Identification Of Genetically Related HCV Infections Among Self-Described Injecting Partnerships BackgroundThe current opioid epidemic across the United States has fueled a surge in the rate of new HCV infections among young persons who inject drugs (PWIDs). Paramount to interrupting transmission is targeting these high-risk populations and understanding the underlying network structures facilitating transmission within these communities.

MethodsDeep sequencing data were obtained for 52 participants from 32 injecting partnerships enrolled in the UFO Partner Study which is a prospective study of self-described injecting dyad partnerships from a large community-based study of HCV infection in young adult PWIDs from San Francisco. Phylogenetically linked transmission events were identified using traditional genetic-distance measures and viral deep sequence phylogenies reconstructed to determine the statistical support of inferences and the direction of transmission within partnerships.

ResultsUsing deep sequencing data, we found that 12 of 32 partnerships were genetically similar and clustered. Three additional phylogenetic clusters were found describing novel putative transmission links outside of the injecting relationship. Transmission direction was inferred correctly for five partnerships with the incorrect transmission direction inferred in more than 50% of cases. Notably, we observed that phylogenetic linkage was most often associated with a lower number of network partners and involvement in a sexual relationship.

ConclusionsDeep sequencing of HCV among self-described injecting partnerships demonstrates that the majority of transmission events originate from outside of the injecting partnership. Furthermore, these findings caution that phylogenetic methods may be unable to routinely infer the direction of transmission among PWIDs especially when transmission events occur in rapid succession within high-risk networks.

SummaryDeep sequencing of HCV from 32 self-described injecting partnerships revealed that only 37% were genetically similar and inferring the direction of transmission using phylogenetic tools is challenging as HCV transmission is complex and multifaceted.
Effect of control measures on the pattern of COVID-19 Epidemics in Japan BackgroundCOVID-19 has spread worldwide since its emergence in 2019. In contrast to many other countries with epidemics, Japan differed in that it avoided lockdowns and instead asked people for self-control. A travel campaign was conducted with a sizable budget, but the number of PCR tests was severely limited. These choices may have influenced the course of the epidemic.

MethodsThe increase or decrease in the classes of SARS-CoV-2 variants was estimated by analyzing the published sequences with an objective multivariate analysis. This approach observes the samples in multiple directions, digesting complex differences into simpler forms. The results were compared over time with the number of confirmed cases, PCR tests, and overseas visitors. The kinetics of infection were analyzed using the logarithmic growth rate.

ResultsThe declared states of emergency failed to alter the movement of the growth rate. Three epidemic peaks were caused by domestically mutated variants. In other countries, there are few cases in which multiple variants have peaked. However, due to the relaxation of immigration restrictions, several infective variants have been imported from abroad and are currently competing for expansion, creating the fourth peak. By April 2021, these foreign variants exceeded 80%. The chaotic situation in Japan will continue for some time, in part because no effort has been made to identify asymptomatic carriers, and details of the vaccination program are undecided.
Caffeine and Methylliberine: A Human Pharmacokinetic Interaction Study 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. Prognostication for prelabor rupture of membranes and the time of delivery in nationwide insured women: development, validation, and deployment ImportancePrognostic predictions of prelabor rupture of membranes lack proper sample sizes and external validation.

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

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

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

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

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

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

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

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

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

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

MeaningPreliminary prediction can be conducted in a wide population of insured women to predict prelabor rupture of membranes and estimate the time of delivery. Comparison of algorithm-based versus single-item diagnostic measures of anxiety and depression disorders in the GLAD and COPING cohorts BackgroundUnderstanding and improving outcomes for people with anxiety or depression often requires large studies. To increase participation and reduce costs, such research is typically unable to utilise "gold-standard" methods to ascertain diagnoses, instead relying on remote, self-report measures.

AimsTo assess the comparability of remote diagnostic methods for anxiety and depression disorders commonly used in research.

MethodParticipants from the UK-based GLAD and COPING NBR cohorts (N = 58,400) completed an online questionnaire between 2018-2020. Responses to detailed symptom reports were compared to DSM-5 criteria to generate algorithm-based diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD), specific phobia, social anxiety disorder, panic disorder, and agoraphobia. Participants also self-reported any prior diagnoses from health professionals, termed single-item diagnoses. "Any anxiety" included participants with at least one anxiety disorder. Agreement was assessed by calculating accuracy, Cohens kappa, McNemars chi-squared, sensitivity, and specificity.

