University students and staff able to maintain low daily contact numbers during various COVID-19 guideline periods IntroductionUK universities re-opened in September 2020, despite the on-going coronavirus epidemic. During the first term, various national social distancing measures were introduced, including banning groups of >6 people and the second lockdown in November. COVID-19 can spread rapidly in university-settings, and students adherence to social distancing measures is critical for controlling transmission.

MethodsWe measured university staff and student contact patterns via an online, longitudinal survey capturing self-reported contacts on the previous day. We investigated the change in contacts associated with COVID-19 guidance periods: post-first lockdown (23/06/2020-03/07/2020), relaxed guidance period (04/07/2020-13/09/2020), "rule-of-six" period (14/09/2020-04/11/2020), and the second lockdown (05/11/2020-25/11/2020).

Results722 staff (4199 responses) (mean household size: 2.6) and 738 students (1906 responses) (mean household size: 4.5) were included in the study. Contact number decreased with age. Staff in single-person households reported fewer contacts than individuals in 2-and 3-person households, and individuals in 4-and 5-person households reported more contacts.

For staff, daily contacts were higher in the relaxed guidance and "rule-of-six" periods (means: 3.2 and 3.5, respectively; medians: 3) than the post-first lockdown and second lockdown periods (means: 4.5 and 5.4, respectively; medians: 2). Few students responded until 05/10/2020, after which the median student contacts was 2 and the mean was 5.7, until the second lockdown when it dropped to 3.1.

DiscussionUniversity staff and students responded to national guidance by altering their social contacts. The response in staff and students was similar, suggesting that students are able to adhere to social distancing guidance while at university.
SeroTracker-RoB: an approach to automating reproducible risk of bias assessment of seroprevalence studies BackgroundEvaluating seroprevalence study risk of bias (RoB) is crucial for robust infection surveillance, but can be a time-consuming and subjective process. We aimed to develop decision rules for reproducible RoB assessment and an automated tool to implement these decision rules.

MethodsWe developed the SeroTracker-RoB approach to RoB assessment. To do so, we created objective criteria for items on the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Prevalence Studies and developed decision rules for RoB based on these items. The criteria and decision rules were based on published guidance for assessing RoB for prevalence studies and expert opinion. Decision rules were validated against the SeroTracker database of seroprevalence studies, which included consensus manual RoB judgements from two independent reviewers. We measured efficiency by calculating paired-samples t-test for time to judge RoB using the automated tool versus manually for 25 randomly selected articles from the SeroTracker database, coverage as the proportion of database studies where the decision rules could evaluate RoB, and reliability by calculating intraclass correlations between automated and manual RoB assessments.

ResultsWe established objective criteria for seven of nine JBI items. We developed a set of decision rules with 61 branches. The SeroTracker-RoB tool was significantly faster than manual assessment with a mean time of 0.80 vs. 2.93 minutes per article (p<0.001), classified 100% (n = 2,070) of studies, and had good reliability compared to manual review (intraclass correlation 0.77, 95% confidence interval 0.74 to 0.80). The SeroTracker-RoB Excel Tool embeds this approach in a simple data extraction sheet for use by other researchers.

ConclusionsThe SeroTracker-RoB approach was faster than manual assessment, with complete coverage and good reliability compared to two independent human reviewers. This approach and tool enable rapid, transparent, and reproducible evidence synthesis of infection prevalence studies, and may support public health efforts during future outbreaks and pandemics.

O_TEXTBOXWhat is new?

