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SummaryBackgroundThe widespread use of the integrase strand transfer inhibitor (INSTI) dolutegravir (DTG) in first- and second-line antiretroviral therapy (ART) may facilitate emerging resistance. We combined data from HIV cohorts to examine patterns of drug resistance mutations (DRMs) and identify risk factors for DTG resistance.MethodsEight cohorts from Canada, Europe, and South Africa contributed data on individuals with genotypic resistance testing on DTG-based ART. Resistance levels were categorised using the Stanford algorithm. We identified risk factors for resistance using mixed-effects ordinal logistic regression models.ResultsWe included 750 people with genotypic resistance testing on DTG-based ART between 2013 and 2022. Most had HIV subtype B (N=444, 59·2%) and were treatment-experienced; 134 (17.9%) were on DTG dual and 19 (2.5%) on DTG monotherapy. INSTI DRMs were detected in 100 (13·3%) individuals; 21 (2·8%) had more than one mutation. Most (N=713, 95·1%) were susceptible to DTG, 8 (1·1%) had potential-low, 5 (0·7%) low, 18 (2·4%) intermediate and 6 (0·8%) high-level DTG resistance. The risk of DTG resistance was higher on DTG monotherapy (adjusted odds ratio (aOR) 37·25, 95% CI 11·17 to 124·2) and DTG lamivudine dual therapy (aOR 6·59, 95% CI 1·70 to 25·55) compared to combination ART, and higher in the presence of potential-low/low (aOR 4.62, 95% CI 1.24 to 17.2) or intermediate/high-level (aOR 7·01, 95% CI 2·52 to 19·48) nucleoside reverse transcriptase inhibitors (NRTI) resistance. Viral load on DTG showed a trend towards increased DTG resistance (aOR 1·42, 95% CI 0·92 to 2·19 per standard deviation of log10area under the viral load curve).InterpretationAmong people experiencing virological failure on DTG-based ART, INSTI DRMs were uncommon, and DTG resistance was rare. DTG monotherapy and NRTI resistance substantially increased the risk for DTG resistance, which is of concern, notably in resource-limited settings.FundingUS National Institutes of Health, Swiss National Science Foundation.Research in contextEvidence before this studyWe searched SCOPUS on 20 March 2023 for all publications from inception using the terms “dolutegravir” or “DTG”, “resistant” or “resistance”, and “HIV”. The available evidence on resistance evolution in people living with HIV (PLHIV) with virological failure on DTG-based ART is limited. Most studies assessed the efficacy of DTG-based regimens in clinical studies and reported drug resistance in individuals experiencing virological failure as a secondary objective or reported single or multiple cases of patients developing resistance on DTG-based ART. Clinical trials such as the NADIA trial showed a high degree of viral suppression even in people with NRTI resistance. Consequently, previous analyses included only a small number of people experiencing failure on DTG; the SINGLE trial with 39 people with virologic failure on DTG was the largest. The highest number of individuals with DTG resistance was nine study participants in the NADIA trial. There is evidence that DTG resistance in PLHIV on a DTG monotherapy may be more likely. Other studies suggest that HIV subtype and mutations acquired during a first-generation INSTI-based regimen might affect the risk of DTG resistance.Added value of this studyTo our knowledge, this is the first study systematically investigating resistance in PLHIV experiencing virologic failure on DTG-based ART using a multi-cohort collaboration design reflecting real-world routine care. We collected genotypic resistance tests and clinical data from eight observational HIV cohorts. This resulted in a large dataset of PLHIV experiencing virologic failure on a DTG regimen (over 700 individuals). It allowed a robust assessment of drug resistance mutations and risk factors for DTG resistance. Cross-resistance of first-generation INSTIs does not appear to explain the mutation patterns in HIV-infected individuals who experience virological failure on DTG-based ART regimens. PLHIV who received DTG monotherapy or DTG lamivudine dual therapy and those infected with non-B subtypes were more likely to develop resistance. Resistance to NRTIs was a major risk factor for DTG resistance, indicating that PLHIV receiving functional monotherapy are more likely to develop DTG resistance.Implications of all the available evidenceHIV drug resistance is a significant threat to the sustainability of current and future antiretroviral therapy for combating the ongoing HIV pandemic. Our collaborative analysis shows that cases of DTG resistance are so far rare but not negligible. Given the global DTG roll-out, this might lead to increased frequencies and transmission of DTG resistance, particularly in PLHIV with resistance to NRTIs. While the evidence regarding subtype differences is tentative, it indicates that non-B subtypes, which are most relevant for the global roll-out of DTG, might be associated with an increased risk of resistance.

