title: Antithrombotic Therapy in COVID-19: Systematic Summary of Ongoing or Completed Randomized Trials

abstract: Endothelial injury and microvascular/macrovascular thrombosis are common pathophysiologic features of coronavirus disease-2019 (COVID-19). However, the optimal thromboprophylactic regimens remain unknown across the spectrum of illness severity of COVID-19. A variety of antithrombotic agents, doses and durations of therapy are being assessed in ongoing randomized controlled trials (RCTs) that focus on outpatients, hospitalized patients in medical wards, and critically-ill patients with COVID-19. This manuscript provides a perspective of the ongoing or completed RCTs related to antithrombotic strategies used in COVID-19, the opportunities and challenges for the clinical trial enterprise, and areas of existing knowledge, as well as data gaps that may motivate the design of future RCTs.


title: Angiotensin converting enzyme inhibitors and risk of lung cancer: a population-based cohort study

abstract:
ObjectivesTo determine whether the use of angiotensin converting enzyme inhibitors (ACEIs) was associated with a higher risk of lung cancer when compared to use of angiotensin receptor blockers (ARBs).

Study DesignPopulation-based cohort study.

SettingPublic hospitals under the Hospital Authority in Hong Kong, P.R. China.

MethodsPatients admitted to public hospitals and first prescribed with ACEI and/or ARB between 1 January 2001 and 31 December 2018 were analyzed. The last follow-up date was 31 August 2020, or death, whichever was earlier.

OutcomesThe primary outcome was the incidence of lung cancer. Logistic regression was used to calculate odds ratio [ORs] with 95% confidence intervals associated with the use of ACEIs compared to ARBs. Incidence and odds ratios were estimated for temporal analysis of incident cancer risk associated with time since the first prescription of ACEI or ARB.

ResultsIn the unmatched cohort, 56,697 patients and 357,011 patients were included the ARB and ACEI cohorts, with lung cancer incidence of 2.16% and 1.29%, respectively. Using 1:3 matching for ARB to ACEI users, the incidences were 2.32% and 1.29%. ACEI use was associated with increased risks of lung cancer both before (hazard ratio: 1.30 [1.21-1.40], P<0.0001) and after (1.40 [1.29-1.51], P<0.0001) matching. There was a dose-dependent relationship between ACEI exposure and lung cancer risk.

ConclusionsACEI use was associated with increased risk of lung cancer compared with ARB use at all time points. Additionally, incidence risk increases with the duration of exposure.

category: cardiovascular medicine


title: Dopamine transporter in obesity: a meta-analysis

abstract: The brain plays a major role in controlling the desire to eat. This meta-analysis aimed to assess the association between dopamine transporter (DAT) availability, and obesity. We performed a systematic search of MEDLINE (from inception to November 2020) and EMBASE (from inception to November 2020) for articles published in English using the keywords "dopamine transporter," "obesity," and "neuroimaging". Data were plotted for each radiopharmaceutical, and linear regression was used to describe the relationship between DAT ratio, and body mass index (BMI), spline curves were adopted to fit data between DAT ratio and BMI. Five studies including 421 subjects were eligible for inclusion in this study. Two studies with 123I-FP-CIT, one with 99mTc-TRODAT, one with 123I-PE21, and one with 18F-FP-CIT were included. DAT availabilities from ENC-DAT project were higher than those from PPMI database both for caudate nucleus, and putamen. As there might be the inter-study variability, we calculated DAT ratio, after dividing DAT availabilities of subjects with overweight/obese BMI with mean DAT availabilities of subjects with normal BMI. In conclusion, we have shown that DAT availability of subjects with overweight/obesity was not different from those with normal BMI.

category: endocrinology


title: Analysis of 200,000 exome-sequenced UK Biobank subjects illustrates the contribution of rare genetic variants to hyperlipidaemia

abstract: A few genes have previously been identified in which very rare variants can have major effects on lipid levels. Weighted burden analysis of rare variants was applied to exome sequenced UK Biobank subjects with hyperlipidaemia as the phenotype, of whom 44,050 were designated cases and 156,578 controls, with the strength of association characterised by the signed log 10 p value (SLP). With principal components included as covariates there was a tendency for genes on the X chromosome to produce strongly negative SLPs, and this was found to be due to the fact that rare X chromosome variants were identified less frequently in males than females. The test performed well when both principal components and sex were included as covariates and strongly implicated LDLR (SLP = 50.08) and PCSK9 (SLP = -10.42) while also highlighting other genes previously found to be associated with lipid levels. Variants classified by SIFT as deleterious have on average a two-fold effect and their cumulative frequency is such that they are present in approximately 1.5% of the population. These analyses shed further light on the way that genetic variation contributes to risk of hyperlipidaemia and in particular that there are very many protein-altering variants which have on average moderate effects and whose effects can be detected when large samples of exome-sequenced subjects are available. This research has been conducted using the UK Biobank Resource.


title: A novel computational approach to reconstruct SARS-CoV-2 infection dynamics through the inference of unsampled sources of infection

abstract: Infectious diseases such as the COVID19 pandemic cemented the importance of disease tracking. The role of asymptomatic, undiagnosed individuals in driving infection has become evident. Their unaccountability results in ineffective prevention. We developed a pipeline using genomic data to accurately predict a populations transmission network complete with the inference of unsampled sources. The system utilises Bayesian phylogenetics to capture evolutionary and infection dynamics of SARS-CoV-2. It identified the effectiveness of preventive measures in Canadas Atlantic bubble and mobile populations such as New York State. Its robustness extends to the prediction of cross-species disease transmission as we inferred SARS-CoV-2 transmission from humans to lions and tigers in New York Citys Bronx Zoo. The proposed methods ability to generate such complete transmission networks, provides a more detailed insight into the transmission dynamics within a population. This potential frontline tool will be of direct help in "the battle to bend the curve".

category: epidemiology


title: Stochastic model for COVID-19 in slums: interaction between biology and public policies

abstract: We present a mathematical model for the simulation of the development of an outbreak of COVID-19 in a slum area under different interventions. Instead of representing interventions as modulations of the parameters of a free running epidemic we introduce a model structure that accounts for the actions but does not assume the results. The disease is modelled in terms of the progression of viremia reported in scientific works. The emergence of symptoms in the model reflects the statistics of a nation-wide highly detailed database consisting of more than 62000 cases (about a half of the confirmed by RT-PCR tests) with recorded symptoms in Argentina. The stochastic model displays several of the characteristics of COVID-19 such as a high variability in the evolution of the outbreaks, including long periods in which they run undetected, spontaneous extinction followed by a late outbreak and unimodal as well as bimodal progressions of daily counts of cases (second waves without ad-hoc hypothesis). We show how the relation between undetected cases (including the "asymptomatic" cases) and detected cases changes as a function of the public policies, the efficiency of the implementation and the timing with respect to the development of the outbreak. We show also that the relation between detected cases and total cases strongly depends on the implemented policies and that detected cases cannot be regarded as a measure of the outbreak, being the dependency between total cases and detected cases in general not monotonic as a function of the efficiency in the intervention method. According to the model, it is possible to control an outbreak with interventions based on the detection of symptoms only in the case when the presence of just one symptom prompts isolation and the detection efficiency reaches about 80% of the cases. Requesting two symptoms to trigger intervention can be enough to fail in the goals.


title: Representative Estimates of COVID-19 Infection Fatality Rates from Three Locations in India

abstract: There are very few estimates of the age-specific infection fatality rate (IFR) of SARS-CoV-2 in low- and middle-income countries. India reports the second highest number of SARS-CoV-2 infections in the world. We estimate age-specific IFR using data from seroprevalence surveys in Mumbai (population 12 million) and Karnataka (population 61 million), and a random sample of economically distressed migrants in Bihar with mortality followup. Among men aged 50-89, IFR is 0.12% in Karnataka (95% C.I. 0.09%-0.15%), 0.53% in Mumbai (0.52%-0.54%), and 5.64% among migrants in Bihar (0-11.16%). IFR in India is approximately twice as high for men as for women, is heterogeneous across contexts, and rises much less at older ages than in comparable studies from high income countries.


title: Potential Blood Transfusion Adverse Events Can be Found in Unstructured Text in Electronic Health Records using the 'Shakespeare Method'

abstract:
BackgroundText in electronic health records (EHRs) and big data tools offer the opportunity for surveillance of adverse events (patient harm associated with medical care) (AEs) in the unstructured notes. Writers may explicitly state an apparent association between treatment and adverse outcome ("attributed") or state the simple treatment and outcome without an association ("unattributed"). We chose the case of transfusion adverse events (TAEs) and potential TAEs (PTAEs) because real dates were obscured in the study data, and new TAE types were becoming recognized during the study data period.

ObjectiveDevelop a new method to identify attributed and unattributed potential adverse events using the unstructured text of EHRs.

MethodsWe used EHRs for adult critical care admissions at a major teaching hospital, 2001-2012. We formed a transfusion (T) group (21,443 admissions treated with packed red blood cells, platelets, or plasma), excluded 2,373 ambiguous admissions, and formed a comparison (C) group of 25,468 admissions. We concatenated the text notes for each admission, sorted by date, into one document, and deleted replicate sentences and lists. We identified statistically significant words in T vs. C. T documents were filtered to those words, followed by topic modeling on the T filtered documents to produce 45 topics.

For each topic, the three documents with the maximum topic scores were manually reviewed to identify events that occurred shortly after the first transfusion; documents with clear alternative explanations for heart, lung, and volume overload problems (e.g., advanced cancer, lung infection) were excluded. We also reviewed documents with the most topics, as well as 20 randomly selected T documents without alternate explanations.

ResultsTopics centered around medical conditions. The average number of significant topics was 6.1. Most PTAEs were not attributed to transfusion in the notes.

Admissions with a top-scoring cardiovascular topic (heart valve repair, tapped pericardial effusion, coronary artery bypass graft, heart attack, or vascular repair) were more likely than random T admissions to have at least one heart PTAE (heart rhythm changes or hypotension, proportion difference = 0.47, p = 0.022). Admissions with a top-scoring pulmonary topic (mechanical ventilation, acute respiratory distress syndrome, inhaled nitric oxide) were more likely than random T admissions (proportion difference = 0.37, p = 0.049) to have at least one lung PTAE (hypoxia, mechanical ventilation, bilateral pulmonary effusion, or pulmonary edema).