ResultsAgreement between diagnoses was moderate for MDD, any anxiety, and GAD, but varied by cohort. Agreement was slight to fair for the phobic disorders. Many participants with single-item GAD did not receive an algorithm-based diagnosis. In contrast, algorithm-based diagnoses of the phobic disorders were more common than single-item diagnoses.

ConclusionsAgreement for MDD, any anxiety, and GAD was higher for cases in the case-enriched GLAD cohort and for controls in the general population COPING NBR cohort. For anxiety disorders, single-item diagnoses classified most participants as having GAD, whereas algorithm-based diagnoses distributed participants more evenly across the anxiety disorders. Further validation against gold standard measures is required. Preferences and patterns of response to public health advice during the COVID-19 pandemic With recurring waves of the Covid-19 pandemic, a dilemma facing public health leadership is whether to provide public advice that is medically optimal (e.g., most protective against infection if followed), but unlikely to be adhered to, or advice that is less protective but is more likely to be followed. To provide insight about this dilemma, we examined and quantified public perceptions about the tradeoff between (a) the stand-alone value of health behavior advice, and (b) the advices adherence likelihood. In a series of studies about preference for public health leadership advice, we asked 1,061 participants to choose between (1) strict advice that is medically optimal if adhered to but which is less likely to be broadly followed, and (2) relaxed advice, which is less medically effective but more likely to gain adherence - given varying infection expectancies. Participants preference was consistent with risk aversion. Offering an informed choice alternative that shifts volition to advice recipients only strengthened risk aversion, but also demonstrated that informed choice was preferred as much or more than the risk-averse strict advice. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

ObjectiveTo develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging.

DesignDerivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules.

SettingPrimary and Express care clinics in a Pennsylvania health system.

ParticipantsPatients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19.

Main outcomes and measuresClassification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC).

ResultsOverall, 7.4% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21) and 5.5% in the late validation cohort (3806 patients presenting 3/1/21 or later) were ultimately hospitalized. We developed and temporally validated three risk scores that all included age, dyspnea, and the presence of comorbidities, adding respiratory rate for the second score and oxygen saturation for the third. All had very good overall accuracy (AUC 0.77 to 0.78) and classified over half of patients in the validation cohort as very low risk with a 1.7% or lower likelihood of hospitalization. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization (2.8%).

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/. Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.

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

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

DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. A Randomised Trial of a Wearable UV dosimeter for Skin Cancer Prevention BackgroundNon-melanoma skin cancer (NMSC) is the most prevalent cancer in the United States, affecting 5 million people and costing $8.1 billion per year. Despite well-defined guidelines on ultraviolet radiation (UVR) avoidance, it remains difficult for people to assess their individual exposure, as UVR is invisible and the onset of symptoms due to UVR damage are delayed.

MethodsIn a prospective, randomized-controlled trial, 97 patients with a history of actinic keratoses were enrolled from March 2018 to July 2018 and followed over 6 months. 50 patients were given a wearable device that measured UV exposure and a smartphone application that provided both real-time and cumulative UV exposure information, and 47 patients were provided with UV protection counseling by a dermatologist.

ResultsWe observed a significant decrease in the incidence rate of NMSC in the intervention group compared to the control group over 3 months (p = 0.02). We did not observe a significant decrease in the incidence rate of actinic keratoses (AK) in the intervention group compared to the control group. The observed clinical benefit was not accompanied by psychological side effects such as anxiety and depression.

ConclusionsThis study suggests that providing real-time UV exposure data using a wearable UV dosimeter is a safe and effective behavioral change strategy to prevent NMSC. (Funded by the National Cancer Institute, contract HHSN261201700005C; ClinicalTrials.gov number NCT03315286.) Knee-extensor strength, symptoms, and need for surgery after two, four, or six exercise sessions/week using a home-based one-exercise program: A randomized dose-response trial of knee-extensor resistance exercise in patients eligible for knee replacement (the QUADX-1 trial). ObjectiveTo investigate firstly the efficacy of three different dosages of one home-based, knee-extensor resistance exercise on knee-extensor strength in patients eligible for knee replacement, and secondly, the influence of exercise on symptoms, physical function and decision on surgery.