Background: Over the past decade, antiretroviral therapy (ART) regimens that include integrase strand inhibitors (INSTIs) have become the most commonly used for people with HIV starting ART. Although trials and observational studies have compared virological failure on INSTI-based with other regimens, few data are available on mortality in people with HIV treated with INSTIs in routine care. Therefore, we compared all-cause mortality between different INSTI-based and non-INSTI-based regimens in adults with HIV starting ART from 2013 to 2018. Methods: This cohort study used data on people with HIV in Europe and North America from the Antiretroviral Therapy Cohort Collaboration (ART-CC) and UK Collaborative HIV Cohort (UK CHIC). We studied the most common third antiretroviral drugs (additional to nucleoside reverse transcriptase inhibitor) used from 2013 to 2018: rilpivirine, darunavir, raltegravir, elvitegravir, dolutegravir, efavirenz, and others. Adjusted hazard ratios (aHRs; adjusted for clinical and demographic characteristics, comorbid conditions, and other drugs in the regimen) for mortality were estimated using Cox models stratified by ART start year and cohort, with multiple imputation of missing data. Findings: 62 500 ART-naive people with HIV starting ART (12 422 [19·9%] women; median age 38 [IQR 30-48]) were included in the study. 1243 (2·0%) died during 188 952 person-years of follow-up (median 3·0 years [IQR 1·6-4·4]). There was little evidence that mortality rates differed between regimens with dolutegravir, elvitegravir, rilpivirine, darunavir, or efavirenz as the third drug. However, mortality was higher for raltegravir compared with dolutegravir (aHR 1·49, 95% CI 1·15-1·94), elvitegravir (1·86, 1·43-2·42), rilpivirine (1·99, 1·49-2·66), darunavir (1·62, 1·33-1·98), and efavirenz (2·12, 1·60-2·81) regimens. Results were similar for analyses making different assumptions about missing data and consistent across the time periods 2013-15 and 2016-18. Rates of virological suppression were higher for dolutegravir than other third drugs. Interpretation: This large study of patients starting ART since the introduction of INSTIs found little evidence that mortality rates differed between most first-line ART regimens; however, raltegravir-based regimens were associated with higher mortality. Although unmeasured confounding cannot be excluded as an explanation for our findings, virological benefits of first-line INSTIs-based ART might not translate to differences in mortality. We would like to thank our funders (US National Institute on Alcohol Abuse and Alcoholism and UK Medical Research Council) and all patients and the clinical teams associated with the participating cohort studies. The antiretroviral therapy cohort collaboration is funded by the US National Institute on Alcohol Abuse and Alcoholism (U01-AA026209). UK Collaborative HIV Cohort is funded by the UK Medical Research Council (grant numbers G0000199, G0600337, G0900274, and M004236/1). JACS is funded by National Institute for Health Research Senior Investigator award (NF-SI-0611-10168). AT is funded by the Wellcome Trust under a Sir Henry Wellcome Postdoctoral Fellowship (222770/Z/21/Z). Funding for the individual antiretroviral therapy cohort collaboration cohorts included in this analysis was from Alberta Health, Gilead, National Agency for AIDS Research (France REcherche Nord&Sud Sida-hiv Hépatites), the French Ministry of Health, the Austrian Agency for Health and Food Safety, Stichting HIV Monitoring, the Dutch Ministry of Health, Welfare and Sport through the Centre for Infectious Disease Control of the National Institute for Public Health and the Environment, the TP-HIV by the German Centre for Infection Research (NCT02149004), Instituto de Salud Carlos III (through the Red Temática de Investigación Cooperativa en Sida [RD06/006, RD12/0017/0018, and RD16/0002/0006]) as part of the Plan Nacional I + D + i. Other funders of the individual cohorts participating data for this analysis are ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional, ViiV Healthcare, Preben og Anna Simonsens Fond, ANRS-Maladies infectieuses émergentes, Institut National de la Santé et de la Recherche Médicale (INSERM), Bristol Myers Squibb, Janssen, Merck, the US National Institute on Alcohol Abuse and Alcoholism (U01-AA026230), the Spanish Ministry of Health, the Swiss National Science Foundation (grant 33CS30_134277), Centers for AIDS Research Network of Integrated Clinical Systems (1R24 AI067039-1, P30-AI-027757), the US Department of Veterans Affairs, the US National Institute on Alcohol Abuse and Alcoholism (U01-AA026224, U01-AA026209, U24-AA020794), the Veterans Health Administration Office of Research and Development, and the US National Institute of Allergy and Infectious Diseases (Tennessee Center for AIDS Research P30 AI110527). Sí

BackgroundEstimating real-world vaccine effectiveness is vital to assess the impact of the vaccination programme on the pandemic and inform the ongoing policy response. However, estimating vaccine effectiveness using observational data is inherently challenging because of the non-randomised design and the potential for unmeasured confounding.MethodsWe used a Regression Discontinuity Design (RDD) to estimate vaccine effectiveness against COVID-19 mortality in England, exploiting the discontinuity in vaccination rates resulting from the UK’s age-based vaccination priority groups. We used the fact that people aged 80 or over were prioritised for the vaccine roll-out in the UK to compare the risk of COVID-19 and non-COVID-19 death in people aged 75–79 and 80–84.FindingsThe prioritisation of vaccination of people aged 80 or above led to a large discrepancy in vaccination rates in people 80–84 compared to those 75–79 at the beginning of the vaccination campaign. We found a corresponding difference in COVID-19 mortality, but not in non-COVID-19 mortality, suggesting that our approach appropriately addresses the issue of unmeasured confounding factors. Our results suggest that the first vaccine dose reduced the risk of COVID-19 death by 52.6% (95% Cl 26.6–84.2) in those aged 80.InterpretationsOur results support existing evidence that a first dose of a COVID-19 vaccine has a strong protective effect against COVID-19 mortality in older adults. The RDD estimate of vaccine effectiveness is comparable to previously published studies using different methods, suggesting that unmeasured confounding factors are unlikely to substantially bias these studies.FundingOffice for National Statistics.Research in ContextEvidence before this studyWe searched PubMed for studies reporting on the ‘real-world’ effectiveness of the COVID-19 vaccination on risk of death using terms such as “COVID-19”, “vaccine effectiveness”, “mortality” and “death”. The relevant published studies on this topic report vaccine effectiveness estimates against risk of death ranging from 64.2% to 98.7%, for varying times post-vaccination. All of these are observational studies and therefore potentially subject to bias from unmeasured confounding. We found no studies that used a quasi-experimental method such as regression discontinuity design, which is not subject to bias from unmeasured confounding, to calculate the effectiveness of the COVID-19 vaccination on risk of COVID-19 death, or on other outcomes such as hospitalisation or infection.Added value of this studyThe estimates of vaccine effectiveness based on observational data may be biased by unmeasured confounding. This study uses a regression discontinuity design to estimate vaccine effectiveness, exploiting the fact that the vaccination campaign in the UK was rolled out following age-based priority groups. This enables the calculation of an unbiased estimate of the effectiveness of the COVID-19 vaccine against risk of death.The vaccine effectiveness estimate of 52.6% (95% Cl 26.6–84.2) is slightly lower but similar to previously published estimates, therefore suggesting that these estimates are not substantially affected by unmeasured confounding factors and confirming the effectiveness of the COVID-19 vaccine against risk of COVID-19 death.Implications of all the available evidenceObtaining an unbiased estimate of COVID-19 vaccine effectiveness is of vital importance in informing policy for lifting COVID-19 related measures. The regression discontinuity design provides confidence that the existing estimates from observational studies are unlikely to be substantially biased by unmeasured confounding.