ConclusionsThe "Shakespeare Method" could be a useful supplement to AE reporting and surveillance of structured EHR data. Future improvements should include automation of the manual review process.


title: Prevalence of RT-PCR-detected SARS-CoV-2 infection at schools: First results from the Austrian School-SARS-CoV-2 Study

abstract:
BackgroundThe role of schools in the SARS-CoV-2 pandemic is much debated. We aimed to quantify reliably the prevalence of SARS-CoV-2 infections at schools detected with reverse-transcription quantitative polymerase-chain-reaction (RT-qPCR).

MethodsThis nationwide prospective cohort study monitors a representative sample of pupils (grade 1-8) and teachers at Austrian schools throughout the school year 2020/2021. We repeatedly test participants for SARS-CoV-2 infection using a gargling solution and RT-qPCR. We herein report on the first two rounds of examinations. We used mixed-effect logistic regression to estimate odds ratios and robust 95% confidence intervals (95% CI).

FindingsWe analysed data on 10734 participants from 245 schools (9465 pupils, 1269 teachers). Prevalence of SARS-CoV-2 infection increased from 0.39% at round 1 (95% CI 0.28-0{middle dot}55%, 29 September-22 October 2020) to 1{middle dot}39% at round 2 (95% CI 1{middle dot}04-1{middle dot}85%, 10-16 November). Odds ratios for SARS-CoV-2 infection were 2{middle dot}26 (95% CI 1{middle dot}25-4{middle dot}12, P=0{middle dot}007) in regions with >500 vs. [≤]500 inhabitants/km2, 1{middle dot}67 (95% CI 1{middle dot}42-1{middle dot}97, P<0{middle dot}001) per two-fold higher regional 7-day incidence, and 2{middle dot}78 (95% CI 1{middle dot}73-4{middle dot}48, P<0{middle dot}001) in pupils at schools with high/very high vs. low/moderate social deprivation. Associations of community incidence and social deprivation persisted in a multivariable adjusted model. Prevalence did not differ by average number of pupils per class nor between age groups, sexes, pupils vs. teachers, or primary (grade 1-4) vs. secondary schools (grade 5-8).

InterpretationThis monitoring study in Austrian schools revealed SARS-CoV-2 infection in 0{middle dot}39%-1{middle dot}39% of participants and identified associations of regional community incidence and social deprivation with higher prevalence.

FundingBMBWF Austria.


title: Prevalence of RT-qPCR-detected SARS-CoV-2 infection at schools: First results from the Austrian School-SARS-CoV-2 prospective cohort study


title: Viral Variants and Vaccinations: If We Can Change the COVID-19 Vaccine, Should We?

abstract: As we close in on one year since the COVID-19 pandemic began, hope has been placed on bringing the virus under control through mass administration of recently developed vaccines. Unfortunately, newly emerged, fast-spreading strains of COVID-19 threaten to undermine progress by interfering with vaccine efficacy. While a long-term solution to this challenge would be to develop vaccines that simultaneously target multiple different COVID-19 variants, this approach faces both developmental and regulatory hurdles. A simpler option would be to switch the target of the current vaccine to better match the newest viral variant. I use a stochastic simulation to determine when it is better to target a newly emerged viral variant and when it is better to target the dominant but potentially less transmissible strain. My simulation results suggest that it is almost always better to target the faster spreading strain, even when the initial prevalence of this variant is much lower. In scenarios where targeting the slower spreading variant is best, all vaccination strategies perform relatively well, meaning that the choice of vaccination strategy has a small effect on public health outcomes. In scenarios where targeting the faster spreading variant is best, use of vaccines against the faster spreading viral variant can save many lives. My results provide  rule of thumb guidance for those making critical decisions about vaccine formulation over the coming months.


title: Associations between Stress and Child Verbal Abuse and Corporal Punishment during the COVID-19 Pandemic and Potential Effect Modification by Lockdown Measures

abstract:
BackgroundChild abuse appears to be on the increase during the COVID-19 pandemic, but the extent that lockdown measures modified the association between stress and abuses has not been systematically assessed.

ObjectivesTo assess: 1) the association between caregivers stress and self-reported verbal abuse and corporal punishment of a child in the household, and; 2) modification of the stated association by experienced COVID-19 lockdown measures.

Participants and settingsCaregivers residing in villages on lockdown in the Deep South of Thailand (n=466 participants)

MethodsWe randomly sampled 12 villages in the study area, and 40 households per village. Trained enumerators who were residents of the sampled villages collected the data using phone-based interview. We measured stress level using the standard ST-5 questionnaire. We developed and pilot-tested questions for measurement of child abuse and lockdown experiences specifically for this study.

ResultsCaregivers with moderate and higher levels of stress were more likely than caregivers with low level of stress to report verbal abuse (48% vs. 23%, respectively; Adj. OR = 3.12, 95% CI = 1.89, 5.15) and corporal punishment (28% vs. 8%, respectively; Adj. OR = 2.76, 95% CI = 1.41, 5.42). We found that COVID-19 lockdown experiences modified the associations between stress and verbal abuse and corporal punishment.

ConclusionThere were associations between stress and abuses, which were modified by lockdown experiences. However, social desirability, lack of details in the answers, and potential confounding by mental illness co-morbidities were notable limitations of the study. Caveat is advised in the interpretation of the study findings.


title: SARS-CoV-2 seroprevalence in the urban population of Qatar: An analysis of antibody testing on a sample of 112,941 individuals

abstract:
BackgroundQatar has experienced a large SARS-CoV-2 epidemic. Our first objective was to assess the proportion of the urban population that has been infected with SARS-CoV-2, by measuring the prevalence of detectable antibodies. Our second objective was to identify predictors for infection and for having higher antibody titers.

MethodsResidual blood specimens from individuals receiving routine and other clinical care between May 12-September 9, 2020 were tested for anti-SARS-CoV-2 antibodies. Associations with seropositivity and higher antibody titers were identified through regression analyses. Probability weights were applied in deriving the epidemiological measures.

ResultsWe tested 112,941 individuals ([~]10% of Qatars urban population), of whom 51.6% were men and 66.0% were 20-49 years of age. Seropositivity was 13.3% (95% CI: 13.1-13.6%) and was significantly associated with sex, age, nationality, clinical-care type, and testing date. The proportion with higher antibody titers varied by age, nationality, clinical-care type, and testing date. There was a strong correlation between higher antibody titers and seroprevalence in each nationality, with a Pearson correlation coefficient of 0.85 (95% CI: 0.47-0.96), suggesting that higher antibody titers may indicate repeated exposure to the virus. The percentage of antibody-positive persons with prior PCR-confirmed diagnosis was 47.1% (95% CI: 46.1-48.2%), severity rate was 3.9% (95% CI: 3.7-4.2%), criticality rate was 1.3% (95% CI: 1.1-1.4%), and fatality rate was 0.3% (95% CI: 0.2-0.3%).

ConclusionsFewer than two in every 10 individuals in Qatars urban population had detectable antibodies against SARS-CoV-2 between May 12-September 9, 2020, suggesting that this population is still far from the herd immunity threshold and at risk from a subsequent epidemic wave.


title: Machine Learning Forecast of Growth in COVID-19 Confirmed Infection Cases with Non-Pharmaceutical Interventions and Cultural Dimensions: Algorithm Development and Validation

abstract:
BackgroundNational governments have implemented non-pharmaceutical interventions to control and mitigate against the COVID-19 pandemic. A deep understanding of these interventions is required.

ObjectiveWe investigate the prediction of future daily national Confirmed Infection Growths - the percentage change in total cumulative cases across 14 days - using metrics representative of non-pharmaceutical interventions and cultural dimensions of each country.

MethodsWe combine the OxCGRT dataset, Hofstedes cultural dimensions, and COVID-19 daily reported infection case numbers to train and evaluate five non-time series machine learning models in predicting Confirmed Infection Growth. We use three validation methods - in-distribution, out-of-distribution, and country-based cross-validation - for evaluation, each applicable to a different use case of the models.

ResultsOur results demonstrate high R2 values between the labels and predictions for the in-distribution, out-of-distribution, and country-based cross-validation methods (0.959, 0.513, and 0.574 respectively) using random forest and AdaBoost regression. While these models may be used to predict the Confirmed Infection Growth, the differing accuracies obtained from the three tasks suggest a strong influence of the use case.

ConclusionsThis work provides new considerations in using machine learning techniques with non-pharmaceutical interventions and cultural dimensions data for predicting the national growth of confirmed infections of COVID-19.


title: Common Factors in Serious Case Reviews of Child Maltreatment where there is a Medical Cause of Death: Qualitative Thematic Analysis

abstract:
AimTo identify common factors in Serious Case Reviews (SCRs) where a child has died of a medical cause. Design: Qualitative thematic analysis.

BackgroundSCRs take place when neglect or abuse results in children dying or being seriously harmed. Known key factors within SCRs include parental substance misuse, mental health problems, and domestic abuse. To date there has been no investigation of children who die of a medical cause where there are concerns about child maltreatment.

Data sourcesA list of SCRs relating to deaths through medical causes was provided from previous coded studies and accessed from the NSPCC National Case Review Repository. Twenty-three SCRs with a medical cause of death from 1st April 2009-31st March 2017 were sourced.

ResultsTwenty children died of an acute condition and 12 of a chronic condition; 20 of the deaths were unexpected and maltreatment contributed to the deaths of 18 children. Most children were either under one or over 16 at time of death. Many parents were caring for a child with additional vulnerabilities including behavioural issues (6/23), learning difficulties (6/23), mental health issues (5/23) or a chronic medical condition (12/23). Common parental experiences included: domestic violence/abuse (13/23), drug/alcohol misuse (10/23), mental ill health or struggling to cope (7/23), criminal history (11/23), and caring for another vulnerable individual (8/23). Most children lived in a chaotic household characterised by missed medical appointments (18/23), poor school attendance (11/23), poor physical home environment (7/23) and disguised compliance (12/23). All 23 SCRs reported elements of abusive or neglectful parenting. In most there was evidence of cumulative harm, where multiple factors contributed to their premature death. At the time of death 11 children were receiving social care support.

ConclusionWhile the underlying medical cause of the childs death was often incurable, the maltreatment that often exacerbated the medical issue could have been prevented.

