A meta-analysis of Early Results to predict Vaccine efficacy against Omicron In the studies to date, the estimated fold-drop in neutralisation titre against Omicron ranges from 2- to over 20-fold depending on the study and serum tested. Collating data from the first four of these studies results in a combined estimate of the drop in neutralisation titre against Omicron of 9.7-fold (95% CI 5.5-17.1). We use our previously established model to predict that six months after primary immunisation with an mRNA vaccine, efficacy for Omicron is estimated to have waned to around 40% against symptomatic and 80% against severe disease. A booster dose with an existing mRNA vaccine (even though it targets the ancestral spike) has the potential to raise efficacy for Omicron to 86.2% (95% CI: 72.6-94) against symptomatic infection and 98.2% (95% CI: 90.2-99.7) against severe infection.
The anti-SARS-CoV-2 immunoglobulin G levels and neutralising capacities against alpha and delta virus variants of concern achieved after initial immunisation with vector vaccine followed by mRNA vaccine boost are comparable to those after double immunisation with mRNA vaccines BackgroundThe humoral immune response after primary immunisation with a SARS-CoV-2 vector vaccine (AstraZeneca AZD1222, ChAdOx1 nCoV-19, Vaxzevria) followed by an mRNA vaccine boost (Pfizer/BioNTech, BNT162b2; Moderna, m-1273) was examined and compared with the antibody response after homologous vaccination schemes (AZD1222/AZD1222 or BNT162b2/BNT162b2).

MethodsSera from 59 vaccinees were tested for anti-SARS-CoV-2 immunoglobulin G (IgG) and virus-neutralising antibodies (VNA) with four IgG assays, a surrogate neutralisation test (sVNT), and a Vero cell-based neutralisation test (cVNT) using the B.1.1.7 variant of concern (VOC; alpha) as antigen. Investigation was done before and after heterologous (n=31 and 42) or homologous booster vaccination (AZD1222/AZD1222, n=8/9; BNT162b2/BNT162b2, n=8/8). After the second immunisation, 26 age and gender matched sera (AZD1222/mRNA, n=9; AZD1222/AZD1222, n=9; BNT162b2/BNT162b2, n=8) were also tested for VNA against VOC B.1.617.2 (delta) in the cVNT. The strength of IgG binding to separate SARS-CoV-2 antigens was measured by avidity.

ResultsAfter the first vaccination, prevalence of IgG directed against (trimeric) SARS-CoV-2 spike (S)-protein and its receptor-binding domain (RBD) varied from 55-95 % (AZD1222) to 100% (BNT162b2), depending on the vaccine used and the SARS-CoV-2 antigen used. The booster vaccination resulted in 100 percent seroconversion and appearance of highly avid IgG as well as VNA against VOC B.1.1.7. The results of the anti-SARS-CoV-2 IgG tests showed an excellent correlation to the VNA titres against this VOC. The agreement of cVNT and sVNT results was good. However, the sVNT seems to overestimate non and weak B.1.1.7-neutralising titres. The mean anti-SARS-CoV-2 IgG and B.1.1.7-neutralising titres were significantly higher after heterologous vaccination compared to the homologous AZD1222 scheme. If VOC B.1.617.2 was used as antigen, significantly lower mean VNAs were measured in the cVNT, and three (33.3%) vector vaccine recipients had a VNA titre <1:10.

ConclusionsThe heterologous SARS-CoV-2 vaccination leads to a strong antibody response with anti-SARS-CoV-2 IgG and VNA titres at a level comparable to that of a homologous BNT162b2 vaccination scheme. Irrespectively of the chosen immunisation regime, highly avid IgG antibodies can be detected just two weeks after the second vaccine dose indicating the development of a robust humoral immunity. The observed reduction in the VNA titre against VOC B.1.617.2 is remarkable and may be attributed to a partial immune escape of the delta variant.
Treatment interruption is a risk factor for sickness presenteeism: a large-scale cross-sectional study during the COVID-19 pandemic ObjectivesThis study examined the relationship between interruption to routine medical care during the coronavirus disease 2019 pandemic and sickness presenteeism among workers in Japan.

MethodsA cross-sectional study using data obtained from an internet monitor questionnaire was conducted. Interruption to medical care was defined based on the response "I have not been able to go to the hospital or receive treatment as scheduled." The fraction of sickness presenteeism days in the past 30 days was employed as the primary outcome. A fractional logit model was used for analysis to treat bounded data.

ResultsOf the 27,036 participants, 17,526 (65%) were workers who did not require routine medical care, 8,451 (31%) were using medical care as scheduled, and 1,059 (4%) experienced interrupted medical care. The adjusted odds ratio (aOR) of sickness presenteeism was significantly higher among workers who experienced interrupted medical care (3.44; 95% confidence interval [CI]: 3.04-3.89) than those who did not require routine medical care. In terms of symptoms, the highest aOR was observed among workers with mental health symptoms (aOR: 5.59, 95%CI: 5.04-6.20).