O_LIWhat is already known: Risk of bias assessments are a core element of evidence synthesis but can be time consuming and subjective. As such, there is a need for validated and transparent tools to automate such assessments, particularly during disease outbreaks and pandemics to inform public health decision making. However, there are currently no automated tools for risk of bias assessment of prevalence studies.
C_LIO_LIWhat is new: We developed a reproducible approach to risk of bias assessment for SARS-CoV-2 seroprevalence studies. The automated approach was five times faster than manual human assessment, successfully categorized all 2,070 studies that it was tested on, and had good agreement with manual review. We built a simple Excel tool so that other researchers can use this automated approach.
C_LIO_LIPotential impact: The SeroTracker-RoB approach and tool enables rapid, transparent, and reproducible risk of bias assessments for SARS-CoV-2 seroprevalence studies, and could be readily adapted for other types of disease prevalence studies. This process may also be applicable to automation of critical appraisal and risk of bias assessment for other types of studies and in other scientific disciplines.
C_LI

C_TEXTBOX
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. 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. 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. Characterization of small fiber neuropathy in hypermobile Ehlers Danlos Syndrome Ehlers Danlos syndromes (EDS) are heritable connective tissue disorders. The hypermobile form (hEDS) is the most frequent, yet the only one without an identified genetic mutation. Patients suffering from symptomatic joint hypermobility, yet not fulfilling the hEDS criteria, enter the Hypermobility Spectrum Disorder (HSD) category. In addition to musculoskeletal pain affecting joints, hEDS/HSD patients often describe painful sensations, hypoesthesia, and autonomic symptoms suggesting a neuropathic component. Small fiber neuropathy (SFN) refers to the dysfunction or damage of A-{delta} and C-fibers, which relay thermal and nociceptive information as well as mediating autonomic function. SFN has been suggested by prior studies in hEDS but these early findings (case series N[&le;]20) with sole reliance on intraepidermal nerve fiber density (IENFD) called for a larger sample combined with functional testing.

In this retrospective chart extraction from 79 hEDS/HSD patients referred to a pain center due to neuropathic pain or dysautonomia, both functional (Quantitative Sensory Testing (QST), N=79) and structural (IENFD, N=69) evaluations of small nerve fibers were analyzed in combination with clinical data and standardized questionnaires.

All the patients reported moderate to severe pain interfering with daily life. A decreased thermal detection (QST) was shown in 55/79 patients (70%) and a decreased IENFD in 54/69 patients (78%). Hence a small fiber neuropathy (both abnormal IENFD and QST) was definite in 40/69 patients (58%), possible in 23/69 patients (33%) and excluded in only 6/69 patients (9%).

These results add strong evidence for a peripheral neuropathic contribution to pain symptoms in hEDS/HSD, in addition to the known nociceptive and central sensitization components. Such neuropathic contribution could raise the hypothesis of a neurological cause of hEDS, the only EDS syndrome still without a known genetic cause. Hence, our data is leading the way to a better stratification of this very heterogeneous population, which could improve symptommanagement and expand pathophysiological research. Examining the Factor Structure of the DSM-5 Level 1 Cross-Cutting Symptom Measure ObjectivesThe DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) is a transdiagnostic mental health symptom measure that has shown promise in informing clinical diagnostic evaluations and as a screening tool for research. However, few studies have assessed the latent dimensionality of the DSM-XC. We examined the factor structure of the DSM-XC in a large convenience sample of participants with varying degrees of psychological health.

MethodsParticipants (n=3533) enrolled in a protocol conducted at the National Institute of Mental Health (NCT04339790). We used a factor analytic framework to evaluate an existing two-factor solution (Lace & Merz, 2020) and two additional candidate solutions.

ResultsThe Lace and Merz solution had acceptable fit. Exploratory factor analysis yielded two candidate solutions: a six-factor (characterized as mood, worry, activation, somatic, thoughts, and substance use) and a bifactor (general factor of non-specific psychopathology, residual factors characterized as internalizing and thought disorder), which both had good fit and full measurement invariance across age, sex, and enrollment date.

ConclusionsOur findings confirm that the DSM-XC may be conceptualized as a multidimensional instrument and provide a scoring solution for researchers who wish to measure distinct constructs. Future research on the psychometric profile of the DSM-XC is needed, focused on the validity of these candidate solutions and their performance across research populations and settings. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

Material & MethodsUsing mass spectrometry and immunoblotting analyses, we profiled degradation patterns of cytoskeletal proteins in deceased (n=55) and living (n=10) donor kidneys.