Article Summary. Strengths and weaknesses of the studyO_LINo other study has analysed SCRs in which children have died of medical causes.
C_LIO_LIThe most complete dataset possible was used to conduct the robust analysis: SCRs were sourced from the complete list from the Department for Education used for previous national analyses of SCRs.
C_LIO_LIRandomly selected SCRs were re-coded by two further researchers to check for any discrepancies in coding, increasing the reliability of results.
C_LIO_LINot all child deaths lead to SCR, even when there are concerns about maltreatment; local areas may differ on their threshold of suspicion; content within SCRs is often variable and inconsistent; so there may be deaths relevant to this study which were not included.
C_LIO_LIWe only investigated those cases in which a child died, focusing therefore on the worst cases and perhaps missing incidents in which a child had a medical condition and experienced maltreatment but did not die.
C_LI

category: pediatrics


title: Assessment of Pharmacokinetic Interaction Potential Between Caffeine and Methylliberine

abstract: Methylliberine and theacrine are methylurates found in the leaves of various Coffea species and Camellia assamica var. kucha, respectively. We previously demonstrated that the methylxanthine caffeine increased theacrines oral bioavailability in humans. Consequently, we conducted a double-blind, placebo-controlled study pharmacokinetic study in humans administered methylliberine, theacrine, and caffeine to determine methylliberines pharmacokinetic interaction potential with either caffeine or theacrine. Subjects (n = 12) received an oral dose of either methylliberine (25 or 100 mg), caffeine (150 mg), methylliberine (100 mg) plus caffeine (150 mg), or methylliberine (100 mg) plus theacrine (50 mg) using a randomized, double-blind, crossover design. Blood samples were collected over 24 hours and analyzed for methylliberine, theacrine, and caffeine using UPLC-MS/MS. Methylliberine exhibited linear pharmacokinetics that were unaffected by co-administration of either caffeine or theacrine. However, methylliberine co-administration resulted in decreased oral clearance (41.9 {+/-} 19.5 vs. 17.1 {+/-} 7.80 L/hr) and increased half-life (7.2 {+/-} 5.6 versus 15 {+/-} 5.8 hrs) of caffeine. Methylliberine had no impact on caffeines maximum concentration (440 {+/-} 140 vs. 458 {+/-} 93.5 ng/mL) or oral volume of distribution (351 {+/-} 148 vs. 316 {+/-} 76.4 L). We previously demonstrated theacrine bioavailability was enhanced by caffeine, however, caffeine pharmacokinetics were unaffected by theacrine. Herein, we found that methylliberine altered caffeine pharmacokinetics without a reciprocal interaction, which suggests caffeine may interact uniquely with different methylurates. Understanding the mechanism(s) of interaction between methylxanthines and methylurates is of critical importance in light of the recent advent of dietary supplements containing both purine alkaloid classes.

category: pharmacology and therapeutics


title: Caffeine and Methylliberine: A Human Pharmacokinetic Interaction Study


title: Genomic epidemiology of the SARS-CoV-2 epidemic in Zimbabwe: Role of international travel and regional migration in spread

abstract: Zimbabwe reported its first case of SARS-Cov-2 infection in March 2020, and case numbers increased to more than 8,099 to 16th October 2020. An understanding of the SARS-Cov-2 outbreak in Zimbabwe will assist in the implementation of effective public health interventions to control transmission. Nasopharyngeal samples from 92,299 suspected and confirmed COVID-19 cases reported in Zimbabwe between 20 March and 16 October 2020 were obtained. Available demographic data associated with those cases identified as positive (8,099) were analysed to describe the national breakdown of positive cases over time in more detail (geographical location, sex, age and travel history). The whole genome sequence (WGS) of one hundred SARS-CoV-2-positive samples from the first 120 days of the epidemic in Zimbabwe was determined to identify their relationship to one another and WGS from global samples. Overall, a greater proportion of infections were in males (55.5%) than females (44.85%), although in older age groups more females were affected than males. Most COVID-19 cases (57 %) were in the 20-40 age group. Eight lineages, from at least 25 separate introductions into the region were found using comparative genomics. Of these, 95% had the D614G mutation on the spike protein which was associated with higher transmissibility than the ancestral strain. Early introductions and spread of SARS-CoV-2 were predominantly associated with genomes common in Europe and the United States of America (USA), and few common in Asia at this time. As the pandemic evolved, travel-associated cases from South Africa and other neighbouring countries were also recorded. Transmission within quarantine centres occurred when travelling nationals returning to Zimbabwe. International and regional migration followed by local transmission were identified as accounting for the development of the SARS-CoV-2 epidemic in Zimbabwe. Based on this, rapid implementation of public health interventions are critical to reduce local transmission of SARS-CoV-2. Impact of the predominant G614 strain on severity of symptoms in COVID-19 cases needs further investigation.

category: public and global health


title: A novel age-informed approach for genetic association analysis in Alzheimer's disease

abstract:
IntroductionMany Alzheimers disease (AD) genetic association studies disregard age or incorrectly account for it, hampering variant discovery.

MethodUsing simulated data, we compared the statistical power of several models: logistic regression on AD diagnosis adjusted and not adjusted for age; linear regression on a score integrating case-control status and age; and multivariate Cox regression on age-at-onset. We applied these models to real exome-wide data of 11,127 sequenced individuals (54% cases) and replicated suggestive associations in 21,631 genotype-imputed individuals (51% cases).

ResultsModelling variable AD risk across age results in 10-20% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads to critical power loss. Applying our novel AD-age score and/or Cox regression, we discovered and replicated novel variants associated with AD on KIF21B, USH2A, RAB10, RIN3 and TAOK2 genes.

DiscussionOur AD-age score provides a simple means for statistical power gain and is recommended for future AD studies.

category: neurology


title: In Vivo Assessment of the Safety of Standard Fractionation Temporally Feathered Radiation Therapy (TFRT) for Head and Neck Squamous Cell Carcinoma: An R-IDEAL Stage 1/2a First-in- Humans/Feasibility Demonstration of New Technology Implementation

abstract:
IntroductionPrior in silico simulations of studies of Temporally Feathered Radiation Therapy (TFRT) have demonstrated potential reduction in normal tissue toxicity. This R-IDEAL Stage 1/2A study seeks to demonstrate the first-in-human implementation of TFRT in treating patients with head and neck squamous cell carcinoma (HNSCC).

Materials and MethodsPatients with HNSCC treated with definitive radiation therapy were eligible (70 Gy in 35 fractions) were eligible. The primary endpoint was feasibility of TFRT planning as defined by radiation start within 15 days of CT simulation. Secondary endpoints included estimates of acute grade 3-5 toxicity.

ResultsThe study met its accrual goal of 5 patients. TFRT plans were generated in four of the five patients within 15 business days of CT simulation, therefore meeting the primary endpoint. One patient was not treated with TFRT at physicians discretion, though the TFRT plan had been generated within sufficient time from the CT simulation. For patients who received TFRT, the median time from CT simulation to radiation start was 10 business days (range 8-15). The average time required for radiation planning was 6 days. In all patients receiving TFRT, each subplan and every daily fraction was delivered in the correct sequence without error. The OARs feathered included: oral cavity, each submandibular gland, each parotid gland, supraglottis, and posterior pharyngeal wall (OAR pharynx). Prescription dose PTV coverage (>95%) was ensured in each TFRT subplan and the composite TFRT plan. One of five patients developed an acute grade 3 toxicity.

ConclusionsThis study demonstrates the first-in-human implementation of TFRT (R-IDEAL Stage 1), proving its feasibility in the modern clinical workflow. Additionally, assessments of acute toxicities and dosimetric comparisons to a standard radiotherapy plan were described (R-IDEAL Stage 2a).

HighlightsO_LIThis prospective study is the first-in-human application for Temporally Feathered Radiation Therapy (TFRT).
C_LIO_LIIn theory, TFRT may reduce radiation-induced toxicities by optimizing the time through which radiation is delivered and consequently improve normal tissue recovery.
C_LIO_LIIn this study, patients with head and neck squamous cell carcinoma were treated with TFRT.
C_LIO_LIThe primary endpoint of technical feasibility was met when patients were successfully treated with TFRT techniques without introducing delays in radiation commencement.
C_LI

category: oncology


title: Twitter Discourse on Nicotine as Potential Prophylactic or Therapeutic for COVID-19

abstract:
BackgroundAn unproven "nicotine hypothesis" that indicates nicotines therapeutic potential for COVID-19 has been proposed in recent literature. This study is about Twitter posts that misinterpret this hypothesis to make baseless claims about benefits of smoking and vaping in the context of COVID-19. We quantify the presence of such misinformation and characterize the tweeters who post such messages.

MethodsTwitter premium API was used to download tweets (n = 17,533) that match terms indicating (a) nicotine or vaping themes, (b) a prophylactic or therapeutic effect, and (c) COVID-19 (January-July 2020) as a conjunctive query. A constraint on the length of the span of text containing the terms in the tweets allowed us to focus on those that convey the therapeutic intent. We hand-annotated these filtered tweets and built a classifier that identifies tweets that extrapolate the nicotine hypothesis to smoking/vaping with a positive predictive value of 85%. We analyzed the frequently used terms in author bios, top Web links, and hashtags of such tweets.

Results21% of our filtered COVID-19 tweets indicate a vaping or smoking-based prevention/treatment narrative. Qualitative analyses show a variety of ways therapeutic claims are being made and tweeter bios reveal pre-existing notions of positive stances toward vaping.

ConclusionThe social media landscape is a double-edged sword in tobacco communication. Although it increases information reach, consumers can also be subject to confirmation bias when exposed to inadvertent or deliberate framing of scientific discourse that may border on misinformation. This calls for circumspection and additional planning in countering such narratives as the COVID-19 pandemic continues to ravage our world. Our results also serve as a cautionary tale in how social media can be leveraged to spread misleading information about tobacco products in the wake of pandemics.

category: health informatics


title: Prevalence and Factors associated with Mental health impact of COVID-19 Pandemic in Bangladesh: A survey-based cross-sectional study

abstract:
BackgroundFeelings of isolation, insecurity, and instability triggered by COVID-19 could have a long-term impact on the mental health status of individuals. This study examined the prevalence and factors associated with the mental health symptoms of anxiety, depression, and stress during the COVID-19 pandemic in Bangladesh.

MethodsFrom 1st - 30th April 2020, we used a validated self-administered questionnaire to conduct a cross-sectional study on 10,609 participants through an online survey platform. We assessed mental health status using the Depression, Anxiety, and Stress Scale (DASS-21). The total depression, anxiety, and stress subscale scores were divided into normal, mild, moderate, severe, and multinomial logistic regression was used to examine associated factors.