ConclusionsThis study suggests the importance of continuing necessary treatment during a pandemic to prevent presenteeism. The effects of modifiable maternal pregnancy risk factors on molar-incisor hypomineralisation: A negative control study ObjectivesO_LITo explore the associations between modifiable maternal pregnancy exposures: pre-pregnancy body mass index (BMI), pregnancy smoking and alcohol consumption with offspring molar-incisor hypomineralisation (MIH).
C_LIO_LITo explore for the presence of residual confounding using negative control analyses.
C_LI

MethodsThis study used data from Avon Longitudinal Study of Parents and Children (ALSPAC), a UK prospective birth cohort. We defined offspring MIH using prospectively collected questionnaire data. We used logistic regression to explore confounder adjusted associations between maternal pre-pregnancy BMI and smoking and alcohol consumption during pregnancy with MIH. We included negative control exposure (paternal BMI, smoking and alcohol around the time of pregnancy) and outcome (offspring dental trauma) analyses to explore for the presence of residual confounding.

Results5536 mother/offspring pairs were included (297 MIH cases [5.4%]). We found a positive association between maternal mean BMI and offspring MIH (OR per 1-kg/m2 difference in maternal BMI: 1.04, 95% CI: 1.00, 1.08). In subsequent analyses, we found evidence that this effect was non-linear and being driven by women in the highest BMI quintiles. In negative control analyses, we found no evidence of association between paternal BMI and offspring MIH (OR: 0.94, 95% CI: 0.89, 1.00) and maternal BMI and offspring dental trauma (OR: 0.99, 95% CI: 0.96, 1.02). There was no clear evidence of an association for maternal pregnancy smoking (OR: 0.76, 95%CI: 0.46, 1.22) and alcohol consumption (OR: 0.79, 95% CI: 0.56, 1.21) with offspring MIH with results imprecisely estimated.

ConclusionIn summary we found evidence of a possible intrauterine effect of high maternal pre-pregnancy BMI on offspring MIH. We did not find robust evidence for an intrauterine effect of maternal pregnancy smoking or alcohol consumption on offspring MIH. Our findings provide further support for women of reproductive age to maintain a healthy weight. Future studies are warranted to explore possible mechanisms on how the pregnancy environment may relate to offspring MIH. SARS-CoV-2 Acquisition and Immune Pathogenesis Among School-Aged Learners in Four Diverse Schools BackgroundUnderstanding SARS-CoV-2 infection in children is necessary to reopen schools safely.

MethodsWe measured SARS-CoV-2 infection in 320 learners [10.5 {+/-} 2.1(sd); 7-17 y.o.] at four diverse schools with either remote or on-site learning. Schools A and B served low-income Hispanic learners; school C served many special-needs learners; and all provided predominantly remote instruction. School D served middle- and upper-income learners, with predominantly on-site instruction. Testing occurred in the fall (2020), and 6-8 weeks later during the fall-winter surge (notable for a tenfold increase in COVID-19 cases). Immune responses and mitigation fidelity were also measured.

ResultsWe found SARS-CoV-2 infections in 17 learners only during the surge. School A (97% remote learners) had the highest infection (10/70, 14.3%, p<0.01) and IgG positivity rates (13/66, 19.7%). School D (93% on-site learners) had the lowest infection and IgG positivity rates (1/63, 1.6%). Mitigation compliance [physical distancing (mean 87.4%) and face covering (91.3%)] was remarkably high at all schools. Documented SARS-CoV-2-infected learners had neutralizing antibodies (94.7%), robust IFN-{gamma}+ T cell responses, and reduced monocytes.

ConclusionSchools can implement successful mitigation strategies across a wide range of student diversity. Despite asymptomatic to mild SARS-CoV-2 infection, children generate robust humoral and cellular immune responses.

Key PointsO_LISuccessful COVID-19 mitigation was implemented across a diverse range of schools.
C_LIO_LISchool-associated SARS-CoV-2 infections reflect regional rates rather than remote or on-site learning.
C_LIO_LISeropositive school-aged children with asymptomatic to mild SARS-CoV-2 infections generate robust humoral and cellular immunity.
C_LI Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

MethodsThis prospective cross-sectional study recruited ocular-treatment-naive patients with type 2 diabetes mellitus (DM) registered in the community of Guangzhou, China. OCTA was used to obtain the measurements of FD and BVT in the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). Univariate and multivariate linear regression was used to analyse the correlation of FD and BVT in different layers with DR severity.