MethodOne-hundred and forty patients eligible for knee replacement were randomized to three groups: 2, 4 or 6 home-based knee-extensor resistance exercise-sessions per week (group 2, 4 and 6 respectively) for 12 weeks. Primary outcome: isometric knee-extensor strength. Secondary outcomes: Oxford Knee Score, Knee injury and Osteoarthritis Outcome Score, average knee pain last week (0-10 numeric rating scale), 6-minute walk test, stair climbing test, exercise adherence and "need for surgery".

ResultsPrimary analysis: Intention-to-treat analysis of 140 patients did not find statistically significant differences between the groups from baseline to after 12 weeks of exercise in isometric knee-extensor strength: Group 2 vs. 4 (0.003 Nm/kg (0.2%) [95% CI -0.15 to 0.15], P=0.965) and group 4 vs. 6 (-0.04 Nm/kg (-2.7%) [95% CI -0.15 to 0.12], P=0.628). Secondary analysis: Intention-to-treat analyses showed statistically significant differences between the two and six sessions/week groups in favor of the two sessions/week group for Oxford Knee Score: 4.8 OKS points (15.2%) [1.3 to 8.3], P=0.008) and avg. knee pain last week (NRS 0-10): - 1.3 NRS points (-19.5%) [-2.3 to -0.2], P=0.018. After the 12-week exercise intervention, data were available for 117 patients (N=39/group): 38 (32.5%) patients wanted surgery and 79 (67.5%) postponed surgery. This was independent of exercise dosage.

ConclusionIn patients eligible for knee-replacement we found no between-group differences in isometric knee extensor strength after 2, 4 and 6 knee-extensor resistance exercise sessions per week. We saw no indication of an exercise dose-response relationship for isometric knee-extensor strength and only clinically irrelevant within group changes. For some secondary outcome (e.g. KOOS subscales) we found clinically relevant within group changes, which could help explain why only one in three patients decided to have surgery after the simple home-based exercise intervention.

Trial registrationClinicalTrials.gov identifier: NCT02931058. Preprint: https://doi.org/10.1101/2021.04.07.21254965. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

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

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

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. The effect of hypersensitivity pneumonitis guideline on pathologic diagnosis of interstitial pneumonia Hypersensitivity pneumonitis (HP) and interstitial pneumonia (IP) have several overlapping characteristics, and a high diagnostic concordance rate of HP is rarely obtained. New guideline, highly influenced by pathology, were devised for its diagnosis. We recently reported that the 2020 HP guideline may result in a possible overdiagnosis of fibrotic HP (fHP) through multidisciplinary discussion. Here, we attempted to investigate the impact of the 2020 HP guideline on the pathological diagnosis of cases previously diagnosed as IP. We classified 247 cases with fibrotic IP diagnoses sourced from 2014-2019 into three categories according to the 2020 HP guideline: typical, probable, and indeterminate HP. The original pathological diagnosis and categorization based on the 2020 HP guideline were compared. The clinical data including serum data and pulmonary function tests were compared among groups. The number of cases that changed to HP from an original diagnosis other than HP based on the guideline was 56 (23%). The clinical data of these cases bore a greater resemblance to cases diagnosed as indeterminate for HP than those diagnosed as typical or probable. The ratio of typical and probable HP to the total cases was significantly lower when using a transbronchial lung cryobiopsy (TBLC). Based on the new guideline, the pathological diagnosis of HP efficiently excluded HP cases but increased the rate of HP diagnosis for cases with fibrotic IP that may not suit an HP diagnosis. Thus, a TBLC may not be useful when imparting findings for fibrotic HP diagnosis using the new criteria.

Key messagesO_LIWhat is the key question? >
Does the 2020 HP Guideline improve pathological diagnosis?
C_LIO_LIWhat is the bottom line? >
By applying the new guideline, about 1/4 of the pathological diagnoses were changed from not chronic HP to probable or typical fHP, but most of the changed cases showed a clinical picture closer to not chronic HP.
C_LIO_LIWhy read on? >
To understand that simple application of the pathological criteria of the HP guideline may cause a misleading diagnosis.
C_LI COVID Outcome Prediction in the Emergency Department (COPE): Development and validation of a model for predicting death and need for intensive care in COVID-19 patients Background and aimCOVID-19 is putting extraordinary pressure on emergency departments (EDs). To support decision making in the ED, we aimed to develop a simple and valid model for predicting mortality and need for intensive care unit (ICU) admission in suspected COVID-19 patients.