ObjectiveTo estimate waning of covid-19 vaccine effectiveness over six months after second dose.DesignCohort study, approved by NHS England.SettingLinked primary care, hospital, and covid-19 records within the OpenSAFELY-TPP database.ParticipantsAdults without previous SARS-CoV-2 infection were eligible, excluding care home residents and healthcare professionals.ExposuresPeople who had received two doses of BNT162b2 or ChAdOx1 (administered during the national vaccine rollout) were compared with unvaccinated people during six consecutive comparison periods, each of four weeks.Main outcome measuresAdjusted hazard ratios for covid-19 related hospital admission, covid-19 related death, positive SARS-CoV-2 test, and non-covid-19 related death comparing vaccinated with unvaccinated people. Waning vaccine effectiveness was quantified as ratios of adjusted hazard ratios per four week period, separately for subgroups aged ≥65 years, 18-64 years and clinically vulnerable, 40-64 years, and 18-39 years.Results1 951 866 and 3 219 349 eligible adults received two doses of BNT162b2 and ChAdOx1, respectively, and 2 422 980 remained unvaccinated. Waning of vaccine effectiveness was estimated to be similar across outcomes and vaccine brands. In the ≥65 years subgroup, ratios of adjusted hazard ratios for covid-19 related hospital admission, covid-19 related death, and positive SARS-CoV-2 test ranged from 1.19 (95% confidence interval 1.14 to 1.24)to 1.34 (1.09 to 1.64) per four weeks. Despite waning vaccine effectiveness, rates of covid-19 related hospital admission and death were substantially lower among vaccinated than unvaccinated adults up to 26 weeks after the second dose, with estimated vaccine effectiveness ≥80% for BNT162b2, and ≥75% for ChAdOx1. By weeks 23-26, rates of positive SARS-CoV-2 test in vaccinated people were similar to or higher than in unvaccinated people (adjusted hazard ratios up to 1.72 (1.11 to 2.68) for BNT162b2 and 1.86 (1.79 to 1.93) for ChAdOx1).ConclusionsThe rate at which estimated vaccine effectiveness waned was consistent for covid-19 related hospital admission, covid-19 related death, and positive SARS-CoV-2 test and was similar across subgroups defined by age and clinical vulnerability. If sustained to outcomes of infection with the omicron variant and to booster vaccination, these findings will facilitate scheduling of booster vaccination.

Objective To compare the effectiveness of the BNT162b2 mRNA (Pfizer-BioNTech) and mRNA-1273 (Moderna) covid-19 vaccines during the booster programme in England. Design Matched cohort study, emulating a comparative effectiveness trial. Setting Linked primary care, hospital, and covid-19 surveillance records available within the OpenSAFELY-TPP research platform, covering a period when the SARS-CoV-2 delta and omicron variants were dominant. Participants 3 237 918 adults who received a booster dose of either vaccine between 29 October 2021 and 25 February 2022 as part of the national booster programme in England and who received a primary course of BNT162b2 or ChAdOx1. Intervention Vaccination with either BNT162b2 or mRNA-1273 as a booster vaccine dose. Main outcome measures Recorded SARS-CoV-2 positive test, covid-19 related hospital admission, covid-19 related death, and non-covid-19 related death at 20 weeks after receipt of the booster dose. Results 1 618 959 people were matched in each vaccine group, contributing a total 64 546 391 person weeks of follow-up. The 20 week risks per 1000 for a positive SARS-CoV-2 test were 164.2 (95% confidence interval 163.3 to 165.1) for BNT162b2 and 159.9 (159.0 to 160.8) for mRNA-1273; the hazard ratio comparing mRNA-1273 with BNT162b2 was 0.95 (95% confidence interval 0.95 to 0.96). The 20 week risks per 1000 for hospital admission with covid-19 were 0.75 (0.71 to 0.79) for BNT162b2 and 0.65 (0.61 to 0.69) for mRNA-1273; the hazard ratio was 0.89 (0.82 to 0.95). Covid-19 related deaths were rare: the 20 week risks per 1000 were 0.028 (0.021 to 0.037) for BNT162b2 and 0.024 (0.018 to 0.033) for mRNA-1273; hazard ratio 0.83 (0.58 to 1.19). Comparative effectiveness was generally similar within subgroups defined by the primary course vaccine brand, age, previous SARS-CoV-2 infection, and clinical vulnerability. Relative benefit was similar when vaccines were compared separately in the delta and omicron variant eras. Conclusions This matched observational study of adults estimated a modest benefit of booster vaccination with mRNA-1273 compared with BNT162b2 in preventing positive SARS-CoV-2 tests and hospital admission with covid-19 20 weeks after vaccination, during a period of delta followed by omicron variant dominance.