ResultsA total of 1282 patients with DM (1282 eyes), with a mean age of 64.2{+/-}7.8 years, were included. FD in the DCP decreased and BVT in the DCP increased in DR patients compared to non-DR patients, even after adjusting for confounding factors (P< 0.05). Trend analysis showed a significant decrease in the FD values as the DR progressed, while the BVT progressively increased with worsening DR severity (P< 0.01). The FD in DCP had a statistically significant positive correlation with FD in SCP and a negative correlation with BVT in SCP and BVT in DCP in all of the participants, including the non-DR group, moderate DR group and severe DR group (P< 0.01).

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. EDUCATIONAL NEEDS OF MEDICAL PRACTITIONERS ABOUT MEDICAL BILLING: A SCOPING REVIEW OF THE LITERATURE. IntroductionThe World Health Organization has suggested the solution to health system waste caused by incorrect billing and fraud is policing and prosecution. However, a growing body of evidence suggests leakage may not always be fraudulent or corrupt, with researchers suggesting medical practitioners may sometimes struggle to understand increasingly complex legal requirements around health financing and billing transactions, which may be improved through education. To explore this phenomenon further, we undertook a scoping review of the literature to identify the medical billing education needs of medical practitioners and whether those needs are being met.

MethodsEligible records included English language materials published between 1 January 2000 and 4 May 2020. Searches were conducted on MEDLINE, PubMed, Google Scholar, CINAHL, LexisNexis and Heinonline.

ResultsWe identified 74 records as directly relevant to the search criteria. Despite undertaking a comprehensive, English language search, with no country restrictions, studies meeting the inclusion criteria were limited to three countries (Australia, Canada, U.S), indicating a need for further work internationally. The literature suggests the education needs of medical practitioners in relation to medical billing compliance are not being met and medical practitioners desire more education on this topic. Evidence suggests education may be effective in improving medical billing compliance and reducing waste in health systems. There is broad agreement amongst medical education stakeholders in multiple jurisdictions that medical billing should be viewed as a core competency of medical education, though there is an apparent inertia to include this competency in medical education curricula. Penalties for non-compliant medical billing are serious and medical practitioners are at risk of random audits and investigations for breaches of sometimes incomprehensible, and highly interpretive regulations they may never have been taught.

ConclusionDespite acknowledged significance of waste in health systems due to poor practitioner knowledge of billing practices, there has been very little research to date on education interventions to improve health system efficiency at a practitioner level. Subpopulation-specific Machine Learning Prognosis for Underrepresented Patients with Double Prioritized Bias Correction Many clinical datasets are intrinsically imbalanced, dominated by overwhelming majority groups. Off-the-shelf machine learning models that optimize the prognosis of majority patient types (e.g., healthy class) may cause substantial errors on the minority prediction class (e.g., disease class) and demographic subgroups (e.g., Black or young patients). For example, our work found that missed death cases are 3.14 times higher than missed survival cases in a mortality prediction model. In the typical one-machine-learning-model-fits-all paradigm, racial and age disparities are likely to exist, but unreported. What makes it worse is the deceptive nature of widely used whole-population metrics, such as AUC-ROC. We show that some metrics fail to reflect serious prediction deficiencies. To mitigate representational biases, we design a double prioritized (DP) bias correction technique. Our method trains customized models for specific ethnicity or age groups, a substantial departure from the one-model-predicts-all convention. We report our findings on four prognosis tasks over two imbalanced clinical datasets. DP reduces relative disparities among race and age groups, 5.6% to 86.8% better than the 8 existing sampling solutions being compared, in terms of the minority class' recall. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. Prognostication for prelabor rupture of membranes and the time of delivery in nationwide insured women: development, validation, and deployment ImportancePrognostic predictions of prelabor rupture of membranes lack proper sample sizes and external validation.

ObjectiveTo develop, validate, and deploy statistical and/or machine learning prediction models using medical histories for prelabor rupture of membranes and the time of delivery.

DesignA retrospective cohort design within 2-year period (2015 to 2016) of a single-payer, government-owned health insurance database covering 75.8% individuals in a country

SettingNationwide healthcare providers (n=22,024) at primary, secondary, and tertiary levels

Participants12-to-55-year-old women that visit healthcare providers using the insurance from [~]1% random sample of insurance holders stratified by healthcare provider and category of family: (1) never visit; (2) visit only primary care; and (3) visit all levels of care

PredictorsMedical histories of diagnosis and procedure (International Classification of Disease version 10) before the latest visit of outcome within the database period

Main Outcomes and MeasuresPrelabor rupture of membranes prognostication (area under curve, with sensitivity, specificity, and likelihood ratio), the time of delivery estimation (root mean square error), and inference time (minutes), with 95% confidence interval