MethodsFor model development, we retrospectively collected data of patients who were admitted to 4 large Dutch hospitals with suspected COVID-19 between March and August 2020 (first wave of the pandemic). Based on prior literature we considered quickly and objectively obtainable patient characteristics, vital parameters and blood test values as predictors. Logistic regression analyses with post-hoc uniform shrinkage was used to obtain predicted probabilities of in-hospital death and of the need for ICU admission, both within 28 days after hospital admission. We assessed model performance (Area Under the ROC curve (AUC); calibration plots) with temporal validation in patients who presented between September and December 2020 (second wave). We used multiple imputation to account for missing values.

ResultsThe development data included 5,831 patients, of whom 629 (10.8%) died and 5,070 (86.9%) were discharged within 28 days after admission. ICU admission was fully recorded for 2,633 first wave patients in 2 hospitals, with 214 (8%) ICU admissions within 28 days. A simple model - COVID Outcome Prediction in the Emergency Department (COPE) - with age, respiratory rate, C-reactive protein, lactic dehydrogenase, albumin and urea captured most of the ability to predict death. COPE was well-calibrated and showed good discrimination in 3,252 second wave patients (AUC in 4 hospitals: 0.82 [0.78; 0.86]; 0.82 [0.74; 0.90]; 0.79 [0.70; 0.88]; 0.83 [0.79; 0.86]). COPE was also able to identify patients at high risk of needing IC in 706 second wave patients with complete information on ICU admission (AUC: 0.84 [0.78; 0.90]; 0.81 [0.66; 0.95]). The models are implemented in web-based and mobile applications.

ConclusionCOPE is a simple tool that is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19 and may help patients and doctors in decision making.

CONTRIBUTION TO THE LITERATUREO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIPrediction models have the potential to support decision making about hospital admission of patients presenting to the emergency department with suspected COVID-19
C_LIO_LIMost currently available models that were independently assessed contain a high risk of bias
C_LIO_LIPromising models were developed in different patient selections and included predictors that are not quickly and objective obtainable in emergency departments
C_LI

What this study addsO_LIA simple and objective tool ("COPE") is well able to predict mortality and need for ICU admission for patients who present to the ED with suspected COVID-19
C_LIO_LICOPE may support ED physicians to identify high-risk patients - i.e. those at high risk of deterioration and/or death - requiring treatment in the ICU, intermediate-risk patients requiring admission to the clinical ward, and low-risk patients who can potentially be sent home
C_LI Factors affecting first return to work following arthroscopic rotator cuff repair: A retrospective observational study in an occupational medicine clinic and single-surgeon practice BackgroundReturn to work (RTW) following arthroscopic rotator cuff repair (aRCR) within New South Wales (NSW), Australia, under compensable schemes has not been reported.

AimsDetermine factors affecting RTW status and time in patients treated with aRCR under state-based compensation schemes, compared to those outside such schemes.

MethodsPatients undergoing aRCR by one surgeon with minimum 1-year follow-up were grouped into those under (CP) or outside (non-CP) workers or vehicle accident compensation schemes, matched by age and gender. RTW status and time were assessed using chi-square analysis and multivariable linear regression.

ResultsOf 1054 available patients, 90 CP patients were identified with 29 consented and matched to non-CP (N=29). A higher proportion of CP patients (17.2 vs 0%, P<0.001) never returned to work and a lower proportion resumed pre-injury duties at first RTW (3 vs 52%, P<0.01). Median time to first RTW did not differ between CP and non-CP groups (5.1 vs 4.4, P=0.86). Smoking (P=0.007) and post-injury activity level (P=0.004) were significantly associated with longer time to first RTW, whereas compensation status was not.

ConclusionsCP patients undergoing aRCR in NSW are at risk of not returning to work. For those that return, there is no significant difference compared to non-CP in time to first RTW. Particularly, patient and management factors associated with extended time to first RTW have been identified. Interventions aimed at modifiable factors such as smoking cessation and increasing preoperative activity may improve future outcomes.