ResultsThe prevalence of depressive symptoms was 15%, 34%, and 15% for mild, moderate, and severe depressive symptoms, respectively. The prevalence of anxiety symptoms was 59% for severe anxiety symptoms, 14% for moderate anxiety symptoms, and 14% for mild anxiety symptoms while, the prevalence for stress levels were 16% for severe stress level, 22% for moderate stress level and 13% for mild stress level. Multivariate analyses revealed that the most consistent factors associated with mild, moderate, and severe of the three mental health subscales (depression, anxiety, and stress) were respondents who lived in Dhaka and Rangpur division, females, those who self-quarantine in the previous 7 days before the survey and those respondents who experienced chills, breathing difficulty, dizziness, and sore throat.

ConclusionOur results showed that about 64%, 87%, and 61% experienced depressive symptoms, anxiety symptoms, and levels of stress, respectively. In Bangladesh, there is a need for better mental health support for females especially those that lived in Dhaka and Rangpur division and experienced chills, breathing difficulty, dizziness, and sore throat during COVID-19 and other future pandemics.

category: health systems and quality improvement


title: Saliva viral load is a dynamic unifying correlate of COVID-19 severity and mortality

abstract: While several clinical and immunological parameters correlate with disease severity and mortality in SARS-CoV-2 infection, work remains in identifying unifying correlates of coronavirus disease 2019 (COVID-19) that can be used to guide clinical practice. Here, we examine saliva and nasopharyngeal (NP) viral load over time and correlate them with patient demographics, and cellular and immune profiling. We found that saliva viral load was significantly higher in those with COVID-19 risk factors; that it correlated with increasing levels of disease severity and showed a superior ability over nasopharyngeal viral load as a predictor of mortality over time (AUC=0.90). A comprehensive analysis of immune factors and cell subsets revealed strong predictors of high and low saliva viral load, which were associated with increased disease severity or better overall outcomes, respectively. Saliva viral load was positively associated with many known COVID-19 inflammatory markers such as IL-6, IL-18, IL-10, and CXCL10, as well as type 1 immune response cytokines. Higher saliva viral loads strongly correlated with the progressive depletion of platelets, lymphocytes, and effector T cell subsets including circulating follicular CD4 T cells (cTfh). Anti-spike (S) and anti-receptor binding domain (RBD) IgG levels were negatively correlated with saliva viral load showing a strong temporal association that could help distinguish severity and mortality in COVID-19. Finally, patients with fatal COVID-19 exhibited higher viral loads, which correlated with the depletion of cTfh cells, and lower production of anti-RBD and anti-S IgG levels. Together these results demonstrated that viral load - as measured by saliva but not nasopharyngeal -- is a dynamic unifying correlate of disease presentation, severity, and mortality over time.

category: infectious diseases


title: Long term impact on lung function of patients with moderate and severe COVID-19. A prospective cohort study

abstract:
IntroductionA significant number of patients continue to recover from COVID-19; however, little is known about the lung function capacity among survivors. We aim to determine the long-term impact on lung function capacity in patients who have survived moderate or severe COVID-19 disease in a resource-poor setting.

Methods and analysisThis prospective cohort study will include patients aged 15 years and above and have reverse transcriptase-polymerase chain reaction (RT-PCR) positive for COVID 19 (nasopharyngeal or oropharyngeal). Patients with a pre-existing diagnosis of obstructive or interstitial lung disease, lung fibrosis and cancers, connective tissue disorders, autoimmune conditions affecting the lungs, underlying heart disease, history of syncope and refuse to participate will be excluded. Pulmonary function will be assessed using spirometry and diffusion lung capacity for carbon monoxide (DLCO) at three- and six-months interval. A chest X-ray at three and six-month follow-up and CT-chest will be performed if clinically indicated after consultation with the study pulmonologist or Infectious Disease (ID) physician. Echocardiogram (ECHO) to look for pulmonary hypertension at the three months visit and repeated at six months if any abnormality is identified initially. Data analysis will be performed using standard statistical software.

Ethics and disseminationThe proposal was reviewed and approved by ethics review committee (ERC) of the institution (ERC reference number 2020-4735-11311). Informed consent will be obtained from each study participant. The results will be disseminated among study participants, institutional, provincial and national level through seminars and presentations. Moreover, the scientific findings will be published in high-impact peer-reviewed medical journals.

Strengths and Limitations of this study- The study has the potential to develop context-specific evidence on the long-term impact on lung function among COVID-19 survivors
- Findings will play key role in understanding the impact of the disease on vital functions and help devise rehabilitative strategies to best overcome the effects of disease
- This is a single-center, study recruiting only a limited number of COVID-19 survivors
- The study participants may loss-to-follow up due to uncertain conditions and disease reemergence


title: THE INTESTINAL AND ORAL MICROBIOMES ARE ROBUST PREDICTORS OF COVID-19 SEVERITY THE MAIN PREDICTOR OF COVID-19-RELATED FATALITY

abstract: The reason for the striking differences in clinical outcomes of SARS-CoV-2 infected patients is still poorly understood. While most recover, a subset of people become critically ill and succumb to the disease. Thus, identification of biomarkers that can predict the clinical outcomes of COVID-19 disease is key to help prioritize patients needing urgent treatment. Given that an unbalanced gut microbiome is a reflection of poor health, we aim to identify indicator species that could predict COVID-19 disease clinical outcomes. Here, for the first time and with the largest COVID-19 patient cohort reported for microbiome studies, we demonstrated that the intestinal and oral microbiome make-up predicts respectively with 92% and 84% accuracy (Area Under the Curve or AUC) severe COVID-19 respiratory symptoms that lead to death. The accuracy of the microbiome prediction of COVID-19 severity was found to be far superior to that from training similar models using information from comorbidities often adopted to triage patients in the clinic (77% AUC). Additionally, by combining symptoms, comorbidities, and the intestinal microbiota the model reached the highest AUC at 96%. Remarkably the model training on the stool microbiome found enrichment of Enterococcus faecalis, a known pathobiont, as the top predictor of COVID-19 disease severity. Enterococcus faecalis is already easily cultivable in clinical laboratories, as such we urge the medical community to include this bacterium as a robust predictor of COVID-19 severity when assessing risk stratification of patients in the clinic.


title: Fever, Diarrhea, and Severe Disease Correlate with High Persistent Antibody Levels against SARS-CoV-2

abstract: Lasting immunity will be critical for overcoming the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, factors that drive the development of high titers of anti-SARS-CoV-2 antibodies and how long those antibodies persist remain unclear. Our objective was to comprehensively evaluate anti-SARS-CoV-2 antibodies in a clinically diverse COVID-19 convalescent cohort at defined time points to determine if anti-SARS-CoV-2 antibodies persist and to identify clinical and demographic factors that correlate with high titers. Using a novel multiplex assay to quantify IgG against four SARS-CoV-2 antigens, a receptor binding domain-angiotensin converting enzyme 2 inhibition assay, and a SARS-CoV-2 neutralization assay, we found that 98% of COVID-19 convalescent subjects had anti-SARS-CoV-2 antibodies five weeks after symptom resolution (n=113). Further, antibody levels did not decline three months after symptom resolution (n=79). As expected, greater disease severity, older age, male sex, obesity, and higher Charlson Comorbidity Index score correlated with increased anti-SARS-CoV-2 antibody levels. We demonstrated for the first time that COVID-19 symptoms, namely fever, abdominal pain, diarrhea and low appetite, correlated consistently with higher anti-SARS-CoV-2 antibody levels. Our results provide new insights into the development and persistence of anti-SARS-CoV-2 antibodies.


title: Impaired performance of SARS-CoV-2 antigen-detecting rapid tests at elevated temperatures

abstract: Rapid antigen-detecting tests (Ag-RDTs) can complement molecular diagnostics for COVID-19. The recommended temperature for storage of SARS-CoV-2 Ag-RDTs ranges between 5-30{degrees}C. In many countries that would benefit from SARS-CoV-2 Ag-RDTs, mean temperatures exceed 30{degrees}C. We assessed analytical sensitivity and specificity of eleven commercially available SARS-CoV-2 Ag-RDTs using different storage and operational temperatures, including (i) long-term storage and testing at recommended conditions, (ii) recommended storage conditions followed by 10 minutes exposure to 37{degrees}C and testing at 37{degrees}C and (iii) 3 weeks storage followed by testing at 37{degrees}C. The limits of detection of SARS-CoV-2 Ag-RDTs under recommended conditions ranged from 8.2x105-7.9x107 genome copies/ml of infectious SARS-CoV-2 cell culture supernatant. Despite long-term storage at recommended conditions, 10 minutes pre-incubation of Ag-RDTs and testing at 37{degrees}C resulted in about ten-fold reduced sensitivity for 46% of SARS-CoV-2 Ag-RDTs, including both Ag-RDTs currently listed for emergency use by the World Health Organization. After 3 weeks of storage at 37{degrees}C, 73% of SARS-CoV-2 Ag-RDTs exhibited about ten-fold reduced sensitivity. Specificity of SARS-CoV-2 Ag-RDTs using cell culture-derived human coronaviruses HCoV-229E and HCoV-OC43 was not affected by storage and testing at 37{degrees}C. In summary, short- and long-term exposure to elevated temperatures likely impairs sensitivity of several SARS-CoV-2 Ag-RDTs that may translate to false-negative test results at clinically relevant virus concentrations compatible with inter-individual transmission. Ensuring appropriate transport and storage conditions, and development of tests that are more robust across temperature fluctuations will be important for accurate use of SARS-CoV-2 Ag-RDTs in tropical settings.


title: Modelling Decay of Population Immunity With Proposed Second Dose Deferral Strategy

abstract: A second dose deferred strategy has been proposed to increase initial population immunity as an alternative to the default two dose vaccine regimen with spacing of 21 or 28 days between vaccine doses for the mRNA vaccines from Pfizer and Moderna. This increased initial population immunity is only of value if one dose immunity does not decay so fast as to nullify the benefit. Because decay rates of one dose and two dose efficacy are currently unknown, a model to project population immunity between the two strategies was created. By evaluating the decay rate of one dose efficacy, two dose efficacy, and time until the second dose is given, the model shows that if there is an increased decay rate of one dose efficacy relative to the two dose decay rate, it is highly unlikely to nullify the benefit of increased population immunity seen in a second dose deferral strategy. Rather, all reasonable scenarios strongly favour a second dose deferral strategy with much higher projected population immunity in comparison to the default regimen.

category: allergy and immunology


title: Burden is in the eye of the beholder: Sensitivity of yellow fever disease burden estimates to modeling assumptions

abstract: Geographically stratified estimates of disease burden play an important role in setting priorities for the management of different diseases and for targeting interventions against a single disease. Such estimates involve numerous assumptions, which uncertainty about is not always well accounted for. We developed a framework for estimating the burden of yellow fever in Africa and evaluated its sensitivity to assumptions about the interpretation of serological data and choice of regression model. We addressed the latter with an ensemble approach, and we found that the former resulted in a nearly twentyfold difference in burden estimates (range of central estimates: 8.4x104-1.5x106 deaths in 2021-2030). Even so, statistical uncertainty made even greater contributions to variance in burden estimates (87%). Combined with estimates that most infections go unreported (range of 95% credible intervals: 99.65-99.99%), our results suggest that yellow fevers burden will remain highly uncertain without major improvements in surveillance.


title: Combining machine learning and mathematical models of disease dynamics to guide development of novel disease interventions

abstract:
BackgroundSubstantial research is underway to develop next-generation interventions that address current malaria control challenges. As there is limited testing in their early development, it is difficult to predefine intervention properties such as efficacy that achieve target health goals, and therefore challenging to prioritize selection of novel candidate interventions. Here, we present a quantitative approach to guide intervention development using mathematical models of malaria dynamics coupled with machine learning. Our analysis identifies requirements of efficacy, coverage, and duration of effect for five novel malaria interventions to achieve targeted reductions in malaria prevalence. This study highlights the role of mathematical models to support intervention development.