ResultsWe selected 219,272 women aged 33 {+/-} 12 years. The best prognostication achieved area under curve 0.73 (0.72 to 0.75), sensitivity 0.494 (0.489 to 0.500), specificity 0.816 (0.814 to 0.818), and likelihood ratio being positive 2.68 (2.63 to 2.75) and negative 0.62 (0.61 to 0.63). This outperformed models from previous studies according to area under curve of an external validation set, including one using a biomarker (area under curve 0.641; sensitivity 0.419; sensitivity 0.863; positive likelihood ratio 3.06; negative likelihood ratio 0.67; n=1177). Meanwhile, the best estimation achieved {+/-} 2.2 and 2.6 weeks respectively for predicted events and non-events. Our web application only took 5.14 minutes (5.11 to 5.18) per prediction.

Conclusions and RelevancePrelabor rupture of membranes and the time of delivery were predicted by medical histories; but, an impact study is required before clinical application.

Key PointsO_ST_ABSQuestionC_ST_ABSCan we use medical histories of diagnosis and procedure in electronic health records to predict prelabor rupture of membranes and the time of delivery before the day in nationwide insured women?

FindingsIn this prognostic study applying retrospective cohort paradigm, a significant predictive performance was achieved and validated. The area under receiver operating characteristics curve was 0.73 with the estimation errors of {+/-} 2.2 and 2.6 weeks for the time of delivery.

MeaningPreliminary prediction can be conducted in a wide population of insured women to predict prelabor rupture of membranes and estimate the time of delivery. Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface Prosthetics and orthotics have been recognized for decades as a potential means to restore hand function and independence to individuals living with impairment due to stroke. However, 75% of stroke survivors, caregivers, and health care professionals (HCP) believe current practices are insufficient, specifically calling out the upper extremity as an area where innovation is needed to develop highly usable prosthetics/orthotics for the stroke population. A promising method for controlling upper limb technologies is to infer movement intent non-invasively from surface electromyography (EMG) activity. While this approach has garnered significant attention in the literature, existing technologies are often limited to research settings and struggle to meet stated user needs. To address these limitations, we have developed the NeuroLife(R) EMG System, which consists of a wearable forearm sleeve with 150 embedded electrodes and associated hardware and software to record and decode surface EMG. Here, we demonstrate accurate decoding of 12 functional hand, wrist, and forearm movements, including multiple types of grasps from participants with varying levels of chronic impairment from stroke, with an overall accuracy of 77.1{+/-}5.6%. Importantly, we demonstrate the ability to decode a subset of 3 fundamental movements in individuals with severe hand impairment at 85.4{+/-}6.4% accuracy, highlighting the potential as a control mechanism for assistive technologies. Feedback from stroke survivors who tested the system indicates that the sleeves design meets various user needs, including being comfortable, portable, and lightweight. The sleeve is in a form factor such that it can be used at home without an expert technician and can be worn for multiple hours without discomfort. Taken together, the NeuroLife EMG System represents a platform technology to record and decode high-definition EMG for the eventual real-time control of assistive devices in a form factor designed to meet user needs. How Informative Were Early SARS-CoV-2 Treatment and Prevention Trials? A longitudinal cohort analysis of trials registered on clinicaltrials.gov BackgroundEarly in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

MethodsWe created a cohort of SARS-CoV-2 treatment and prevention efficacy trials that were initiated from 2020-01-01 to 2020-06-30 using ClinicalTrials.gov registration records. We evaluated trials on 3 criteria of informativeness: potential redundancy, design quality and feasibility of patient-participant recruitment. The study protocol was prospectively registered with the Open Science Framework (https://osf.io/fp726/).

ResultsWe included 500 trials in our cohort, 58% of which were Phase 2 and 84.8% were directed towards the treatment of SARS-CoV-2. Close to one third of trials met all three criteria and were deemed informative (29.0% (95% Confidence Interval 23.7 - 36.9)). The proportion of potentially redundant trials in our cohort was 4.1%. Over half of the trials in our cohort (56.2%) did not meet our criteria for high quality trial design. The proportion of trials with infeasible patient-participant recruitment was 22.6%.

ConclusionsLess than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic. Short Practical Regimen of Acupuncture for Melasma: A Prospective Cohort Study in a Tertiary Hospital in Thailand BackgroundMelasma is a common skin pigmentation disorder. Acupuncture shows benefits for patients with melasma, although no standardized method or optimal number of sessions have been determined.

ObjectiveTo comparatively assess clinical outcomes of melasma between five vs ten standard acupuncture sessions.