Background Unhealthy alcohol use among persons living with HIV (PLWH) is linked to significant morbidity and use of alcohol services may differ by HIV status. Our objective was to compare unhealthy alcohol use screening and treatment by HIV status in primary care. Methods Cohort study of adult (≥18 years) PLWH and HIV-uninfected participants frequency-matched 20:1 to PLWH by age, sex, and race/ethnicity who were enrolled in a large integrated healthcare system in the United States, with information ascertained from an electronic health record. Outcomes included unhealthy alcohol screening, prevalence, provider-delivered brief interventions and addiction specialty care visits. Other predictors included age, sex, race/ethnicity, neighborhood deprivation index, depression, smoking, substance use disorders, Charlson comorbidity index, prior outpatient visits, insurance type, and medical facility. Cox proportional hazards models were used to compute hazard ratios (HR) for the outcomes of time to unhealthy alcohol use screening and time to first addiction specialty visit. Poisson regression with robust standard errors were used to compute prevalence ratios (HR) for other outcomes. Results 11,235 PLWH and 227,320 HIV-uninfected participants were included. By 4.5 years after baseline, most participants were screened for unhealthy alcohol use (85% of PLWH and 93% of HIV-uninfected), but with a lower rate among PLWH (adjusted hazard ratio [HR] 0.84, 95% CI 0.82-0.85). PLWH were less likely, compared with HIV-uninfected participants, to report unhealthy drinking among those screened (adjusted PR 0.74, 95% CI 0.69-0.79), and among those who screened positive, less likely to receive brief interventions (adjusted PR 0.82, 95% CI 0.75-0.90), but more likely (adjusted HR 1.7, 95% CI 1.2-2.4) to have an addiction specialty visit within one year. Conclusions Unhealthy alcohol use was lower in PLWH, but the treatment approach by HIV status differed. PLWH reporting unhealthy alcohol use received less brief interventions and more addiction specialty care than HIV-uninfected participants.

Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage., Many published studies of the current SARS-CoV-2 pandemic have analysed data from non-representative samples from populations. Here, using UK BioBank samples, Gibran Hemani and colleagues discuss the potential for such studies to suffer from collider bias, and provide suggestions for optimising study design to account for this.

We describe our analyses of data from over 49.7 million people in England, representing near-complete coverage of the relevant population, to assess the risk of myocarditis and pericarditis following BNT162b2 and ChAdOx1 COVID-19 vaccination. A self-controlled case series (SCCS) design has previously reported increased risk of myocarditis after first ChAdOx1, BNT162b2, and mRNA-1273 dose and after second doses of mRNA COVID-19 vaccines in England. Here, we use a cohort design to estimate hazard ratios for hospitalised or fatal myocarditis/pericarditis after first and second doses of BNT162b2 and ChAdOx1 vaccinations. SCCS and cohort designs are subject to different assumptions and biases and therefore provide the opportunity for triangulation of evidence. In contrast to the findings from the SCCS approach previously reported for England, we found evidence for lower incidence of hospitalised or fatal myocarditis/pericarditis after first ChAdOx1 and BNT162b2 vaccination, as well as little evidence to suggest higher incidence of these events after second dose of either vaccination.

Background: Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a prothrombotic state, but long-term effects of COVID-19 on incidence of vascular diseases are unclear. Methods: We studied vascular diseases after COVID-19 diagnosis in population-wide anonymized linked English and Welsh electronic health records from January 1 to December 7, 2020. We estimated adjusted hazard ratios comparing the incidence of arterial thromboses and venous thromboembolic events (VTEs) after diagnosis of COVID-19 with the incidence in people without a COVID-19 diagnosis. We conducted subgroup analyses by COVID-19 severity, demographic characteristics, and previous history. Results: Among 48 million adults, 125 985 were hospitalized and 1 319 789 were not hospitalized within 28 days of COVID-19 diagnosis. In England, there were 260 279 first arterial thromboses and 59 421 first VTEs during 41.6 million person-years of follow-up. Adjusted hazard ratios for first arterial thrombosis after COVID-19 diagnosis compared with no COVID-19 diagnosis declined from 21.7 (95% CI, 21.0–22.4) in week 1 after COVID-19 diagnosis to 1.34 (95% CI, 1.21–1.48) during weeks 27 to 49. Adjusted hazard ratios for first VTE after COVID-19 diagnosis declined from 33.2 (95% CI, 31.3–35.2) in week 1 to 1.80 (95% CI, 1.50–2.17) during weeks 27 to 49. Adjusted hazard ratios were higher, for longer after diagnosis, after hospitalized versus nonhospitalized COVID-19, among Black or Asian versus White people, and among people without versus with a previous event. The estimated whole-population increases in risk of arterial thromboses and VTEs 49 weeks after COVID-19 diagnosis were 0.5% and 0.25%, respectively, corresponding to 7200 and 3500 additional events, respectively, after 1.4 million COVID-19 diagnoses. Conclusions: High relative incidence of vascular events soon after COVID-19 diagnosis declines more rapidly for arterial thromboses than VTEs. However, incidence remains elevated up to 49 weeks after COVID-19 diagnosis. These results support policies to prevent severe COVID-19 by means of COVID-19 vaccines, early review after discharge, risk factor control, and use of secondary preventive agents in high-risk patients.