MethodsA mathematical model of malaria transmission dynamics is used to simulate deployment and predict potential impact of new malaria interventions by considering operational, health-system, population, and disease characteristics. Our method relies on consultation with product development stakeholders to define the putative space of novel intervention specifications. We couple the disease model with machine learning to search this multi-dimensional space and efficiently identify optimal intervention properties that achieve specified health goals. We demonstrate the power of our approach by application to five malaria interventions in development.

ResultsAiming for malaria prevalence reduction, we identify and quantify key determinants of intervention impact along with their minimal properties required to achieve the desired health goals. While coverage is generally identified as the largest driver of impact, higher efficacy, longer protection duration or multiple deployments per year are needed to increase prevalence reduction. We show that the efficacy and duration needs depend on the biological action of the interventions. Interventions on multiple parasite or vector targets, as well as combinations the new interventions with drug treatment, lead to significant burden reductions and lower efficacy or duration requirements.

ConclusionsOur approach uses disease dynamic models and machine learning to support decision-making and resource investment, facilitating development of new malaria interventions. By evaluating the intervention capabilities in relation to the targeted health goal, our analysis allows prioritization of interventions and of their specifications from an early stage in development, and subsequent investments to be channeled cost-effectively towards impact maximization. Although we focus on five malaria interventions, the analysis is generalizable to other new malaria interventions.


title: Combining machine learning and mathematical models of disease dynamics to guide development of novel malaria interventions


title: Leveraging mathematical models of disease dynamics and machine learning to improve development of novel malaria interventions


title: Acceptability and efficacy of vaginal self-sampling for genital infection and bacterial vaginosis: A large, cross-sectional, non-inferiority trial

abstract:
ObjectiveScreening for genital infection (GI), bacterial vaginosis (BV), sexually transmitted infection (STI) and asymptomatic carriage of group B streptococcus (GBS) in pregnant women is a common reason for medical appointments. Objectives were first to determine the non-inferiority of vaginal self-sampling compared with vaginal/cervical classical sampling to screen for GIs, bacterial vaginosis (BV), STIs, and GBS asymptomatic carriage in pregnant women; second to determine the feasibility of vaginal self-sampling.

MethodsVaginal self-sampling (VSS) and vaginal/cervical classical sampling (VCS) of 1027 women were collected by health care professionals and simultaneously carried out on each patient. Bacterial infection, yeast infection, Chlamydia trachomatis, Neisseria gonorrhoea, Mycoplasma genitalium, Trichomonas vaginalis and Herpes simplex virus types were systematically screened in both paired VSS and VCS samples.

ResultsStatistical tests supported the non-inferiority of VSS compared with VCS. Agreements between VCS and VSS remained high regardless of the type of studied infection. VSS had successful diagnostic performances, especially for Predictive negative value (PNV) (over 90%) for all studied infections. Most participants (84%) recommended the use of VSS.

ConclusionsThis study remains the most exhaustive in screening for GI, BV, STI agents and asymptomatic GBS carriage. Given its efficacy and acceptability, VSS seems to be a viable alternative to classic physician sampling among women in the general population. This study provides evidence that vaginal self-sampling can be used as a universal specimen for detection of lower genital tract infections in women.

Study Identification numberID-RCB 2014-A01250-4


title: Thinner cortex is associated with psychosis onset in individuals at Clinical High Risk for Developing Psychosis: An ENIGMA Working Group mega-analysis

abstract:
ImportanceThe ENIGMA clinical high risk for psychosis (CHR) initiative, the largest pooled CHR-neuroimaging sample to date, aims to discover robust neurobiological markers of psychosis risk in a sample with known heterogeneous outcomes.

ObjectiveWe investigated baseline structural neuroimaging differences between CHR subjects and healthy controls (HC), and between CHR participants who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). We assessed associations with age by group and conversion status, and similarities between the patterns of effect size maps for psychosis conversion and those found in other large-scale psychosis studies.

Design, Setting, and ParticipantsBaseline T1-weighted MRI data were pooled from 31 international sites participating in the ENIGMA CHR Working Group. MRI scans were processed using harmonized protocols and analyzed within a mega- and meta-analysis framework from January-October 2020.

Main Outcome(s) and Measure(s)Measures of regional cortical thickness (CT), surface area (SA), and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR, HC) and conversion status (CHR-PS+, CHR-PS-, HC).

ResultsThe final dataset consisted of 3,169 participants (CHR=1,792, HC=1,377, age range: 9.5 to 39.8 years, 45% female). Using longitudinal clinical information, we identified CHR-PS+ (N=253) and CHR-PS- (N=1,234). CHR exhibited widespread thinner cortex compared to HC (average d=-0.125, range: -0.09 to -0.17), but not SA or subcortical volume. Thinner cortex in the fusiform, superior temporal, and paracentral regions was associated with psychosis conversion (average d=-0.22). Age showed a stronger negative association with left fusiform and left paracentral CT in HC, compared to CHR-PS+. Regional CT psychosis conversion effect sizes resembled patterns of CT alterations observed in other ENIGMA studies of psychosis.

Conclusions and RelevanceWe provide evidence for widespread subtle CT reductions in CHR. The pattern of regions displaying greater CT alterations in CHR-PS+ were similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread CT disruptions coupled with abnormal age associations in CHR may point to disruptions in postnatal brain developmental processes.

Key PointsO_ST_ABSQuestionC_ST_ABSHow do baseline brain morphometric features relate to later psychosis conversion in individuals at clinical high risk (CHR)?

FindingsIn the largest coordinated international analysis to date, reduced baseline cortical thickness, but not cortical surface area or subcortical volume, was more pronounced in CHR, in a manner highly consistent with thinner cortex in established psychosis. Regions that displayed greater cortical thinning in future psychosis converters additionally displayed abnormal associations with age.

MeaningCHR status and later transition to psychosis is robustly associated with reduced cortical thickness. Abnormal age associations and specificity to cortical thickness may point to aberrant postnatal brain development in CHR, including pruning and myelination.

category: psychiatry and clinical psychology


title: Adaptive immune responses to SARS-CoV-2 in recovered severe COVID-19 patients

abstract:
ObjectivesThere is an imperative need to determine the durability of adaptive immunity to SARS-CoV-2. We enumerated SARS-CoV-2-reactive CD4+ and CD8+ T cells targeting S1 and M proteins and measured RBD-specific serum IgG over a period of 2-6 months after symptoms onset in a cohort of subjects who had recovered from severe clinical forms of COVID-19.

MethodsWe recruited 58 patients (38 males and 20 females; median age, 62.5 years), who had been hospitalized with bilateral pneumonia, 60% with one or more comorbidities. IgG antibodies binding to SARS-CoV-2 RBD were measured by ELISA. SARS-CoV-2-reactive CD69+-expressing-IFN{gamma}-producing-CD4+ and CD8+ T cells were enumerated in heparinized whole blood by flow cytometry for ICS.

ResultsDetectable SARS-CoV-2-S1/M-reactive CD69+-IFN-{gamma} CD4+ and CD8+ T cells were displayed in 17 (29.3%) and 6 (10.3%) subjects respectively, at a median of 84 days after onset of symptoms (range, 58-191 days). Concurrent comorbidities increased the risk (OR, 3.15; 95% CI, 1.03-9.61; P=0.04) of undetectable T-cell responses in models adjusted for age, sex and hospitalization ward. Twenty-one out of the 35 patients (60%) had detectable RBD-specific serum IgGs at a median of 118 days (range, 60 to 145 days) after symptoms onset. SARS-CoV-2 RBD-specific IgG serum levels were found to drop significantly over time.

ConclusionA relatively limited number of subjects who developed severe forms of COVID-19 had detectable SARS-CoV-2-S1/M IFN{gamma} CD4+ and CD8+ T cells at midterm after clinical diagnosis. Our data also indicated that serum levels of RBD-specific IgGs decline over time, becoming undetectable in some patients.


title: The spread of breathing air from wind instruments and singers using schlieren techniques

abstract: In this article, the spread of breathing air when playing wind instruments and singing was investigated and visualized using two methods: (1) schlieren imaging with a schlieren mirror and (2) background-oriented schlieren (BOS). These methods visualize airflow by visualizing density gradients in transparent media. The playing of professional woodwind and brass instrument players, as well as professional classical trained singers, were investigated to estimate the spread distances of the breathing air. For a better comparison and consistent measurement series, a single high and a single low note as well as an extract of a musical piece were investigated. Additionally, anemometry was used to determine the velocity of the spreading breathing air and the extent to which it was still quantifiable. The results presented in this article show there is no airflow escaping from the instruments, which is transported farther than 1.2 m into the room. However, differences in the various instruments have to be considered to assess properly the spread of the breathing air. The findings discussed below help to estimate the risk of cross-infection for wind instrument players and singers and to develop efficacious safety precautions, which is essential during critical health periods such as the current COVID-19 pandemic.