ResultsWe found that in DBD kidneys, key podocyte cytoskeletal proteins had been proteolytically cleaved. Generated degradation profiles were not associated to donor related demographic and clinical factors but were associated to suboptimal post-transplant function. Strikingly, -actinin -4 and Talin-1 degradation profiles were not observed in circulatory-death or living-donor kidneys. As Talin-1 is a specific proteolytic target of Calpain-1, we investigated a potential trigger of Calpain activation and Talin-1 degradation using ex-vivo precision-cut human kidney slices and in-vitro immortalised human podocytes. Notably, we found that Transforming-Growth Factor-{beta} (TGF-{beta}) activated Calpain-1 and proteolytically cleaved Talin-1 to generate distinct peptide fragments. These peptide fragments were of similar size and matched the degradation patterns observed in DBD kidneys. Talin-1 degradation was prevented in vitro by Calpain-1 inhibition.

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Trajectory of Growth of SARS-CoV-2 Variants in Houston, Texas, January through May 2021 Based on 12,476 Genome Sequences Genetic variants of the SARS-CoV-2 virus are of substantial concern because they can detrimentally alter the pandemic course and disease features in individual patients. Here we report SARS-CoV-2 genome sequences from 12,476 patients in the Houston Methodist healthcare system diagnosed from January 1, 2021 through May 31, 2021. The SARS-CoV-2 variant designated U.K. B.1.1.7 increased rapidly and caused 63%-90% of all new cases in the Houston area in the latter half of May. Eleven of the 3,276 B.1.1.7 genomes had an E484K change in spike protein. Compared with non-B.1.1.7 patients, individuals with B.1.1.7 had a significantly lower cycle threshold value (a proxy for higher virus load) and significantly higher rate of hospitalization. Other variants (e.g., B.1.429, B.1.427, P.1, P.2, and R.1) also increased rapidly, although the magnitude was less than for B.1.1.7. We identified 22 patients infected with B.1.617 "India" variants; these patients had a high rate of hospitalization. Vaccine breakthrough cases (n=207) were caused by a heterogeneous array of virus genotypes, including many that are not variants of interest or concern. In the aggregate, our study delineates the trajectory of concerning SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston, and heralds the arrival and spread of B.1.617 variants in the metroplex. The effect of stimulus duration on preferences for gain adjustments when listening to speech ObjectivesIn the personalisation of hearing aid fittings, gain is often adjusted to suit patient preferences using live speech. When using brief sentences as stimuli, the minimum gain adjustments necessary to elicit consistent preferences ( preference thresholds) were previously found to be much greater than typical adjustments in current practice. The current study examined the role of duration on preference thresholds.

DesignParticipants heard 2, 4 and 6-s segments of a continuous monologue presented successively in pairs. The first segment of each pair was presented at each individuals real-ear or prescribed gain. The second segment was presented with a {+/-}0-12 dB gain adjustment in one of three frequency bands. Participants judged whether the second was "better", "worse" or "no different" from the first.

Study SampleTwenty-nine adults, all with hearing-aid experience.

ResultsThe minimum gain adjustments needed to elicit "better" or "worse" judgments decreased with increasing duration for most adjustments. Inter-participant agreement and intra-participant reliability increased with increasing duration up to 4 s, then remained stable.

ConclusionsProviding longer stimuli improves the likelihood of patients providing reliable judgments of hearing-aid gain adjustments, but the effect is limited, and alternative fitting methods may be more viable for effective hearing-aid personalisation. DNR orders in SARS-CoV-2 patients: a retrospective validation study in a Swiss COVID-19 Center BackgroundThe worldwide pandemic situation forced many hospitals to adapt COVID-19 management strategies. In this scenario, the Swiss Academy of Medical Sciences (SAMW/ASSM) organized national guidelines based on expert opinion to identify Do-Not-Resuscitate (DNR) patients, to reduce futile ICU admission and resource misuse. However, the practical impact of this standardized national protocol has not been yet evaluated. In our specialized COVID-19 Center, we investigated characteristics and mortality of DNR patients identified according to national standardized protocol, comparing them to non-DNR patients.