Background Thromboses in unusual locations after the Coronavirus Disease 2019 (COVID-19) vaccine ChAdOx1-S have been reported, although their frequency with vaccines of different types is uncertain at a population level. The aim of this study was to estimate the population-level risks of hospitalised thrombocytopenia and major arterial and venous thromboses after COVID-19 vaccination. Methods and findings In this whole-population cohort study, we analysed linked electronic health records from adults living in England, from 8 December 2020 to 18 March 2021. We estimated incidence rates and hazard ratios (HRs) for major arterial, venous, and thrombocytopenic outcomes 1 to 28 and >28 days after first vaccination dose for ChAdOx1-S and BNT162b2 vaccines. Analyses were performed separately for ages 2, sex, ethnicity, and deprivation. We also prespecified adjustment for anticoagulant medication, combined oral contraceptive medication, hormone replacement therapy medication, history of pulmonary embolism or deep vein thrombosis, and history of coronavirus infection in analyses of venous thrombosis; and diabetes, hypertension, smoking, antiplatelet medication, blood pressure lowering medication, lipid lowering medication, anticoagulant medication, history of stroke, and history of myocardial infarction in analyses of arterial thromboses. We selected further covariates with backward selection. Of 46 million adults, 23 million (51%) were women; 39 million (84%) were The crude incidence rates (per 100,000 person-years) of all venous events were as follows: prevaccination, 140 [95% confidence interval (CI): 138 to 142]; ≤28 days post-ChAdOx1-S, 294 (281 to 307); >28 days post-ChAdOx1-S, 359 (338 to 382), ≤28 days post-BNT162b2-S, 241 (229 to 253); >28 days post-BNT162b2-S 277 (263 to 291). The crude incidence rates (per 100,000 person-years) of all arterial events were as follows: prevaccination, 546 (95% CI: 541 to 555); ≤28 days post-ChAdOx1-S, 1,211 (1,185 to 1,237); >28 days post-ChAdOx1-S, 1678 (1,630 to 1,726), ≤28 days post-BNT162b2-S, 1,242 (1,214 to 1,269); >28 days post-BNT162b2-S, 1,539 (1,507 to 1,572). Adjusted HRs (aHRs) 1 to 28 days after ChAdOx1-S, compared with unvaccinated rates, at ages Rates of intracranial venous thrombosis (ICVT) and of thrombocytopenia in adults aged The main limitations of the study are as follows: (i) it relies on the accuracy of coded healthcare data to identify exposures, covariates, and outcomes; (ii) the use of primary reason for hospital admission to measure outcome, which improves the positive predictive value but may lead to an underestimation of incidence; and (iii) potential unmeasured confounding. Conclusions In this study, we observed increases in rates of ICVT and thrombocytopenia after ChAdOx1-S vaccination in adults aged

OBJECTIVES Interest in the clinical usefulness of machine learning for risk prediction has bloomed recently. Cardiac surgery patients are at high risk of complications and therefore presurgical risk assessment is of crucial relevance. We aimed to compare the performance of machine learning algorithms over traditional logistic regression (LR) model to predict in-hospital mortality following cardiac surgery. METHODS A single-centre data set of prospectively collected information from patients undergoing adult cardiac surgery from 1996 to 2017 was split into 70% training set and 30% testing set. Prediction models were developed using neural network, random forest, naive Bayes and retrained LR based on features included in the EuroSCORE. Discrimination was assessed using area under the receiver operating characteristic curve, and calibration analysis was undertaken using the calibration belt method. Model calibration drift was assessed by comparing Goodness of fit χ2 statistics observed in 2 equal bins from the testing sample ordered by procedure date. RESULTS A total of 28 761 cardiac procedures were performed during the study period. The in-hospital mortality rate was 2.7%. Retrained LR [area under the receiver operating characteristic curve 0.80; 95% confidence interval (CI) 0.77–0.83] and random forest model (0.80; 95% CI 0.76–0.83) showed the best discrimination. All models showed significant miscalibration. Retrained LR proved to have the weakest calibration drift. CONCLUSIONS Our findings do not support the hypothesis that machine learning methods provide advantage over LR model in predicting operative mortality after cardiac surgery.