MethodsWe performed a prospective observational cohort study in all melasma patients at the Acupuncture Clinic, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. All patients were treated with standard acupuncture procedure twice a week and were evaluated after the fifth and the tenth sessions of acupuncture, with a follow-up one week after the last session. Participants were divided into two treatment groups: Groups A and B received five and ten acupuncture sessions respectively. Melasma outcomes were assessed by using the Melanin Index (MI), Melasma Area and Severity Index (MASI), patient-reported improvement scores and acupuncture-related adverse events.

ResultsOf 113 participants, 67 received five sessions of acupuncture treatment while 39 received ten sessions. 7 participants did not finish treatment. After five sessions of acupuncture in Group A, the mean MI decreased by 28.7 (95%CI -38.5 to -18.8), whereas the median MASI decreased by 3.4 (-6.9, -1.2) points. After ten sessions of acupuncture in Group B, the mean MI decreased by 31.3 (95%CI -45.0 to -17.6), whereas the median MASI decreased by 5.4 (-9.9, - 3.0) points. The first five sessions of acupuncture had a higher effect on the change in magnitude than the last five sessions, although there was no statistically significant difference. However, ten-session of acupuncture, had not reached the peak benefit on melasma yet. Further studies should be done with a higher number of sessions to determine the optimal rounds of treatment. Twenty-nine participants reported minor side effects, mostly consisting of persistent pain and small hematoma. Group B had RR of having adverse events 1.8 times (95% CI 1.0-3.4) compared to group A.

ConclusionAcupuncture has a potential dose-response effect on clinical and patient-reported melasma outcomes with minor side effects. Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. Humoral immune responses to COVID-19 vaccination in people living with HIV receiving suppressive antiretroviral therapy Humoral responses to COVID-19 vaccines in people living with HIV (PLWH) remain incompletely understood. We measured circulating antibodies against the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, ACE2 displacement and live viral neutralization activities one month following the first and second COVID-19 vaccine doses in 100 adult PLWH and 152 controls. All PLWH were receiving suppressive antiretroviral therapy, with median CD4+ T-cell counts of 710 (IQR 525-935) cells/mm3. Nadir CD4+ T-cell counts ranged as low as <10 (median 280; IQR 120-490) cells/mm3. After adjustment for sociodemographic, health and vaccine-related variables, HIV infection was significantly associated with 0.2 log10 lower anti-RBD antibody concentrations (p=0.03) and [~]11% lower ACE2 displacement activity (p=0.02), but not lower viral neutralization (p=0.1) after one vaccine dose. Following two doses however, HIV was no longer significantly associated with the magnitude of any response measured. Rather, older age, a higher burden of chronic health conditions, and having received two ChAdOx1 doses (versus a heterologous or dual mRNA vaccine regimen) were independently associated with lower responses. After two vaccine doses, no significant correlation was observed between the most recent or nadir CD4+ T-cell counts and vaccine responses in PLWH. These results suggest that PLWH with well-controlled viral loads on antiretroviral therapy and CD4+ T-cell counts in a healthy range will generally not require a third COVID-19 vaccine dose as part of their initial immunization series, though other factors such as older age, co-morbidities, vaccine regimen type, and durability of vaccine responses will influence when this group may benefit from additional doses. Further studies of PLWH who are not receiving antiretroviral treatment and/or who have low CD4+ T-cell counts are needed. Deep Covid -Covid Diagnosis Using Deep Neural Networks and Transfer Learning Coronavirus is a global emergency as of May 2021. If not acted upon by drugs at the right time, coronavirus may result in the death of individuals. Hence early diagnosis is very important along the progress of the disease. This paper focuses on coronavirus detection using x-ray images, for automating the diagnosis pipeline using convolutional neural networks and transfer learning. This could be deployed in places where radiologists are not easily available in order to detect the disease at very early stages. In this study we propose our deep learning architecture for the classification task, which is trained with modified images, through multiple steps of preprocessing. Our classification method uses convolutional neural networks and transfer learning architecture for classifying the images. Our findings yield an accuracy value of 91.03%, precision of 89.76 %, recall value of 96.67% and F1 score of 93.09%. Clinical Characteristics and Outcomes of Critically ill Mechanically Ventilated COVID-19 Patients Receiving interleukin-6 Receptor Antagonists and Corticosteroid Therapy: A Multicenter International Observational Study ObjectivesThe interest in interleukin-6 receptor antagonists (IL-6RA) and steroids have increased recently due to their potential role as immunomodulatory effect in critically ill coronavirus disease (COVID-19). The magnitude of this therapy in subgroups of patients with invasive mechanical ventilation (MV) remains to be fully clarified. We compared the clinical characteristics and outcomes of patients requiring iMV, and receiving IL-6RA and steroids with different steroids regimens.