What is already known about this subjectO_LIWork-related injury and disease present a significant financial burden to the Australian economy ($AUD61.8billion per annum), with shoulder conditions due to body stressing accounting for 7% of this total cost (>$AUD4.2billion)
C_LIO_LIPatients receiving compensation appear to have poorer outcomes and take longer to return to work than their non-compensated counterparts, but the degree to which this occurs is variably reported in the literature
C_LIO_LIThe effect of modifiable factors on return to work status and time remain unclear, and have not previously been reported for the Australian population under the New South Wales workers compensation scheme
C_LI

What this study addsO_LIPatients receiving arthroscopic rotator cuff repair under a compensable scheme in New South Wales are at increased risk of not returning to work compared to patients presenting outside of a compensable scheme and patients in equivalent schemes internationally
C_LIO_LIPatients reporting a longer duration of symptoms and smokers are at increased risk of extended time to first return to work
C_LI

What impact this may have on practice or policyO_LIThe study has identified smoking and pre-surgery activity levels as key targets for intervention in patients receiving arthroscopic rotator cuff repair under a workers compensation scheme in New South Wales
C_LIO_LIBy further investigating whether interventions designed to modify these factors are able to favourably affect patient outcomes, there is potential to return patients to their preoperative level of work sooner
C_LI Statistical modeling for quality risk assessment of clinical trials: follow-up at the era of remote auditing BackgroundAs investigator site audits have largely been conducted remotely during the COVID-19 pandemic, remote quality monitoring has gained some momentum. To further facilitate the conduct of remote Quality Assurance (QA) activities for clinical trials, we developed new quality indicators, building on a previously published statistical modeling methodology.

MethodsWe modeled the risk of having an audit or inspection finding using historical audits and inspections data from 2011 - 2019. We used logistic regression to model finding risk for 4 clinical impact factor (CIF) categories: Safety Reporting, Data Integrity, Consent and Protecting Endpoints.

ResultsWe could identify 15 interpretable factors influencing audit finding risk of 4 out of 5 CIF categories. They can be used to realistically predict differences in risk between 25 and 43% for different sites which suffice to rank sites by audit and inspection finding risk.

ConclusionContinuous surveillance of the identified risk factors and resulting risk estimates could be used to complement remote QA strategies for clinical trials and help to manage audit targets and audit focus also in post-pandemic times. What We Learned from COVID-19: From endotheliitis to treatment ObjectiveCOVID-19 may yield a variety of clinical pictures, differing from pneumonitis to Acute Respiratory Distress Syndrome (ARDS) along with vascular damage in the lung tissue, named as endotheliitis. To date, no specific treatment strategy was approved by any authority for the prevention or treatment of COVID-19 in terms of endotheliitis-related comorbidities. Here, we present our experience of COVID-19 by evaluating 11,190 COVID-19 patients with the manifestations of endotheliitis in skin, lung, and brain tissues according to the different phases of COVID-19.

MethodsAfter a retrospective examination, patients were divided into three groups according to their repercussions of vascular distress, which were represented by radiological, histopathological, and clinical findings. (Group A: no or mild pulmonary involvement, Group B: moderate pulmonary involvement with clinical risk of deterioration, Group C: severe pulmonary involvement and respiratory failure). We presented the characteristics and disease course of seven representative and complicated cases which represents the different phases of the disease, and discussed the treatment strategies in each group. The current pathophysiological mechanisms responsible from SARS-CoV-2 infection, COVID-19 related respiratory failure and current treatment strategies were reviewed and discussed in detail.

ResultsAmong 11.190 patients, 9294 patients met the criteria for Group A, and 1376 patients were presented to our clinics with Group B characteristics. Among these patients, 1896 individuals(Group B and Group C) were hospitalized. While 1220 inpatients were hospitalized within the first 10 days after the diagnosis, 676 of them were worsened and hospitalized 10 days after their diagnosis. Among hospitalized patients, 520 of them did not respond to group A and B treatments and developed hypoxemic respiratory failure (Group C) and 146 individuals needed ventilator support and were followed in the intensive care unit, and 43 (2.2%) patients died.