MethodsThis was a pilot retrospective validation study, evaluating consecutive hospital admitted COVID-19 patients. Primary outcome was 30-days survival of DNR patients in comparison to the control group. Secondary outcomes reported quality of treatment of deceased patients, especially of agitation/sedation and dyspnea, using respectively the Richmond Agitation-Sedation Scale - Palliative care (RASS-PAL) for sedation and agitation (+4/-5) and the modified Borg Scale for dyspnea (1-10).

ResultsFrom March 16 to April 1, 2020, 213 consecutive patients were triaged; at 30-days follow-up, 9 patients (22.5%) died in the DNR group, 4 (2.2%) in the control group. The higher mortality rate in the DNR group was further confirmed by Log-Rank Mantel-Cox (23.104, p < 0.0001). In the DNR-group deceased patients, end-of-life support was performed with oxygen (100%), opioids (100%) and sedatives (89%); the mean RASS-PAL improved from 2.2 to -1.8 (p < 0.0001) and the Borg scale improved from 5.7 to 4.7 (p = 0.581).

ConclusionA national standardized protocol identified patients at higher risk of short-term death. Although the legal status of DNRs varies from country to country, the implementation of national standardized protocol could be the way to guarantee a better treatment of COVID-19 patients in a pandemic situation with limited resources. Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis Fecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2x2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after six weeks of treatment, versus 2 of 11 non-pretreated patients (odds ratio: 1.69, 95% confidence interval: -0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer. Feasibility of an online Langerian mindfulness program for stroke survivors and caregivers BackgroundMindfulness is promising for individuals with neurological disorders and their caregivers to improve psychological well-being. The potential application of a Langerian mindfulness intervention, focused on attention to variability, however, is still unknown.

ObjectiveTo determine the feasibility (usability, satisfaction, and potential effectiveness on psychological well-being) of an online mindfulness intervention for stroke survivors and caregivers.

MethodologyUsing mixed-methods, 11 stroke survivors and 3 caregivers participated in a 3-week, online, Langerian mindfulness intervention. A semi-structured interview assessed the interventions usability and gathered feedback. Self-reported measures about psychological well-being were documented remotely three times (pre, post, one-month follow-up).

ResultsQualitatively, participants were highly satisfied with the intervention, reported subjective benefits, but the usability of the online platform was poor. None of the self-reported measures changed over time.

ConclusionThis study provided evidence of feasibility of an online Langerian mindfulness intervention in a new population: stroke survivors and caregivers. GARD is a pan-cancer predictor of radiation therapy benefit BackgroundDespite advances in cancer genomics, radiation therapy (RT) is still prescribed based on an empiric one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic adjusted radiation dose (GARD) to personalize RT prescription dose based on the biological effect of a given physical RT dose, calculated using individual tumor genomics. We hypothesize that GARD will reveal interpatient heterogeneity associated with opportunities to improve outcomes compared to physical RT dose alone. To test this hypothesis, and the GARD-based RT dosing paradigm, we performed a pooled pan-cancer analysis in 11 separate clinical cohorts of 1,615 unique patients with 7 different cancer types that represent all available cohorts with the data required to calculate GARD, together with clinical outcome.

MethodsUsing 11 previously-published datasets of cancers including breast, head and neck, non-small cell lung, pancreas, endometrium, melanoma and glioma, we defined two clinical endpoints: (i) time to first recurrence and (ii) overall survival, comprising 1,298 (982 +RT, 316 -RT) and 677 patients (424 +RT, 253 -RT), respectively. We used Cox regression stratified by cohort to test association between GARD and outcome with separate models using RT dose and sham-GARD for comparison. Interaction tests between GARD and treatment (+/- RT) were performed using the Wald statistic.