DesignInternational, multicenter, observational study derived from Viral Infection and Respiratory Illness University Study registry and conducted through Discovery Network, Society of Critical Care Medicine. Marginal structural modeling was used to adjust time-dependent confounders; observations were weighted using inverse probability of treatment weight. A sensitivity analysis was conducted for target trial design.

Setting168 hospitals, 16 countries.

PatientsCovid-19 ICU patients ([&ge;]18 years) requiring MV between March 01,2020, and January 10,2021.

InterventionNone.

Measurements and Main ResultsOf 860 patients met eligibility criteria, 589 received steroids, 170 IL-6RA, and 101 combinations; groups were balanced after adjustment. Median daily steroid dose was 7.5 mg dexamethasone or equivalent (IQR:6-14 mg); 80.8% and 19.2% received low-dose and high-dose steroids, respectively. The median C-reactive protein level was >75 mg/L in majority of our cohort. The use of IL-6R antagonists alone or in combination was not associated with a significant difference in ventilator-free days (VFD) compared to steroids alone with different steroids regimens (adjusted incidence rate ratio [95% CI]): IL-6R antagonists (1.12 [0.88,1.4]), combination (0.83 [0.6,1.14]). Patients treated with low or high-dose steroids had non-significant differences in VFD compared to IL-6RA ({beta}=0.62, 95% CI -1.54,2.78 for low-dose steroid; {beta}=-1.19, 95% CI -3.85,1.47 for high-dose steroid). There was no difference in 28-day mortality and hospital mortality with IL-6RA alone or in combination compared to steroids alone (28-day mortality adjusted odds ratio [95% CI]): IL-6RA (0.68[0.44,1.07]), combination (1.07[0.67,1.70]). Sensitivity analysis findings were consistent with primary analysis. Liver dysfunction was higher in IL-6RA (p=0.04) while rate of bacteremia did not differ among groups.

ConclusionsIn adult ICU COVID-19 patients on iMV, we found no difference in outcomes between those who received IL-6RA, steroids, or combination therapy and those who received IL-6RA or low-or high-dose steroids. Further randomized trials are needed to enhance our understanding for IL-6RA safety with different steroids regimen and the magnitude of benefit in those subgroups of patients. Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of evidence strength IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.

ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.

DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. Effectiveness of a short term induction regimen of a biosimilar Adalimumab in the long term management of symptomatic Ankylosing Spondylitis Symptomatic Ankylosing Spondylitis: A Community Based Proof of Concept Observational Study IntroductionCost and drug toxicity often deter prolonged therapeutic use of anti-TNF agents in ankylosing spondylitis (AS). A planned study was completed to endorse our clinic based observation of long term relief following short-term administration of anti-TNF agent.

Methods50 consenting patients with symptomatic active chronic AS under rheumatology care in a community clinic were enrolled. They had no past history of anti-TNF use. 40 mg standard biosimilar adalimumab (BS-ADA, Exemptia trade name)was injected subcutaneously every fortnight for six injections (10 weeks). Patients were monitored at several time points. Improvement was assessed at regular interval as per protocol which included standard indices (Bath and Assessment Spondyloarthritis International Society /ASAS). An intention to treat analysis with significant p<0.05 was carried out.

ResultsPatients showed early and substantial significant improvement in pain, NSAID requirement, function and in several indices (ASAS 20 & 40, ASAS partial remission, BASDAI, BASFI, ASDAS) which persisted after stopping injections. 84% and 52 % of patients respectively showed ASAS 20 improvement at week 12 and 48: corresponding ASAS partial remission 34% and 24%. Over 50% patients maintained prolonged improvement and provided proof of concept (defined a-priori). Serum Interleukin-6 assay showed a sharp reduction at 24 weeks. None developed TB or serious drug toxicity. 11 patients withdrew (mostly inadequate response). Absence of control was a limitation.

ConclusionA ten-week administration of biosimilar adalimumab in difficult to treat AS showed early substantial improvement which often persisted for 24 weeks. This unconventional strategy was socioeconomically appealing. It merits further validation and acceptance especially in resource strained settings. Gene-level germline contributions to clinical risk of recurrence scores in Black and White breast cancer patients Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer (BC). Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to BC disparities, evidence for biological and germline contributions is emerging. We investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N=1,043 WW, 1083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; Proliferation Score; ROR-P: ROR-S plus Proliferation Score) on imputed Genetically-Regulated tumor eXpression (GReX). Using Bayesian multivariate regression and adaptive shrinkage, we tested GReX-prioritized genes for associations with PAM50 tumor expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, we detected 7 and 1 GReX-prioritized genes among WW and BW. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower Proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among BC patients, we find differential germline associations with CRS by race, underscoring the need for larger, diverse datasets in molecular studies of BC. Our findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings.