category: occupational and environmental health


title: Dynamics of antibodies to SARS-CoV-2 in convalescent plasma donors

abstract: The novel SARS-CoV-2 virus emerged in late 2019 and has caused a global health and economic crisis. The characterization of the human antibody response to SARS-CoV-2 infection is vital for serosurveillance purposes as well for treatment options such as transfusion with convalescent plasma or immunoglobin products derived from convalescent plasma. In this study, we measured antibody responses in 844 longitudinal samples from 151 RT-PCR positive SARS-CoV-2 convalescent adults during the first 34 weeks after onset of symptoms. All donors were seropositive at the first sampling moment and only one donor seroreverted during follow-up analysis. Anti-RBD IgG and anti-nucleocapsid IgG levels slowly declined with median half-lifes of 62 and 59 days during 2-5 months after symptom onset, respectively. The rate of decline of antibody levels diminished during extended follow-up. In addition, the magnitude of the IgG response correlated with neutralization capacity measured in a classic plaque reduction assay as well in our in-house developed competition assay. The result of this study gives valuable insight into the longitudinal response of antibodies to SARS-CoV-2.


title: No association between the SARS-CoV-2 variants and mortality rates in the Eastern Mediterranean Region

abstract: As the novel coronavirus SARS-CoV-2 continues to spread in all countries, there is a growing interest in monitoring and understanding the impact of emerging strains on virus transmission and disease severity. Here, we analyzed SARS-CoV-2 genomic sequences reported in the Eastern Mediterranean Region (EMR) countries, as of 1 January 2021. The majority ([~]75%) of these sequences originated from three out of 22 EMR countries, and 65.8% of all sequences belonged to GISAID clades GR, GH, G and GV. A delay ranging between 30-150 days from sample collection to sequence submission was observed across all countries, limiting the utility of such data in informing public health policies. We identified ten common non-synonymous mutations represented among SARS-CoV-2 in the EMR and several country-specific ones. Two substitutions, spike_D614G and NSP12_P323L, were predominantly concurrent in most countries. While the single incidence of NSP12_P323L was positively correlated with higher case fatality rates in EMR, no such association was established for the double (spike_D614G and NSP12_P323L) concurrent variant across the region. Our study identified critical data gaps in EMR highlighting the importance of enhancing surveillance and sequencing capacities in the region.


title: No Association Between the SARS-CoV-2 Variants and Mortality Rates in the Eastern Mediterranean Region


title: An Ebola virus disease model with fear and environmental transmission dynamics

abstract:
Recent Ebola virus disease (EVD) outbreaks have been limited not only to the interactions between humans but also to the complex interplay of the environment, human and socio-economic factors. Changes in human behaviour as a result of fear can also affect disease transmission dynamics. In this paper, a compartmental model is used to study the dynamics of EVD incorporating fear and environmental transmission. We formulate a fear dependent contact rate function to measure the rate of person to person, as well as pathogen to person transmissions. The epidemic threshold and the model equilibria are determined and, their stabilities are analysed. The model is validated by fitting it to data from the 2019 and 2020 EVD outbreaks in the Democratic Republic of Congo. Our results suggest that the fear of death from EVD may reduce the transmission and aid the control of the disease, but it is not sufficient to eradicate the disease. Policymakers need to also implement other control measures such as case finding, media campaigns, Quarantine and increase in the number of beds in the Ebola treatment centers, good laboratory services, safe burials and social mobilisation, to eradicate the disease.

HighlightsO_LIDue to its high case fatality rate, EVD undoubtedly instills fear in the inhabitants of any affected community.
C_LIO_LIWe propose an Ebola model with fear, which considers the pathogens in the environment to quantify the effect of fear and environmental transmission on the EVD disease dynamics.
C_LIO_LIThe fear of death from Ebola is proportional to the Ebola disease transmission rate.
C_LIO_LIAt high levels of fear, the number of EVD cases decrease.
C_LI


title: Continued need for non-pharmaceutical interventions after COVID-19 vaccination in long-term-care facilities

abstract: Long-term care facilities (LTCFs) bear disproportionate burden of COVID-19 and are prioritized for vaccine deployment. LTCF outbreaks could continue occurring during vaccine rollout due to incomplete population coverage, and the effect of vaccines on viral transmission are currently unknown. Declining adherence to non-pharmaceutical interventions (NPIs) against within-facility transmission could therefore limit the effectiveness of vaccination. We built a stochastic model to simulate outbreaks in LTCF populations with differing vaccination coverage and NPI adherence to evaluate their interacting effects. Vaccination combined with strong NPI adherence produced the least morbidity and mortality. Healthcare worker vaccination improved outcomes in unvaccinated LTCF residents but was less impactful with declining NPI adherence. To prevent further illness and deaths, there is a continued need for NPIs in LTCFs during vaccine rollout.


title: Indirect impacts of the COVID-19 pandemic at two tertiary neonatal units in Zimbabwe and Malawi: an interrupted time series analysis

abstract:
BackgroundDeaths from COVID-19 have exceeded 1.8 million globally (January 2020). We examined trends in markers of neonatal care before and during the pandemic at two tertiary neonatal units in Zimbabwe and Malawi.

MethodsWe analysed data collected prospectively via the NeoTree app at Sally Mugabe Central Hospital (SMCH), Zimbabwe, and Kamuzu Central Hospital (KCH), Malawi. Neonates admitted from 1 June 2019 to 25 September 2020 were included. We modelled the impact of the first cases of COVID-19 (Zimbabwe: 20 March 2020; Malawi: 3 April 2020) on number of admissions, gestational age and birth weight, source of admission referrals, prevalence of neonatal encephalopathy, and overall mortality.

FindingsThe study included 3,450 neonates at SMCH and 3,350 neonates at KCH. Admission numbers at SMCH did not initially change after the first case of COVID-19 but fell by 48% during a nurses strike (Relative risk (RR) 0{middle dot}52, 95%CI 0{middle dot}40-0{middle dot}68, p < 0{middle dot}002). At KCH, admissions dropped by 42% (RR 0{middle dot}58; 95%CI 0{middle dot}48-0{middle dot}70; p < 0{middle dot}001) soon after the first case of COVID-19. At KCH, gestational age and birth weight decreased slightly (1 week, 300 grams), outside referrals dropped by 28%, and there was a slight weekly increase in mortality. No changes in these outcomes were found at SMCH.

InterpretationThe indirect impacts of COVID-19 are context-specific. While this study provides vital evidence to inform health providers and policy makers, national data are required to ascertain the true impacts of the pandemic on newborn health.

FundingInternational Child Health Group, Wellcome Trust.

RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for evidence of the indirect impact of the COVID-19 pandemic on neonatal care in low-income settings using the search terms neonat* or newborn, and COVID-19 or SARS-CoV 2 or coronavirus, and the Cochrane low and middle income country (LMIC) filters, with no language limits between 01.10.2019 and 21.11.20. While there has been a decrease in global neonatal mortality rates, the smaller improvements seen in low-income settings are threatened by the direct and indirect impact of the COVID-19 pandemic. A modelling study of this threat predicted between 250000-1.1 million extra neonatal deaths as a result of decreased service provision and access in LMICs. A webinar and survey of frontline maternal/newborn healthcare workers in >60 countries reported a decline in both service attendance and in quality of service across the ante-, peri- and post-natal journey. Reporting fear of attending services, and difficulty in access, and a decrease in service quality due to exacerbation of existing service weaknesses, confusion over guidelines and understaffing. Similar findings were reported in a survey of healthcare workers providing childhood and maternal vaccines in LMICs. One study to date has reported data from Nepal describing an increase in stillbirths and neonatal deaths, with institutional deliveries nearly halved during lockdown.

Added value of this studyTo our knowledge, this is the first and only study in Sub-Saharan Africa describing the impact of COVID-19 pandemic on health service access and outcomes for newborns in two countries. We analysed data from the digital quality improvement and data collection tool, the NeoTree, to carry out an interrupted time series analysis of newborn admission rates, gestational age, birth weight, diagnosis of hypoxic ischaemic encephalopathy and mortality from two large hospitals in Malawi and Zimbabwe (n[~]7000 babies). We found that the indirect impacts of COVID-19 were context-specific. In Sally Mugabe Central Hospital, Zimbabwe, initial resilience was demonstrated in that there was no evidence of change in mortality, birth weight or gestational age. In comparison, at Kamuzu Central Hospital, Malawi, soon after the first case of COVID-19, the data revealed a fall in admissions (by 42%), gestational age (1 week), birth weight (300 grams), and outside referrals (by 28%), and there was a slight weekly increase in mortality (2%). In the Zimbabwean hospital, admission numbers did not initially change after the first case of COVID-19 but fell by 48% during a nurses strike, which in itself was in response to challenges exacerbated by the pandemic.

Implications of all the available evidenceOur data confirms the reports from frontline healthcare workers of a perceived decline in neonatal service access and provision in LMICs. Digital routine healthcare data capture enabled rapid profiling of indirect impacts of COVID-19 on newborn care and outcomes in two tertiary referral hospitals, Malawi and Zimbabwe. While a decrease in service access was seen in both countries, the impacts on care provided and outcome differed by national context. Health systems strengthening, for example digital data capture, may assist in planning context-specific mitigation efforts.


title: Construction of a demand and capacity model for intensive care and hospital ward beds, and mortality from COVID-19

abstract:
BackgroundThis paper describes the construction of a model used to estimate the number of excess deaths that could be expected as a direct consequence of a lack of hospital bed and intensive care unit (ICU) capacity.

MethodsA series of compartmental models was used to estimate the number of deaths under different combinations of care required (ICU or ward), and care received (ICU, ward or no care) in England up to the end of April 2021. Model parameters were sourced from publicly available government information, organisations collating COVID-19 data and calculations using existing parameters. A compartmental sub-model was used to estimate the mortality scalars that represent the increase in mortality that would be expected from a lack of provision of an ICU or general ward bed when one is required. Three illustrative scenarios for admissions numbers,  Optimistic,  Middling and  Pessimistic, are described showing how the model can be used to estimate mortality rates under different scenarios of capacity.

ResultsThe key output of our collaboration was the model itself rather than the results of any of the scenarios. The model allows a user to understand the excess mortality impact arising as a direct consequence of capacity being breached under various scenarios or forecasts of hospital admissions. The scenarios described in this paper are illustrative and are not forecasts.

There were no excess deaths from a lack of capacity in any of the  Optimistic scenario applications in sensitivity analysis.

Several of the  Middling scenario applications under sensitivity testing resulted in excess deaths directly attributable to a lack of capacity. Most excess deaths arose when we modelled a 20% reduction compared to best estimate ICU capacity. This led to 597 deaths (0.7% increase).

All the  Pessimistic scenario applications under sensitivity analysis had excess deaths. These ranged from 49,219 (19.4% increase) when we modelled a 20% increase in ward bed availability over the best-estimate, to 103,845 (40.9% increase) when we modelled a 20% shortfall in ward bed availability below the best-estimate. The emergence of a new, more transmissible variant (VOC 202012/01) increases the likelihood of real world outcomes at, or beyond, those modelled in our  Pessimistic scenario.