Background Previous trials suggest lower long-term risk of mortality after invasive rather than non-invasive management of patients with non-ST elevation myocardial infarction (NSTEMI), but the trials excluded very elderly patients. We aimed to estimate the effect of invasive versus non-invasive management within 3 days of peak troponin concentration on the survival of patients aged 80 years or older with NSTEMI. Methods Routine clinical data for this study were obtained from five collaborating hospitals hosting NIHR Biomedical Research Centres in the UK (all tertiary centres with emergency departments). Eligible patients were 80 years old or older when they underwent troponin measurements and were diagnosed with NSTEMI between 2010 (2008 for University College Hospital) and 2017. Propensity scores (patients' estimated probability of receiving invasive management) based on pretreatment variables were derived using logistic regression; patients with high probabilities of non-invasive or invasive management were excluded. Patients who died within 3 days of peak troponin concentration without receiving invasive management were assigned to the invasive or non-invasive management groups based on their propensity scores, to mitigate immortal time bias. We estimated mortality hazard ratios comparing invasive with non-invasive management, and compared the rate of hospital admissions for heart failure. Findings Of the 1976 patients with NSTEMI, 101 died within 3 days of their peak troponin concentration and 375 were excluded because of extreme propensity scores. The remaining 1500 patients had a median age of 86 (IQR 82–89) years of whom (845 [56%] received non-invasive management. During median follow-up of 3·0 (IQR 1·2–4·8) years, 613 (41%) patients died. The adjusted cumulative 5-year mortality was 36% in the invasive management group and 55% in the non-invasive management group (adjusted hazard ratio 0·68, 95% CI 0·55–0·84). Invasive management was associated with lower incidence of hospital admissions for heart failure (adjusted rate ratio compared with non-invasive management 0·67, 95% CI 0·48–0·93). Interpretation The survival advantage of invasive compared with non-invasive management appears to extend to patients with NSTEMI who are aged 80 years or older. Funding NIHR Imperial Biomedical Research Centre, as part of the NIHR Health Informatics Collaborative.

Meta-analyses based on systematic literature reviews are commonly used to obtain a quantitative summary of the available evidence on a given topic. However, the reliability of any meta-analysis is constrained by that of its constituent studies. One major limitation is the possibility of small-study effects, when estimates from smaller and larger studies differ systematically. Small-study effects may result from reporting biases (ie, publication bias), from inadequacies of the included studies that are related to study size, or from reasons unrelated to bias. We propose two estimators based on the median and mode to increase the reliability of findings in a meta-analysis by mitigating the influence of small-study effects. By re-examining data from published meta-analyses and by conducting a simulation study, we show that these estimators offer robustness to a range of plausible bias mechanisms, without making explicit modelling assumptions. They are also robust to outlying studies without explicitly removing such studies from the analysis. When meta-analyses are suspected to be at risk of bias because of small-study effects, we recommend reporting the mean, median and modal pooled estimates.

Supplemental Digital Content is available in the text, Introduction: HIV cohort data from high-income European countries were compared with the UNAIDS Spectrum modelling parameters for these same countries to validate mortality rates and excess mortality estimates for people living with HIV (PLHIV) on antiretroviral therapy (ART). Methods: Data from 2000 to 2015 were analysed from the Antiretroviral Therapy Cohort Collaboration (ART-CC) for Austria, Denmark, France, Italy, the Netherlands, Spain, and Switzerland. Flexible parametric models were used to compare all-cause mortality rates in the ART-CC and Spectrum. The percentage of AIDS-related deaths and excess mortality (both are the same within Spectrum) were compared, with excess mortality defined as that in excess of the general population mortality. Results: Analyses included 94 026 PLHIV with 585 784 person-years of follow-up, from which there were 5515 deaths. All-cause annual mortality rates in Spectrum for 2000–2003 were 0.0121, reducing to 0.0078 in 2012–2015, whilst the ART-CC's corresponding annual mortality rates were 0.0151 [95% confidence interval (95% CI): 0.0130–0.0171] reducing to 0.0049 (95% CI: 0.0039–0.0060). The percentage of AIDS-related deaths in Spectrum was 74.7% in 2000–2003, dropping to 43.6% in 2012–2015. In the ART-CC, AIDS-related mortality constitutes 45.3% (95% CI: 38.4–52.9%) of mortality in 2000–2003 and 26.7% (95% CI: 19–46%) between 2012 and 2015. Excess mortality in the ART-CC was broadly similar to the Spectrum estimates, dropping from 75.3% (95% CI: 60.3–95.2%) in 2000–2003 to 30.7% (95% CI: 25.5–63.7%) in 2012–2015. Conclusion: All-cause mortality assumptions for PLHIV on ART in high-income European settings should be adjusted in Spectrum to be higher in 2000–2003 and decline more quickly to levels currently captured for recent years.