ResultsPooled analysis of all available data reveal that GARD as a continuous variable is associated with recurrence (HR = 0.982, CI [0.970, 0.994], p = 0.002) and survival (HR = 0.970, CI [0.953, 0.988], p = 0.001). The interaction test revealed the effect of GARD on survival depends on whether or not that patient received RT (Wald statistic: p=0.011). Physical RT dose and sham-GARD were not significantly associated with either outcome.

ConclusionsThe biologic effect of radiation therapy, as quantified by GARD, is significantly associated with recurrence and survival for those patients treated with radiation: it is predictive of RT benefit; and physical RT dose is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalizing RT prescription dose. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Prevalence of vitamin D is not associated with the COVID-19 epidemic in Europe. A critical update of the existing evidence. BackgroundCOVID-19 has emerged as a global pandemic, affecting nearly 104 million people worldwide as of February 4th 2021. In previous published studies, the association between the mean Vit D status of each country and COVID-19 infection rate, and mortality among the adult population in European countries was examined. The aim of this study was to re-examine the relationship between the Vit D status of each country and COVID-19 infection, recovery, and mortality using updated data and a different methodological approach.

MethodsInformation only form the last decade on Vit D concentration/deficiency for each country was retrieved through literature search on PubMed(R) database. As of February, 4th 2021, COVID-19 infections and mortalities per one million population as well as total recoveries were extracted from the Worldometer website. The association between vitamin D deficiency and COVID-19 infection, recovery, and mortality were explored using correlation coefficients and scatterplots.

FindingsThe prevalence of vitamin D deficiency among European countries ranged from 6.0 (Finland) to 75.5% (Turkey), with several countries facing more than 50% of vitamin D deficiency among their population. Non-significant correlations were observed between the number of COVID-19 infections (r=0.190; p=0.374), recoveries (rs=0.317, p=0.131), and mortalities (r=0.129; p=0.549) per one million population, with the prevalence of vitamin D deficiency.

InterpretationPrevalence of vitamin D deficiency was not significantly associated with either number of infections, recoveries or mortality rate of COVID-19 among European countries. Thus, it is an important parameter to be considered when implementing preventive measures to face COVID-19.

FundingNone 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. A Cross-Sectional Examination of Conflict-of-Interest Disclosures of Physician-Authors Publishing in High-Impact US Medical Journals ObjectiveTo assess the accuracy of self-reported financial conflict-of-interest (COI) disclosures in the New England Journal of Medicine (NEJM) and Journal of the American Medical Association (JAMA) within the requisite disclosure period prior to article submission.

DesignCross-sectional investigation.

Data SourcesOriginal clinical-trial research articles published in NEJM (n = 206) or JAMA (n = 188) from January 1 to December 31, 2017; self-reported COI disclosure forms submitted to NEJM or JAMA with the authors published articles; Open Payments website (from database inception; latest search: August 2019).

Main outcome measuresFinancial data reported to Open Payments from 2014 to 2016 (time period that included all subjects requisite disclosure windows) were compared to self-reported disclosure forms submitted to the journals. Payments were defined as those not associated with a research study or formal research funding. Payment types were categorized as "disclosed," "undisclosed," "indeterminate," or "unrelated."

ResultsThirty-one articles from NEJM and 31 articles from JAMA met inclusion criteria. The physician-authors (n = 118) received a combined total of $7.48 million. Of the 106 authors (89.8%) who received payments, 86 (81.1%) received undisclosed payments. The top 23 most highly compensated received $6.32 million, of which $3.00 million (47.6%) was undisclosed. Disclosure rates were the equivalent between the top 23 and the entire sample.