ConclusionDistinctive manifestations in each COVID-19 patient, including non-respiratory conditions in the acute phase and the emerging risk of long-lasting complications, suggest that COVID-19 has an endotheliitis-centred thrombo-inflammatory pathophysiology. Endotheliitis can also explain the mechanism behind the respiratory failure in COVID-19, and the difference of COVID-19 related ARDS from ARDS seen in other critical conditions. In addition, use of early corticosteroid in patients with early symptoms and early tocilizumab in ICU helps to reduce mortality and progression of the disease. Endotheliitis-based pathophysiological mechanisms are known to be momentarily changing and difficut to manage due to their risk of sudden aggrevation. Hence, daily evaluation of clinical, laboratory and radiological findings of patients and deciding appropriate pathophysiological treatment would help to reduce the mortality rate of COVID-19. Airway management, procedural data, and mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19) In India, the second wave of coronavirus disease (COVID -19) was associated with a distinct surge in cases of invasive fungal infection with mucormycosis. This disease was seen typically in the sinonasal form in COVID-19 patients. Uncontrolled diabetes, steroid use in COVID-19 treatment, etc. were some of the postulated risk factors for the association of COVID 19 and Mucormycosis. The management plan of these cases included surgical debridement, systemic antifungal therapy, sugar control, and management of antifungal related systemic adverse effects. In this retrospective case record review, we aimed to evaluate the airway management plan, demographics, and overall outcomes in patients undergoing surgical resection for COVID-19 associated mucormycosis. Forty-one (71.9 %) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) had a diagnosis of rhino-orbital mucormycosis, and 2 patients (3.5%) were diagnosed with palatal mucormycosis. Total 44 (77.19 %) patients had co-morbidities. The most common co-morbidity was Diabetes Mellitus 42 (73.6%), followed by hypertension 21 (36.84%) and Acute kidney injury 14 (28.07%). We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 out of 57 patients. In our study, mortality occurred in 7 (12.28 %) patients. The median mortality time was 60 (range, 27-74) days. The median time to hospital discharge was 53.5 (range,10-85) days. Managing COVID-19 on its own is challenging and additional mucormycosis can lead to increased morbidity and mortality. Despite challenges and risks, timely and meticulous interventions can reduce complications. Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

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

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

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. A protocol for a multicentre observational study across an integrated care system to understand the effect of living with frailty on access to video consultations Risks for digital exclusion include older age, disability, and deprivation. No literature exists examining frailty as an additional possible risk factor. Many studies have shown frailty to be a more accurate predictor of adverse outcome in healthcare than age alone. Understanding risk factors for digital exclusion may help healthcare services appropriately tailor interventions. The Healthier Together integrated care system (HTICS) in Bristol is developing video consultations for clinics. The aim of this prospective observational cross-sectional study is to identify whether living with frailty is a risk factor of digital exclusion from video consultation. Data will be collected using a structured survey including patients from three sites across the Heal secondary care services at North Bristol Trust, and then two subsequent sites will be included across HTICS. Data will be collected on known risk factors for digital exclusion, frailty using the Clinical Frailty Scale, and will cover four domains for digital exclusion as defined by NHS Digital: access, skill, motivation, and confidence. Data will be presented with descriptive statistics. The association between frailty and outcomes will be analysed with a multivariable logistic regression.

Key Study Contacts

O_TBL View this table:
org.highwire.dtl.DTLVardef@134f5d7org.highwire.dtl.DTLVardef@1f8149forg.highwire.dtl.DTLVardef@11dbf0org.highwire.dtl.DTLVardef@7e854borg.highwire.dtl.DTLVardef@61272f_HPS_FORMAT_FIGEXP  M_TBL C_TBL Study Summary

O_TBL View this table:
org.highwire.dtl.DTLVardef@53a9f0org.highwire.dtl.DTLVardef@b9e76dorg.highwire.dtl.DTLVardef@108bd12org.highwire.dtl.DTLVardef@b500ddorg.highwire.dtl.DTLVardef@14be1d8_HPS_FORMAT_FIGEXP  M_TBL C_TBL Funding and Support in Kind

O_TBL View this table:
org.highwire.dtl.DTLVardef@d86811org.highwire.dtl.DTLVardef@1985973org.highwire.dtl.DTLVardef@118ca5corg.highwire.dtl.DTLVardef@8d7839org.highwire.dtl.DTLVardef@1cff6e1_HPS_FORMAT_FIGEXP  M_TBL C_TBL Role of Study Sponsor and FunderThe pilot at North Bristol Trust (NBT) is overseen by Neuromusculoskeletal (NMSK) Division governance. NBT NMSK Division takes responsibility for ensuring that the design of the study meets appropriate standards and that arrangements are in place to ensure appropriate conduct and reporting. Governance oversight for Hospital at Home was registered with NBT NMSK, and for primary care with Horfield Health Centre.