SIGNIFICANCEWe find race-specific genetic associations with breast cancer risk-of-recurrence scores (CRS). Follow-up analyses suggest mediation of these associations by PAM50 molecular subtype and gene expression, with implications for clinical interpretation of CRS. One Year of Evidence on Mental Health Disorders in China during the COVID-19 Crisis - A Systematic Review and Meta-Analysis This paper provides a systematic review and meta-analysis on the prevalence rate of mental health issues of general population, general and frontline healthcare workers (HCWs) in China over one year of the COVID-19 crisis. We systematically searched PubMed, Embase, Web of Science, and Medrxiv at November 16th, 2020, pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the heterogeneity. The meta-regression results uncovered several predictors of the prevalence rates, including severity, type of mental issues, population, sampling location, and study quality. Pooled prevalence rates are significantly different from, yet largely between, the findings of previous meta-analyses, suggesting the results of our larger study are consistent with yet more accurate than the findings of the smaller, previous meta-analyses. The prevalence rates of distress and insomnia and those of frontline HCWs are higher suggest future research and interventions should pay more attention to those mental outcomes and populations. Our findings suggest a need to examine the prevalence rates at varying levels of severity. The one-year cumulative evidence on sampling locations (Wuhan vs. non-Wuhan) corroborates the typhoon eye effect theory.

Trial registrationCRD4202022059 Elevated Levels of IL-6 in IgA Nephropathy patients are induced by an Epigenetically Driven Mechanism Triggered by Viral and Bacterial RNA Recently, a several models has been proposed to describe the pathogenesis of Immunoglobulin A nephropathy (IgAN), and among them the multihit and the gut-microbiota. These models explain the pathogenesis of IgAN caused by the production of aberrant IgA, but it is believed further predisposing factors are present, including immunological, genetic, environmental, or nutritional factors that can influence the pathogenesis and that could be useful for development of precision nephrology and personalized therapy.

Newly, the role of IL-6 in pathogenesis is becoming increasingly important. It is essential for glomerular immunoglobulin A deposition and the development of renal pathology in Cd37-deficient mice, even if the reason why levels of IL-6 are elevated in IgAN patients is not well understood. One attainable hypothesis on high levels of IL-6 in IgAN comes out from our recent whole genome DNA methylation screening in IgAN patients, that identified, among others, a hypermethylated region comprising Vault RNA 2-1 (VTRNA2-1), a non-coding RNA also known as precursor of miR-886 (pre-mi-RNA). Consistently, the VTRNA2-1 expression was found down-regulated in IgAN patients.

Here we confirm that VTRNA2-1 is low expressed in IgAN subjects compared to HS and we found that also in transplanted IgAN patients (TP-IgAN), compared to non IgAN transplanted patients (TP), the VTRNA2-1 transcript was expressed at level very low. We found that in IgAN patients with downregulated VTRNA2-1, PKR is overactivated, coherently with the role of the VTRNA2-1 that binds to PKR and inhibits its phosphorylation. The loss of the VTRNA2-1 natural restrain causes, in turn, the activation of CREB by PKR. We found CREB, a classical cAMP-inducible CRE-binding factor interacting with a region of the IL-6 promoter and leading to IL-6 production, overactivated both in IgAN and in TP-IgAN patients. Effectively, in the same patients, we found elevated levels of IL-6 correlating with CREB and PKR phosphorylation.

Since PKR is normally activated by bacterial and viral RNA we hypothesized that these microrganisms can further activate the PKR/CREB/IL-6 pathway leading to an excess of IL-6 production, explaining both the high levels of IL-6, both infection involvement in the disease, both cases of IgAN associated with COVID-19 infection and with COVID-19 RNA-vaccination, and recent data showing microbiota involvment in IgAN.

Effectively, we found that Effectively, we sfound that both the RNA poly(I:C) and the COVID-19 RNA-vaccine stimulation significantly increase the IL-6 levels in IgAN patient PBMCs.

The PKR/CREB/IL-6 pathway may be very important also in the setting of renal transplantation. We found that this pathway is upregulated also in IgAN transplanted patients. Recent studies showed that the cumulative risk of IgA nephropathy recurrence increases after transplant and is associated with a 3.7-fold greater risk of graft loss. Finally, we showed that the IL-6 secretion can be reduced by the PKR inhibitor imoxin.