ConclusionsHigh payment amounts, as well as high proportions of undisclosed financial compensation, regardless of amount received, comprised potential COIs for two influential US medical journals. Further research is needed to explain why such high proportions of general payments were undisclosed and whether journals that rely on self-reported COI disclosure need to reconsider their policies. RELATIONSHIP BETWEEN ADVERSE EVENTS PREVALENCE, PATIENT SAFETY CULTURE AND PATIENT SAFETY PERCEPTION IN A SINGLE SAMPLE OF PATIENTS: A CROSS-SECTIONAL AND CORRELATIONAL STUDY ObjectiveTo assess the relationship between Adverse Events Prevalence, Patient Safety Culture and Patient Safety Perception.

DesignCross-sectional, ex post facto comparative study on a single sample of patients.

SettingFour medium-high-level hospitals were included in the study -- two public and two private from Zulia State in Venezuela.

Participants556 medical records and patients were studied for the prevalence and patient safety perception study, and 397 of the healthcare providers involved in the care of these patients were surveyed for the patient safety culture study, at two public and two private hospitals.

Outcome measurementThe primary outcome of this study was the Association between Adverse Events Prevalence, Patient Safety Culture and Patient Safety Perception, and according to hospital funding type, private and public.

ResultsAn inverse association was observed between Adverse Events Prevalence and its severity and Patient Safety Culture Index (PSCI: rho=-0.8 p=0.5) (95% CI=0.26-0.10) and Patient Safety Perception Index (PSPI: rho=-0.6 p=0.18) (95% CI=0.10-0.28), which were protective factors for patient safety. No association was identified between Patient Safety Culture and Patient Safety Perception (rho=0.0001). No statistical differences were identified by hospital type (p=0.93) (95% CI=0.70-1.2).

ConclusionsThe analysis of the variable correlations studied (AEP, PSC and PSP) within the same sample offers an interesting and useful perspective. In this sample, although no correlation was observed between the three variables as an interacting set, some correlation patterns were observed between pairs of variables that could guide further studies.

Strengths and limitations of this studyO_LIThe association analysis of the three main variables (adverse events prevalence, patient safety culture and patient safety perception) in the same sample of patients and health professionals and over the same time period during which the care process and, consequently, the adverse events took place is an unprecedented and innovative approach, which contributes to the body of knowledge on this field of study.
C_LIO_LIThe relational theoretical framework produced provides a "map" that can facilitate decision-taking and which establishes the variables that should be considered a priority. As a result, it is highly likely to have an impact on the clinical efficiency and safety of healthcare institutions and services.
C_LIO_LIThe study was carried out at both private and public hospitals, enabling the behaviour of the aforementioned variables to be compared and analysed at each type of institution. The literature to date on this approach is scarce and offers little information.
C_LIO_LIAlthough the sample of hospitals selected is not representative of Venezuela, it is representative of the hospitals of one of the most productive and populated states in the country.
C_LIO_LIDuring stages 1 and 2, some resistance to collaborating with and completing the evaluation instruments was identified among the health professionals.
C_LI Xenobiotic tracers uncover the gastrointestinal passage, cellular uptake and Ago2 loading of milk microRNAs in neonates BackgroundExclusive breastfeeding is the best source of nutrition for most infants, but it is not always possible. Enteral nutrition influences intestinal gene regulation and the susceptibility for inflammatory bowel disorders, such as necrotizing enterocolitis (NEC). In modern neonatology it is observed that lactase activity increases during intestinal maturation, but formula-fed infants exhibit lower activity levels than milk-fed infants.

ObjectiveWe interrogate the transmissibility of milk miRNAs, since human breast milk has a high miRNA content in comparison to other body fluids. Our data contribute to the controversial discussion whether milk miRNAs could influence gene regulation in term and preterm neonates and thus might vertically transmit developmental relevant signals.

DesignFollowing their cross-species profiling via miRNA deep-sequencing we utilized dietary xenobiotic taxon-specific milk miRNA as tracers in human and porcine neonates, followed by functional studies in primary human fetal intestinal epithelial cells (HIEC-6) using Ad5-mediated miRNA-gene transfer.