Roles and Responsibilities

Study Flow Chart

O_TBL View this table:
org.highwire.dtl.DTLVardef@594232org.highwire.dtl.DTLVardef@904b3org.highwire.dtl.DTLVardef@138af7org.highwire.dtl.DTLVardef@10898a3org.highwire.dtl.DTLVardef@15d2719_HPS_FORMAT_FIGEXP  M_TBL C_TBL Best practices for multi-ancestry, meta-analytic transcriptome-wide association studies: lessons from the Global Biobank Meta-analysis Initiative SUMMARYThe Global Biobank Meta-analysis Initiative (GBMI), through its genetic and demographic diversity, provides a valuable opportunity to study population-wide and ancestry-specific genetic associations. However, with multiple ascertainment strategies and multi-ethnic study populations across biobanks, the GBMI provides a distinct set of challenges in implementing statistical genetics methods. Transcriptome-wide association studies (TWAS) are a popular tool to boost detection power for and provide biological context to genetic associations by integrating single nucleotide polymorphism to trait (SNP-trait) associations from genome-wide association studies (GWAS) with SNP-based predictive models of gene expression. TWAS presents unique challenges beyond GWAS, especially in a multi-biobank and meta-analytic setting like the GBMI. In this work, we present the GBMI TWAS pipeline, outlining practical considerations for ancestry and tissue specificity and meta-analytic strategies, as well as open challenges at every step of the framework. Our work provides a strong foundation for adding tissue-specific gene expression context to biobank-linked genetic association studies, allowing for ancestry-aware discovery to accelerate genomic medicine. Pausing methotrexate improves immunogenicity of COVID-19 vaccination in elderly patients with rheumatic diseases ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).

MethodsNeutralising SARS-CoV-2 antibodies were measured after second vaccination in 64 rheumatic patients on methotrexate therapy, 31 of whom temporarily paused medication without a fixed regimen. The control group consisted of 21 AIRD patients without immunosuppressive medication.

ResultsMTX patients showed a significantly lower median antibody response compared to AIRD patients without immunosuppressive therapy (p< 0.001). Young age (<60 years) and MTX-hold after vaccination were found to be the main factors influencing antibody response after vaccination, while BMI or MTX dose demonstrated no effect. For patients taking MTX, age correlated negatively with immune response (r=-0.49; p<0.001) and all patients with antibody levels (14 %) below the cut-off were older than 60 years. Patients who held MTX during at least one vaccination showed significantly higher median neutralising antibody levels after second vaccination, compared to patients who continued MTX therapy during both vaccinations (68.82 %, 92.73 %, p=<0.001). This effect was particularly pronounced in patients older than 60 years (p=0.0016). The impact of the time period after vaccination was greater than of the time before vaccination with the critical cut-off being 10 days.

ConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age. Left Hemisphere Bias of NIH Stroke Scale is Most Severe for Middle Cerebral Artery Strokes Background and AimNIHSS score is higher for left versus right hemisphere strokes of equal volumes. However, differences in each vascular territory have not been evaluated yet. We hypothesized that left versus right differences are driven by the middle cerebral artery (MCA) territory, and there is no difference between hemispheres for other vascular territories.

MethodsThis study is based on data from 802 patients with evidence of acute or early subacute ischemic stroke. These patients had infarct restricted to one major arterial territory (MCA, n=437; PCA, n=209; ACA, n=21; vertebrobasilar, n=46) and received NIHSS and MRI at hospital admission. We examined differences in patients with left or right strokes regarding to lesion volume, NIHSS, and other covariates (age, sex, race). We used linear models to test the effects of these covariates on NIHSS. We looked at the whole sample as well as in the sample stratified by NIHSS (<=5 or >5) and by lesion location (MCA or PCA).

ResultsPatients with left MCA strokes had significantly higher NIHSS than those with right strokes. Only patients with MCA strokes showed NIHSS score affected by the hemisphere when controlling for stroke volume and patients age. This difference was driven by the more severe strokes (NIHSS>5). In addition, stroke volume and patients age significantly correlated with NIHSS.

ConclusionRight MCA infarcts are larger than left MCA infarcts associated with a given NIHSS score, after accounting for other significant associations, such as patients age. It is important to consider this systematic bias in the NIHSS when using the score for inclusion criteria for treatment or trials. Patients with right MCA stroke may be under-treated and left with disabling deficits that are not captured by the NIHSS. Effects of Glucagon-like Peptide-1 Receptor Agonists on Cardiovascular and Renal Outcomes: A Meta-analysis and Meta-regression Analysis AimsCardiovascular and renal effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been inconsistent in cardiovascular outcome trials, and factors associated with the efficacy of GLP-1RAs remain to be clarified. Here, we evaluate the cardiovascular and renal outcomes with GLP-1RAs and associations between these outcomes and HbA1c or weight reduction.