The results can be explained by considering how capacity evolves in each of the scenarios. In the Middling scenario, whilst ICU capacity may be approached and even possibly breached, there remains sufficient ward capacity to take lives who need either ward or ICU support, keeping excess deaths relatively low. However, the Pessimistic scenario sees ward capacity breached, and in many scenarios for a period of several weeks, resulting in much higher mortality in those lives who require care but do not receive it.

ConclusionsNo excess deaths from breaching capacity would be expected under the unadjusted  Optimistic assumptions of demand. The  Middling scenario could result in some excess deaths from breaching capacity, though these would be small (0.7% increase) relative to the total number of deaths in that scenario. The  Pessimistic scenario would certainly result in significant excess deaths from breaching capacity. Our sensitivity analysis indicated a range between 49,219 (19.4% increase) and 103,845 (40.9% increase) excess deaths.

Without the new variant, exceeding capacity for hospital and ICU beds did not appear to be the most likely outcome but given the new variant it now appears more plausible and, if so, would result in a substantial increase in the number of deaths from COVID-19.


title: Evaluation of at-home methods for N95 filtering facepiece respirator decontamination

abstract:
N95 filtering facepiece respirators (FFRs) are essential for the protection of healthcare professionals and other high-risk groups against Coronavirus Disease of 2019 (COVID-19). In response to shortages in FFRs during the ongoing COVID-19 pandemic, the Food and Drug Administration issued an Emergency Use Authorization permitting FFR decontamination and reuse. However, although industrial decontamination services are available at some large institutions, FFR decontamination is not widely accessible.

To be effective, FFR decontamination must 1) inactivate the virus; 2) preserve FFR integrity, specifically fit and filtering capability; and 3) be non-toxic and safe. Here we identify and test at-home heat-based methods for FFR decontamination that meet these requirements using common household appliances. Our results identify potential protocols for simple and accessible FFR decontamination, while also highlighting unsuitable methods that may jeopardize FFR integrity.

One sentence summarySurvey of at-home methods for N95 respirator decontamination using heat and evaluation of their effects on N95 respirator integrity.


title: Expression levels of HLA-DRB and HLA-DQ are associated with MHC Class II haplotypes in healthy individuals and rheumatoid arthritis patients

abstract: HLA-DRB1 alleles have been associated with several autoimmune diseases. In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), HLA-DRB1 shared epitope (SE) alleles are the major genetic risk factors. In order to investigate whether expression of different alleles of major histocompatibility complex (MHC) Class II genes influence functions of immune cells, we investigated transcriptomic profiles of a variety of immune cells from healthy individuals carrying different HLA-DRB1 alleles. Sequencing libraries from peripheral blood mononuclear cells, CD4+ T cells, CD8+ T cells, and CD14+ monocytes of 32 genetically pre-selected healthy female individuals were generated, sequenced and reads were aligned to the standard reference. For the MHC region, reads were mapped to available MHC reference haplotypes and AltHapAlignR was used to estimate gene expression. Using this method, HLA-DRB and HLA-DQ were found to be differentially expressed in different immune cells of healthy individuals as well as in whole blood samples of RA patients carrying HLA-DRB1 SE-positive versus SE-negative alleles. In contrast, no genes outside the MHC region were differentially expressed between individuals carrying HLA-DRB1 SE-positive and SE-negative alleles. Existing methods for HLA-DR allele-specific protein expression were evaluated but were not mature enough to provide appropriate complementary information at the protein level. Altogether, our findings suggest that immune effects associated with different allelic forms of HLA-DR and HLA-DQ may be associated not only with differences in the structure of these proteins, but also with differences in their expression levels.

category: rheumatology


title: Prediction of individuals at high-risk of chronic kidney disease during treatment with lithium for bipolar disorder

abstract:
BackgroundLithium is the most effective treatment in bipolar disorder. Its use is limited by concerns about risk of chronic kidney disease (CKD). We aimed to develop a model to predict risk of CKD following lithium treatment initiation, by identifying individuals with a high-risk trajectory of renal function.

MethodsWe used United Kingdom Clinical Practice Research Datalink (CPRD) electronic heath records (EHRs) from 2000-2018. CPRD Aurum for prediction model development and CPRD Gold for external validation. We used elastic net to generate a prediction model from potential features. We performed discrimination and calibration assessments in an external validation data set.

We included all patients aged [≥]16 with bipolar disorder prescribed lithium. To be included patients had to have [≥]1 year of follow-up before lithium initiation, [≥]3 estimated glomerular filtration rate (eGFR) measures after lithium initiation (to be able to determine a trajectory) and a normal ([≥]60 mL/min/1.73m2) eGFR at lithium initiation (baseline). In the Aurum development cohort 1609 fulfilled these criteria. The Gold external validation cohort included 934 patients.

We included 44 potential baseline features in the prediction model, including sociodemographic, mental and physical heath and drug treatment characteristics. We compared a full model with the 3-variable five-year kidney failure risk equation (KFRE) and a 3-variable elastic net model.

We used group-based trajectory modelling to identify latent trajectory groups for eGFR. We were interested in the group with deteriorating renal function (the high-risk group).

FindingsThe high-risk group included 191 (11.87%) of the Aurum cohort and 137 (14.67%) of the Gold cohort, of these 168 (87.96%) and 117 (85.40%) respectively developed CKD 3a or more severe during follow-up. The model, developed in Aurum, had a ROC area of 0.879 (95%CI 0.853-0.904) in the Gold external validation data set. At the empirical optimal cut-point defined in the development dataset, the model had a sensitivity of 0. 91 (95%CI 0.84-0.97) and a specificity of 0.74 (95% CI 0.67-0.82). However, a 3-variable elastic net model (including only age, sex and baseline eGFR) performed similarly well (ROC area 0.888; 95%CI 0.864-0.912), as did the KFRE (ROC area 0.870; 95%CI 0.841-0.898).

ConclusionsIndividuals at high-risk of a poor trajectory of renal function can be identified before initiation of lithium treatment by a simple equation including age, sex and baseline eGFR. We did not identify strong predicters of renal impairment specific to lithium treated patients.

category: nephrology


title: Neurophysiological and brain structural markers of cognitive frailty differs from Alzheimer's disease

abstract: With increasing life span, there is growing importance of understanding the mechanisms of successful cognitive ageing. In contrast, cognitive frailty has been proposed to be a precursor to Alzheimers disease. Here we test the hypothesis that cognitively frail adults represent a branch of healthy ageing, distinct from latent dementia. We used electro-magnetoencephalography and magnetic resonance imaging to investigate the structural and neurophysiological features of cognitive frailty in relation to healthy aging, and clinical presentations of mild cognitive impairment and Alzheimers disease. Cognitive performance of the cognitively frail group was similar to those with mild cognitive impairment. We used a novel cross-modal oddball task to induce mismatch responses to unexpected stimuli. Both controls and cognitively frail showed stronger mismatch responses and larger temporal grey matter volume, compared to people with mild cognitive impairment and Alzheimers disease. Our results suggest that cognitively frail represents a spectrum of normal ageing rather than incipient or undiagnosed Alzheimers disease. Lower cognitive reserve, hearing impairment and medical comorbidity might contribute to the aetiology of cognitive impairment.


title: Meta-Analysis of Adenoviral p53 Gene Therapy Clinical Trials in Recurrent Head and Neck Squamous Cell Carcinoma

abstract:
BackgroundWe conducted a meta-analysis of previous adenoviral p53 (Ad-p53) treatment data in recurrent head and neck squamous cell carcinoma (HNSCC) patients to identify optimal Ad-p53 treatment methods for future clinical trials.

MethodsThe meta-analysis involved recurrent HNSCC patients treated with Ad-p53 for whom p53 genotyping and immunohistochemistry tumor biomarker studies had been performed (n = 70). Ad-p53 tumor treatment responses defined by RECIST 1.1 criteria were correlated with Ad-p53 dose and tumor p53 biomarkers. Gene expression profiles induced by Ad-p53 treatment were evaluated using the Nanostring IO 360 panel.

ResultsAd-p53 dose based upon the injected tumor volume had a critical effect on tumor responses. All responders had received Ad-p53 doses greater than 7 x 1010 viral particles/cm3 of tumor volume. There was a statistically significant difference in tumor responses between patients treated with greater than 7 x 1010 viral particles/cm3 compared to patients treated at lower Ad-p53 doses (Tumor Response 31% (9/29) for Ad-p53 > 7 x 1010 viral particles/cm3 versus 0% (0/25) for Ad-p53 < 7 x 1010 viral particles/cm3; p = 0.0023). All responders were found to have favorable p53 biomarker profiles defined by less than 20% p53 positive tumor cells by immunohistochemistry (IHC), wild type p53 gene sequence or p53 deletions, truncations, or frame-shift mutations without functional p53 tetramerization domains. Preliminary gene expression profiling results revealed that Ad-p53 treatment increased Type I Interferon signaling, decreased TGF-beta and beta-catenin signaling resulting in an increased CD8+ T cell signature which are associated with increased responses to immune checkpoint blockade.

ConclusionsOur findings have important implications for future p53 targeted cancer treatments and identify fundamental principles to guide Ad-p53 gene therapy. We discovered that previous Ad-p53 clinical trials were negatively impacted by the inclusion of patients with unfavorable p53 biomarker profiles and by under dosing of Ad-p53 treatment. Future Ad-p53 clinical trials should have favorable p53 biomarker profiles inclusion criteria and Ad-p53 dosing above 7 x 1010 viral particles/cm3 of injected tumor volume. Preliminary gene expression profiling identified p53 mechanisms of action associated with responses to immune checkpoint blockade supporting evaluation of Ad-p53 in combination with immune checkpoint inhibitors.


title: Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19 - Preliminary report

abstract:
BackgroundThe efficacy of interleukin-6 receptor antagonists in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear.

MethodsWe evaluated tocilizumab and sarilumab in an ongoing international, multifactorial, adaptive platform trial. Adult patients with Covid-19, within 24 hours of commencing organ support in an intensive care unit, were randomized to receive either tocilizumab (8mg/kg) or sarilumab (400mg) or standard care (control). The primary outcome was an ordinal scale combining in-hospital mortality (assigned -1) and days free of organ support to day 21. The trial uses a Bayesian statistical model with pre-defined triggers to declare superiority, efficacy, equivalence or futility.

