); myocardial infarction 1.12 (1.07 to 1.18); and ischemic stroke 1.10 (1.06 to 1.14). Stillbirth was strongly associated with myocardial infarction before age 40, adjusted hazard ratio of 4.60 (2.65 to 8.00).
ConclusionPregnancy loss was associated with later venous thromboembolism, myocardial infarction, and ischemic stroke. The absolute and relative risk of outcomes increased in a dose-response manner with increasing numbers of prior pregnancy losses. Stillbirth was strongly associated with myocardial infarction before age 40. | obstetrics and gynecology |