Materials and MethodsWe searched PubMed/MEDLINE, EMBASE, and CENTRAL for randomized, placebo-controlled trials of GLP1-RAs reporting major adverse cardiovascular events (MACE; a composite of cardiovascular mortality, stroke, and myocardial infarction) as the primary outcome. We conducted a meta-regression analysis of primary and secondary outcomes with HbA1c or weight reduction following a meta-analysis with a random-effects model for these outcomes.

ResultsWe extracted data of 60,800 individuals from eight eligible studies (ELIXA, LEADER, SUSTAIN-6, EXSCEL, HARMONY, PIONEER 6, REWIND, and AMPLITUDE-O). GLP-1RAs reduced MACE (hazard ratio [HR] 0.86; 95% CI: 0.80-0.93; P < 0.001) and secondary outcomes including the composite renal outcome (0.80; 0.73-0.87; P < 0.001). In meta-regression analysis, every 1% reduction in HbA1c was associated with 26% and 35% decreases in the logarithm of HR of MACE (P = 0.044; R2 = 0.65) and the composite renal outcome (P = 0.040; R2 = 0.85), respectively. On the contrary, weight reduction was not associated with any outcome, including MACE (P = 0.390).

ConclusionsThe reduction in HbA1c, but not body weight, is associated with cardiovascular and renal outcomes. The magnitude of HbA1c reduction can be a surrogate for cardiovascular and renal benefits of treatment with GLP-1RAs. How Informative Were Early SARS-CoV-2 Treatment and Prevention Trials? A longitudinal cohort analysis of trials registered on clinicaltrials.gov BackgroundEarly in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

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

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

ConclusionsLess than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic. Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis: a cohort study in UK Biobank ObjectivesTo evaluate the benefit of combining polygenic risk scores (PRS) with the QCancer-10 (colorectal cancer) non-genetic risk prediction model to identify those at highest risk of colorectal cancer (CRC).

DesignPopulation based cohort study. Six different PRS for CRC were developed (using LDpred2 PRS software, clumping and thresholding approaches, and genome-wide significant models). The top-performing genome-wide and GWAS-significant PRS were then combined with QCancer-10 and performance compared to QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women.

Setting and participantsUK Biobank Study. A total of 434587 individuals with complete genetic and QCancer-10 predictor data were included in the QCancer-10+PRS modelling cohorts.

Main outcome measuresPrediction of colorectal cancer diagnosis by genetic, non-genetic and combined risk models.

FindingsPRS derived using the LDpred2 program performed best, with an odds-ratio per standard deviation of 1.58, and top age- and sex-adjusted C-statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10+PRS models out-performed QCancer-10 alone. In men, the integrated LDpred2 (QCancer-10+LDP) model produced a C-statistic of 0.730 (0.720 to 0.741) and explained variation of 28.1% (26.3% to 30.0%), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9% to 23.1%) for QCancer-10 alone. Performance improvements in women were similar. In the top 20% of individuals at highest absolute risk, the sensitivity of QCancer-10+LDP models for predicting CRC diagnosis within 5 years was 47.6% in men and 42.5% in women, with respective 3.49-fold and 2.75-fold absolute increases in the top 5% of risk compared to average. Decision curve analysis showed that adding PRS to QCancer-10 improved net-benefit and interventions avoided, across most probability thresholds.

ConclusionsIntegrating PRS with QCancer-10 significantly improves risk prediction over QCancer-10 alone. Evaluation of risk stratified population screening using this approach is warranted.

Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIRisk stratification based on genetic or environmental risk factors could improve cancer screening outcomes
C_LIO_LINo previously published study has examined integrated models combining genome-wide PRS and non-genetic risk factors beyond age
C_LIO_LIQCancer-10 (colorectal cancer) is the top-performing non-genetic risk prediction model for CRC
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What this study addsO_LIAdding PRS to the QCancer-10 (colorectal cancer) risk prediction model improves performance and clinical benefit, with greatest gain from the LDpred2 genome-wide PRS, to a level that suggests utility in stratifying CRC screening and prevention
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