ResultsWe show that mammals have in common many milk miRNAs yet exhibit taxon-specific miRNA fingerprints. We traced intact bovine-specific miRNAs from formula-nutrition in human preterm stool and 9 days after the onset of enteral feeding in intestinal cells of preterm piglets. Few hours after introducing enteral feeding in preterm piglets with supplemented reporter miRNAs (cel-miR-39-5p/-3p), we observed enrichment of the xenobiotic cel-miR in blood serum and in Ago2-immunocomplexes from intestinal biopsies. In contrast, we did not observe xenobiotic miRNAs in neonatal porcine cerebrospinal fluid.

ConclusionsTaken together, our data point to a transmissibility of milk miRNA signals, which could be relevant at least for intestinal maturation. Ad5-based miRNA-gene transfer into HIEC-6 revealed putative milk miRNA targets on the protein and transcriptome levels. Results suggest that milk miRNAs could influence gene expression in intestinal epithelia of neonates under special conditions.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/21262525v4_ufig1.gif" ALT="Figure 1">
View larger version (80K):
org.highwire.dtl.DTLVardef@8e0435org.highwire.dtl.DTLVardef@1b6747corg.highwire.dtl.DTLVardef@1998821org.highwire.dtl.DTLVardef@b84a04_HPS_FORMAT_FIGEXP  M_FIG C_FIG It is already known that exclusive breastfeeding is the best source of nutrition for neonates.Human breast milk has a high miRNA content in comparison to other body fluids. It is controversially discussed whether they could influence gene regulation in term and preterm neonates and thus might vertically transmit developmental relevant signals. Here, we contribute important new findings: Mammals have in common a significant number of milk miRNAs yet exhibit taxon-specific fingerprints. These differences allowed us to exploit xenobiotic miRNAs as tracers in human preterm neonates, who routinely received formula-supplemented nutrition in addition to breast milk. Tracer miRNAs survived the gastrointestinal (GI) transit in human preterm neonates. In a preterm piglet model the reporter miRNA did not only survive GI transit, but accumulated in the bloodstream few hours post-feeding. Moreover, we show that, cel-mir-39-5p and cel-miR-39-3p became loaded to Ago2 in intestinal tissue samples, which is prerequisite for milk microRNAs biological relevance. Adenovirus type 5-based miRNA-gene transfer into HIEC-6 allowed us to examine predicted bovine milk miRNA targets on the protein and transcriptome levels. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness BackgroundMultiple COVID-19 vaccines appear to be safe and efficacious, but only high-income countries have the resources to procure sufficient vaccine doses for most of their eligible populations. The World Health Organization has published guidelines for vaccine prioritisation, but most vaccine impact projections have focused on high-income countries, and few incorporate economic considerations. To address this evidence gap, we projected the health and economic impact of different vaccination scenarios in Sindh province, Pakistan (population: 48 million).

Methods and FindingsWe fitted a compartmental transmission model to COVID-19 cases and deaths in Sindh from 30 April to 15 September 2020. We then projected cases, deaths, and hospitalization outcomes over 10 years under different vaccine scenarios. Finally, we combined these projections with a detailed economic model to estimate incremental costs (from healthcare and partial societal perspectives), disability adjusted life years (DALYs), and incremental cost-effectiveness ratio (ICER) for each scenario.

We project that one-year of vaccine distribution, at delivery rates consistent with COVAX projections, using an infection-blocking vaccine at $3/dose with 70% efficacy and 2.5 year duration of protection is likely to avert around 0.9 (95% Credible Interval: 0.9, 1.0) million cases, 10.1 (95% CrI: 10.1, 10.3) thousand deaths and 70.1 (95% CrI: 69.9, 70.6) thousand DALYs, with an ICER of $27.9 per DALY averted from the health system perspective. Varying these assumptions, we generally find that prioritizing the older (65+) population prevents more deaths, but broad distribution from the outset is economically comparable in many scenarios, and either scheme can be cost-effective for low per-dose costs. However, high vaccine prices ($10/dose) may not be cost-effective.