ImportanceThe long-term effects of COVID-19 on the incidence of vascular diseases are unclear.ObjectiveTo quantify the association between time since diagnosis of COVID-19 and vascular disease, overall and by age, sex, ethnicity, and pre-existing disease.DesignCohort study based on population-wide linked electronic health records, with follow up from January 1st to December 7th 2020.Setting and participantsAdults registered with an NHS general practice in England or Wales and alive on January 1st 2020.ExposuresTime since diagnosis of COVID-19 (categorised as 0-6 days, 1-2 weeks, 3-4, 5-8, 9-12, 13-26 and 27-49 weeks since diagnosis), with and without hospitalisation within 28 days of diagnosis.Main outcomes and measuresPrimary outcomes were arterial thromboses (mainly acute myocardial infarction and ischaemic stroke) and venous thromboembolic events (VTE, mainly pulmonary embolism and lower limb deep vein thrombosis). We also studied other vascular events (transient ischaemic attack, haemorrhagic stroke, heart failure and angina). Hazard ratios were adjusted for demographic characteristics, previous disease diagnoses, comorbidities and medications.ResultsAmong 48 million adults, 130,930 were and 1,315,471 were not hospitalised within 28 days of COVID-19. In England, there were 259,742 first arterial thromboses and 60,066 first VTE during 41.6 million person-years follow-up. Adjusted hazard ratios (aHRs) for first arterial thrombosis compared with no COVID-19 declined rapidly from 21.7 (95% CI 21.0-22.4) to 3.87 (3.58-4.19) in weeks 1 and 2 after COVID-19, 2.80 (2.61-3.01) during weeks 3-4 then to 1.34 (1.21-1.48) during weeks 27-49. aHRs for first VTE declined from 33.2 (31.3-35.2) and 8.52 (7.59-9.58) in weeks 1 and 2 to 7.95 (7.28-8.68) and 4.26 (3.86-4.69) during weeks 3-4 and 5-8, then 2.20 (1.99-2.44) and 1.80 (1.50-2.17) during weeks 13-26 and 27-49 respectively. aHRs were higher, for longer after diagnosis, after hospitalised than non-hospitalised COVID-19. aHRs were also higher among people of Black and Asian than White ethnicity and among people without than with a previous event. Across the whole population estimated increases in risk of arterial thromboses and VTEs were 2.5% and 0.6% respectively 49 weeks after COVID-19, corresponding to 7,197 and 3,517 additional events respectively after 1.4 million COVID-19 diagnoses.Conclusions and RelevanceHigh rates of vascular disease early after COVID-19 diagnosis decline more rapidly for arterial thromboses than VTEs but rates remain elevated up to 49 weeks after COVID_19. These results support continued policies to avoid COVID-19 infection with effective COVID-19 vaccines and use of secondary preventive agents in high-risk patients.Key pointsQuestionIs COVID-19 associated with higher long-term incidence of vascular diseases?FindingsIn this cohort study of 48 million adults in England and Wales, COVID-19 was associated with higher incidence, that declined with time since diagnosis, of both arterial thromboses [week 1: adjusted HR [aHR] 21.7 (95% CI 21.0-22.4) weeks 27-49: aHR 1.34 (1.21-1.48)] and venous thromboembolism [week 1: aHR 33.2 (31.3-35.2), weeks 27–49 1.80 (1.50-2.17)]. aHRs were higher, for longer, after hospitalised than non-hospitalised COVID-19. The estimated excess number of arterial thromboses and venous thromboembolisms was 10,500.MeaningAvoidance of COVID-19 infection through vaccination, and use of secondary preventive agents after infection in high-risk patients, may reduce post-COVID-19 acute vascular diseases.

Background Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. Methods In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. Findings Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. Interpretation Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. Funding British Heart Foundation Data Science Centre, led by Health Data Research UK.

BackgroundUpdatable understanding of the onset and progression of individuals COVID-19 trajectories underpins pandemic mitigation efforts. In order to identify and characterize individual trajectories, we defined and validated ten COVID-19 phenotypes from linked electronic health records (EHR) on a nationwide scale using an extensible framework.MethodsCohort study of 56.6 million people in England alive on 23/01/2020, followed until 31/05/2021, using eight linked national datasets spanning COVID-19 testing, vaccination, primary & secondary care and death registrations data. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity using a combination of international clinical terminologies (e.g. SNOMED-CT, ICD-10) and bespoke data fields; positive test, primary care diagnosis, hospitalisation, critical care (four phenotypes), and death (three phenotypes). Using these phenotypes, we constructed patient trajectories illustrating the transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status.FindingsWe identified 3,469,528 infected individuals (6.1%) with 8,825,738 recorded COVID-19 phenotypes. Of these, 364,260 (11%) were hospitalised and 140,908 (4%) died. Of those hospitalised, 38,072 (10%) were admitted to intensive care (ICU), 54,026 (15%) received non-invasive ventilation and 21,404 (6%) invasive ventilation. Amongst hospitalised patients, first wave mortality (30%) was higher than the second (23%) in non-ICU settings, but remained unchanged for ICU patients. The highest mortality was for patients receiving critical care outside of ICU in wave 1 (51%). 13,083 (9%) COVID-19 related deaths occurred without diagnoses on the death certificate, but within 30 days of a positive test while 10,403 (7%) of cases were identified from mortality data alone with no prior phenotypes recorded. We observed longer patient trajectories in the second pandemic wave compared to the first.InterpretationOur analyses illustrate the wide spectrum of severity that COVID-19 displays and significant differences in incidence, survival and pathways across pandemic waves. We provide an adaptable framework to answer questions of clinical and policy relevance; new variant impact, booster dose efficacy and a way of maximising existing data to understand individuals progression through disease states.Research in ContextEvidence before the studyWe searched PubMed on October 14, 2021, for publications with the terms “COVID-19” or “SARS-CoV-2”, “severity”, and “electronic health records” or “EHR” without date or language restrictions. Multiple studies explore factors associated with severity of COVID-19 infection, and model predictions of outcome for hospitalised patients. However, most work to date focused on isolated facets of the healthcare system, such as primary or secondary care only, was conducted in subpopulations (e.g. hospitalised patients) of limited sample size, and often utilized dichotomised outcomes (e.g. mortality or hospitalisation) ignoring the full spectrum of disease. We identified no studies which comprehensively detailed severity of infections while describing disease severity across pandemic waves, vaccination status, and patient trajectories.Added value of this studyTo our knowledge, this is the first study providing a comprehensive view of COVID-19 across pandemic waves using national data and focusing on severity, vaccination, and patient trajectories. Drawing on linked electronic health record (EHR) data on a national scale (56.6 million people alive and registered with GP in England), we describe key demographic factors, frequency of comorbidities, impact of the two main waves in England, and effect of full vaccination on COVID-19 severities. Additionally, we identify and describe patient trajectory networks which illustrate the main transition pathways of COVID-19 patients in the healthcare system. Finally, we provide reproducible COVID-19 phenotyping algorithms reflecting clinically relevant stages of disease severity i.e. positive tests, primary care diagnoses, hospitalisation, critical care treatments (e.g. ventilatory support) and mortality.Implications of all the available evidenceThe COVID-19 phenotypes and trajectory analysis framework outlined produce a reproducible, extensible and repurposable means to generate national-scale data to support critical policy decision making. By modelling patient trajectories as a series of interactions with healthcare systems, and linking these to demographic and outcome data, we provide a means to identify and prioritise care pathways associated with adverse outcomes and highlight healthcare system ‘touch points’ which may act as tangible targets for intervention.