ResultsTocilizumab and sarilumab both met the pre-defined triggers for efficacy. At the time of full analysis 353 patients had been assigned to tocilizumab, 48 to sarilumab and 402 to control. Median organ support-free days were 10 (interquartile range [IQR] -1, 16), 11 (IQR 0, 16) and 0 (IQR -1, 15) for tocilizumab, sarilumab and control, respectively. Relative to control, median adjusted odds ratios were 1.64 (95% credible intervals [CrI] 1.25, 2.14) for tocilizumab and 1.76 (95%CrI 1.17, 2.91) for sarilumab, yielding >99.9% and 99.5% posterior probabilities of superiority compared with control. Hospital mortality was 28.0% (98/350) for tocilizumab, 22.2% (10/45) for sarilumab and 35.8% (142/397) for control. All secondary outcomes and analyses supported efficacy of these IL-6 receptor antagonists.

ConclusionsIn critically ill patients with Covid-19 receiving organ support in intensive care, treatment with the IL-6 receptor antagonists, tocilizumab and sarilumab, improved outcome, including survival. (ClinicalTrials.gov number: NCT02735707)

category: intensive care and critical care medicine


title: Combination of blood biomarkers and stroke scales improves identification of large vessel occlusions

abstract:
Background and PurposeAcute ischemic stroke caused by large vessel occlusions (LVO) is a major contributor to stroke deaths and disabilities; however, identification for emergency treatment is challenging.

AimsTo evaluate the diagnostic accuracy of a panel of biomarkers for LVO prediction.

Methods170 patients with suspected stroke were recruited retrospectively at one hospital. We analysed the plasma levels of D-dimer, OPN, OPG, GFAP, vWF, and ADAMTS13 in LVO vs non-LVO. Diagnostic performance was estimated by using blood biomarkers alone or in combination with NIHSS-derived stroke severity scales.

ResultsOur patient cohort comprised 20% stroke mimics, 11% transient ischemic attack, 11% hemorrhagic stroke, 15% LVO ischemic stroke, 28% non-LVO ischemic stroke, and 15% ischemic stroke with unknown LVO status. Multivariable analysis found that the optimal set of blood biomarkers for LVO prediction was D-dimer (OR 15.4, 95% CI 4.9 to 57.6; p-value<0.001) and GFAP (OR 0.83, 95% CI 0.90 to 0.99; p-value=0.03). The combination of D-dimer and GFAP with stroke scales significantly improved LVO prediction, compared to the stroke scales alone (p-value<0.001). The combination of biomarkers with constructed FAST-ED or EMSA scales achieved an AUC of 95% (95% CI 91-100%) or 93% (CI 95% 89-97%), a sensitivity of 91% (95% CI 71-98%) or 86 (95% CI 66-97%), and a specificity of 95% (95% CI 89-98%) or 94% (95% CI 88-98%), for LVO prediction, respectively.

ConclusionsThe combination of D-dimer, GFAP, and stroke scales could provide a simple and highly accurate tool for identifying LVO patients.


title: Quality Control Metrics for Whole Blood Transcriptome Analysis in the Parkinson's Progression Markers Initiative (PPMI)

abstract: The Michael J. Fox Foundations Parkinsons Progression Markers Initiative (PPMI) is an observational study to comprehensively evaluate Parkinsons disease (PD) patients using imaging, biologic sampling, clinical and behavioural assessments to identify biomarkers of PD progression. As part of this study, we obtained 4,756 whole blood samples from 1,570 subjects at baseline, 0.5, 1, 2, and 3 years from enrollment in the study. We isolated RNA and performed whole transcriptome sequencing in this longitudinal cohort. Here, we describe and quantify technical variability associated with this dataset through the use of pooled reference samples, including plate distribution, RNA quality, and outliers. This large, uniformly processed dataset is available to researchers at https://www.ppmi-info.org.

category: genetic and genomic medicine


title: Prioritization of putatively detrimental variants in euploid miscarriages

abstract: Miscarriage is the spontaneous termination of a pregnancy before 24 weeks of gestation. We studied the genome of euploid miscarried embryos from mothers in the range of healthy adult individuals to understand genetic susceptibility to miscarriage not caused by chromosomal aneuploidies. We developed GP, a pipeline that we used to prioritize 439 unique variants in 399 genes, including genes known to be associated with miscarriages. Among the prioritized genes we found STAG2 coding for the cohesin complex subunit, for which inactivation in mouse is lethal, and TLE4 a target of Notch and Wnt, physically interacting with a region on chromosome 9 associated to miscarriages.


title: Automatic Gender Detection in Twitter Profiles for Health-related Cohort Studies

abstract:
ObjectiveBiomedical research involving social media (SM) data is gradually moving from population-level to targeted, cohort-level data analysis. Though crucial for biomedical studies, SM users demographic information (e.g., gender) is often not explicitly known from profiles. Here we present an automatic gender classification system for SM and we illustrate how gender information can be incorporated into a SM-based health-related study.

Materials and MethodsWe used two large Twitter datasets: (i) public, gender-labeled users (Dataset-1), and (ii) users who have self-reported nonmedical use of prescription medications (Dataset-2). Dataset-1 was used to train and evaluate the gender detection pipeline. We experimented with machine-learning algorithms including support vector machines (SVMs) and deep-learning models, and released packages including M3. We considered users information including profile and tweets for classification. We also developed a meta-classifier ensemble that strategically uses the predicted scores from the classifiers. We applied the best-performing pipeline to Dataset-2 to assess the systems utility.

Results and DiscussionWe collected 67,181 and 176,683 users for Dataset-1 and Dataset-2, respectively. A meta-classifier involving SVM and M3 performed the best (Dataset-1 accuracy: 94.4% [95%-CI: 94.0%-94.8%]; Dataset-2: 94.4% [95%-CI: 92.0%-96.6%]. Including automatically-classified information in the analyses of Dataset-2 revealed gender-specific trends-- proportions of females closely resemble data from the National Survey of Drug Use and Health 2018 (tranquilizers: 0.50 vs. 0.50; stimulants: 0.50 vs. 0.45), and the overdose Emergency Room Visit due to Opioids by CDC (pain relievers: 0.38 vs. 0.37).

ConclusionOur publicly-available, automated gender detection pipeline may aid cohort-specific social media data analyses (https://bitbucket.org/sarkerlab/gender-detection-for-public).


title: Zorro versus Covid-19: fighting the pandemic with face masks

abstract: To confront the global Covid-19 pandemic and reduce the spread of the virus, we need to better understand if face mask use is effective to contain the outbreak and investigate the potential drivers in favor of mask adoption. It is highly questionable since there is no consensus among the general public despite official recommendations. For the first time, we conduct a panel econometric exercise to assess the dynamic impact of face mask use on both infected cases and fatalities at a global scale. We reveal a negative impact of mask wearing on fatality rates and on the Covid-19 number of infected cases. The delay of action varies from around 7 days to 28 days concerning infected cases but is more longer concerning fatalities. We also document the increasing adoption of mask use over time. We find that population density and pollution levels are significant determinants of heterogeneity regarding mask adoption across countries, while altruism, trust in government and demographics are not. Surprisingly, government effectiveness and income level (GDP) have an unexpected influence. However, strict government policies against Covid-19 have the most significant effect on mask use. Therefore, the most effective way of increasing the level of mask wearing is to enforce strict laws on the wearing of masks.

category: health policy


title: COVID-19 Rapid Antigen Test at hospital admission associated to the knowledge of individual risk factors allow overcoming the difficulty of managing suspected patients in hospitals

abstract: Early diagnosis of SARS-CoV-2 is essential to limiting the spread of the virus and managing infected patients during hospitalization. The sensitivity of RT-qPCR is contested by the fact that it is time-consuming, executed by trained technicians in proper environment for material extraction. Here, we evaluated the first SARS-CoV-2 antigen test recommended by the World Health Organization at September, 2020 as an alternative for immediate diagnosis of symptomatic and suspected patients at a hospital in Brazil during the epidemic peak. All patients were submitted to RT-qPCR and rapid antigen test using nasopharyngeal swabs rigorously collected at the same time. Demographics, baseline comorbidities, symptoms and outcomes were considered. Prediction analysis revealed that previous stroke, chronic obstructive pulmonary disease, desaturation and tachypnea were the most relevant determinants of the death of COVID-19 patients. Comparison between the rapid antigen test and RT-qPCR revealed an overall PPV of 97%, extended to 100% when performed between 4 and 15 days of symptoms, with an accuracy of 90-91% from days 1 to 7 and a  Substantial agreement. The rapid antigen test presented no inconclusive result. Among the discordant results and RT-qPCR inconclusives, 72% presented bilateral multifocal ground-glass opacities on imaging and other exams alterations. The median time to obtain RT-qPCR results was 83.6 hours, against 15 minutes for the rapid test, precious time for deciding on patient isolation and management. Knowledge of the risk factors and a rapid diagnosis upon patient admission is critical to reduce mortality of COVID-19 patients, hospital internal costs and in-hospital transmission.


title: Mobilefuge: A low-cost, portable, open source, 3D-printed centrifuge that can be used for purification of saliva samples for SARS-CoV2 detection

abstract: One of the best ways to contain the spread of COVID-19 is frequent testing of as many people as possible and timely isolation of uninfected personnel from infected personnel. However, the cost of massive testing is affordable in many countries. The existing technologies might not be scalable to offer affordable testing for millions of people. To address this issue, novel testing methods based on Loop-Mediated Isothermal Amplification (LAMP) were proposed that are more sensitive, require less reagents and can work with saliva samples instead of more tedious nasal swabs. As a result, LAMP based protocols can make it possible to drive the cost down to one dollar per test. These LAMP based methods require a centrifuge device, mostly for separation of viral particles from reaction inhibitors in saliva samples. However, centrifuge is neither accessible nor affordable in many resource limited settings, especially during this pandemic situation when normal supply chains are heavily disrupted. To overcome these challenges, we invented a low-cost centrifuge that can be useful for carrying out low-cost LAMP based detection of SARS-Cov2 virus in saliva. The 3D printed centrifuge (Mobilefuge) is portable, robust, stable, safe, easy to build and operate. The Mobilefuge doesnt require soldering or programming skills and can be built without any specialised equipment, yet practical enough for high throughput use. More importantly, Mobilefuge can be powered from widely available USB ports, including mobile phones and associated power supplies. This allows the Mobilefuge to be used even in off-grid and resource limited settings. We believe that our invention will aid the efforts to contain the spread of COVID-19 by lowering the costs of testing equipment. Apart from the COVID-19 testing, the Mobilefuge can have applications in the field of biomedical research and diagnostics.