The principal drivers of the health outcomes are the fitted values for the overall transmission scaling parameter and disease natural history parameters from other studies, particularly age specific probabilities of infection and symptomatic disease, as well as social contact rates. Other parameters are investigated in sensitivity analyses.

These projections are limited by the mechanisms present in the model. Because the model is a single-population compartmental model, detailed impacts of non-pharmaceutical interventions (NPIs) such as household isolation cannot be practically represented or evaluated in combination with vaccine programmes. Similarly, the model cannot consider prioritizing groups like healthcare or other essential workers. Additionally, because the future impact and implementation cost of NPIs is uncertain, how these would interact with vaccination remains an open question.

ConclusionsCOVID-19 vaccination can have a considerable health impact, and is likely to be cost-effective if more optimistic vaccine scenarios apply. Preventing severe disease is an important contributor to this impact, but the advantage of focusing initially on older, high-risk populations may be smaller in generally younger populations where many people have already been infected, typical of many low- and -middle income countries, as long as vaccination gives good protection against infection as well as disease.

Author SummaryO_ST_ABSWhy Was This Study Done?C_ST_ABS- The evidence base for health and economic impact of COVID-19 vaccination in low- and middle-income settings is limited.
- Searching PubMed, medRxiv, and econLit using the search term ("coronavirus" OR "covid" OR "ncov") AND ("vaccination" OR "immunisation") AND ("model" OR "cost" OR "economic") for full text articles published in any language between 1 January 2020 and 20 January 2021, returned 29 (PubMed), 1,167 (medRxiv) and 0 (econLit) studies: 20 overall were relevant, with only 4 exclusively focused on low- or middle-income countries (India, China, Mexico), while 3 multi-country analyses also included low- or middle-income settings,
- However only three of these studies are considered economic outcomes, all of them comparing the costs of vaccination to the costs of non-pharmaceutical interventions and concluding that both are necessary to reduce infections and maximise economic benefit.
- The majority of studies are set in high-income settings and conclude that targeting COVID-19 vaccination to older age groups is the preferred strategy to minimise mortality, particularly when vaccine supplies are constrained, while other age- or occupational risk groups should be priorities when vaccine availability increases or when other policy objectives are pursued.


What Did the Researchers Do and Find?- We combined epidemiological and economic analysis of COVID-19 vaccination based on real-world disease and programmatic information in the Sindh province of Pakistan.
- We found vaccination in this setting is likely to be highly cost-effective, and even cost saving, as long as the vaccine is reasonably priced and efficacy is high.
- Unlike studies in high-income settings, we also found that vaccination programmes targeting all adults may have almost as much benefit as those initially targeted at older populations, likely reflecting the higher previous infection rates and different demography in these settings.


What Do These Findings Mean?- Lower- and middle-income countries (LMICs) and international bodies providing guidance for LMICs need to consider evidence specific to these settings when making recommendations about COVID-19 vaccination.
- Further data and model-based analyses in such settings are urgently needed in order to ensure that vaccination decisions are appropriate to these contexts. "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

MethodsA realist-informed qualitative study was conducted with unattached patients in Nova Scotia, Canada. Semi-structured interviews with nine participants were conducted and transcribed for analysis. The framework method was used to carry out analysis, which was guided by Donabedians model of assessing healthcare access and quality.

ResultsFive key findings were noted in this study: 1) Participants experienced a range of consequences from not having a regular PHC provider. Participants used creative strategies to 2) attempt to gain attachment to a regular PHC provider, and, to 3) address their health needs in the absence of a regular PHC provider. 4) Participants experienced negative feelings about themselves and the healthcare system, and 5) stress related to the consequences and added work of being unattached and lost care.

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need.