In conclusion, the discovery of the upregulated VTRNA2-1/PKR/CREB/IL-6 pathway in IgAN patients may provide novel approach to treat the disease and may be useful for development of precision nephrology and personalized therapy, possibly by checking the VTRNA2-1 methylation level in IgAN patients. A Novel Penalized Inverse-Variance Weighted Estimator for Mendelian Randomization with Applications to COVID-19 Outcomes SO_SCPLOWUMMARYC_SCPLOWMendelian randomization (MR) utilizes genetic variants as instrumental variables (IVs) to estimate the causal effect of an exposure variable on an outcome of interest even in the presence of unmeasured confounders. However, the popular inverse-variance weighted (IVW) estimator could be biased in the presence of weak IVs, a common challenge in MR studies. In this article, we develop a novel penalized inverse-variance weighted (pIVW) estimator, which adjusts the original IVW estimator to account for the weak IV issue by using a penalization approach to prevent the denominator of the pIVW estimator from being close to zero. Moreover, we adjust the variance estimation of the pIVW estimator to account for the presence of horizontal pleiotropy. We show that the recently proposed debiased IVW (dIVW) estimator is a special case of our proposed pIVW estimator. We further prove that the pIVW estimator has smaller bias and variance than the dIVW estimator under some regularity conditions. We also conduct extensive simulation studies to demonstrate the performance of the proposed pIVW estimator. Furthermore, we apply the pIVW estimator to estimate the causal effects of five obesity-related exposures on three coronavirus disease 2019 (COVID-19) outcomes. Notably, we find that hypertensive disease is associated with an increased risk of hospitalized COVID-19, and peripheral vascular disease and higher body mass index are associated with increased risks of COVID-19 infection, hospitalized COVID-19 and critically ill COVID-19. The R package for the pIVW method is publicly available at https://github.com/siqixu/mr.pivw. Colorectal Cancer Disparities Across the Continuum of Cancer Care with a Focus on Surgery and Black Patients: A Systematic Review and Meta-Analysis ImportanceDespite increases in screening among vulnerable populations, colorectal cancer disparities persist.

ObjectiveTo direct future efforts towards high impact opportunities in addressing these disparities, we performed a systematic review and meta-analysis of the colorectal cancer disparities literature with a focus on the utilization of Surgery, the primary treatment for colorectal cancer.

Data SourcesTwo electronic databases (PubMed and SCOPUS) were searched for prospective and retrospective studies reporting on colorectal cancer disparities between 2011 and March 29, 2021.

Study SelectionStudies for the systematic review were selected if: (1) reported on disparities within colorectal, colon, or rectal cancer (2) articles were published in the English language (3) articles used only United States-sourced data.

Studies for the meta-analysis were selected if: (1) reported on at least one of three utilization of surgery outcomes: receipt of colorectal, colon, or rectal surgery, refusal of surgery, or receipt of laparoscopic versus open surgery (2) Outcomes were reported as Odds ratio according to multivariate analysis.

Data Extraction and SynthesisQuality appraisal and data extraction were performed independently by 2 reviewers using the Newcastle-Ottawa Scale for quality assessment. For the meta-analysis, pooled multivariate odds ratios for the three outcomes regarding utilization of surgery were separately calculated according to fixed or random-effects models. Reporting followed the Preferred Reporting Items for Systematic Review and Meta-analyses guidelines.

Main Outcomes and MeasuresSystematic Review: The volume of publications attributed to the following sectors of the colorectal cancer care continuum: (1) Prevention, Screening, or Diagnosis (2) Treatment (3) Survivorship (4) End-of-life Care. Meta-analysis: Receipt of Colorectal, Colon, or Rectal Surgery and Black Race, Refusal of Surgery and Black Race, or Receipt of Laparoscopic versus Open Surgery and Black Race.

ResultsThe systematic review included 1,199 relevant publications. Among them, 60% were focused on Prevention, Screening, or Diagnosis, followed by Survivorship (20%), Treatment (15%), and End-of-Life Care (1%). Within the studies reporting on treatment disparities, 46% were focused on Race/Ethnicity, followed by Socioeconomic Status (28%), Age (17%), Gender (6%), Disabilities/Comorbidities (3%), and LGBTQI+ (0%). A total of 16 studies, including 1,110,674 patients, were applied to three separate meta-analyses regarding utilization of Surgery. Patients of black race were less likely to receive colorectal, or colon, or rectal surgery (OR 0.75, 95% CI 0.67-0.83), less likely to receive laparoscopic versus open colorectal cancer surgery (OR 0.91, 95% CI 0.88-0.94), and twice as likely to refuse colon surgery (OR 2.41, 95% CI 1.91-3.06).

Conclusions and RelevanceThe majority of research, to date, related to colorectal cancer disparities is focused on prevention, screening, or diagnosis and a minimal amount is dedicated to treatment. Additionally, all of the limited publications related to colorectal cancer surgery, as a treatment modality, are observational in nature. The application of this knowledge of past efforts and current continuing adverse outcomes is required in order to shift the focus of the research community towards treatment. In particular, research addressing surgical disparities is necessary, as surgery remains the primary treatment for colorectal cancer.