Background An Informatics Consult has been proposed in which clinicians request novel evidence from large scale health data resources, tailored to the treatment of a specific patient. However, the availability of such consultations is lacking. We seek to provide an Informatics Consult for a situation where a treatment indication and contraindication coexist in the same patient, i.e., anti-coagulation use for stroke prevention in a patient with both atrial fibrillation (AF) and liver cirrhosis. Methods We examined four sources of evidence for the effect of warfarin on stroke risk or all-cause mortality from: (1) randomised controlled trials (RCTs), (2) meta-analysis of prior observational studies, (3) trial emulation (using population electronic health records (N = 3,854,710) and (4) genetic evidence (Mendelian randomisation). We developed prototype forms to request an Informatics Consult and return of results in electronic health record systems. Results We found 0 RCT reports and 0 trials recruiting for patients with AF and cirrhosis. We found broad concordance across the three new sources of evidence we generated. Meta-analysis of prior observational studies showed that warfarin use was associated with lower stroke risk (hazard ratio [HR] = 0.71, CI 0.39–1.29). In a target trial emulation, warfarin was associated with lower all-cause mortality (HR = 0.61, CI 0.49–0.76) and ischaemic stroke (HR = 0.27, CI 0.08–0.91). Mendelian randomisation served as a drug target validation where we found that lower levels of vitamin K1 (warfarin is a vitamin K1 antagonist) are associated with lower stroke risk. A pilot survey with an independent sample of 34 clinicians revealed that 85% of clinicians found information on prognosis useful and that 79% thought that they should have access to the Informatics Consult as a service within their healthcare systems. We identified candidate steps for automation to scale evidence generation and to accelerate the return of results. Conclusion We performed a proof-of-concept Informatics Consult for evidence generation, which may inform treatment decisions in situations where there is dearth of randomised trials. Patients are surprised to know that their clinicians are currently not able to learn in clinic from data on ‘patients like me’. We identify the key challenges in offering such an Informatics Consult as a service.

Objective: To estimate pairwise associations between administration of tocilizumab, sarilumab and usual care or placebo with 28-day mortality, in COVID-19 patients receiving concomitant corticosteroids and non-invasive or mechanical ventilation, based on all available direct and indirect evidence. Methods: Eligible trials randomized hospitalized patients with COVID-19 that compared either interleukin-6 receptor antagonist with usual care or placebo in a recent prospective meta-analysis (27 trials, 10930 patients) or that directly compared tocilizumab with sarilumab. Data were restricted to patients receiving corticosteroids and either non-invasive or invasive ventilation at randomization. Pairwise associations between tocilizumab, sarilumab and usual care or placebo for all-cause mortality 28 days after randomization were estimated using a frequentist contrast-based network meta-analysis of odds ratios (ORs), implementing multivariate fixed-effects models that assume consistency between the direct and indirect evidence. Results: One trial (REMAP-CAP) was identified that directly compared tocilizumab with sarilumab and supplied results on all-cause mortality at 28-days. This network meta-analysis was based on 898 eligible patients (278 deaths) from REMAP-CAP and 3710 eligible patients from 18 trials (1278 deaths) from the prospective meta-analysis. Summary ORs were similar for tocilizumab [0.82 [0.71-0.95, P=0.008]] and sarilumab [0.80 [0.61-1.04, P=0.09]] compared with usual care or placebo. The summary OR for 28-day mortality comparing tocilizumab with sarilumab was 1.03 [95%CI 0.81-1.32, P=0.80]. The P value for the global test for inconsistency was 0.28. Conclusion: Administration of either tocilizumab or sarilumab was associated with lower 28-day all-cause mortality compared with usual care or placebo. The association is not dependent on the choice of interleukin-6 receptor antagonist.

BackgroundThromboses in unusual locations after the COVID-19 vaccine ChAdOx1-S have been reported. Better understanding of population-level thrombotic risks after COVID-19 vaccination is needed.MethodsWe analysed linked electronic health records from adults living in England, from 8th December 2020 to 18th March 2021. We estimated incidence rates and hazard ratios (HRs) for major arterial, venous and thrombocytopenic outcomes 1-28 and >28 days after first vaccination dose for ChAdOx1-S and BNT162b2 vaccines. Analyses were performed separately for ages ResultsOf 46,162,942 adults, 21,193,814 (46%) had their first vaccination during follow-up. Adjusted HRs 1-28 days after ChAdOx1-S, compared with unvaccinated rates, at ages Rates of intracranial venous thrombosis (ICVT) and thrombocytopenia in adults aged ConclusionsIncreases in ICVT and thrombocytopenia after ChAdOx1-S vaccination in adults aged

Ribavirin is the only available Lassa fever treatment. The rationale for using ribavirin is based on one clinical study conducted in the early 1980s. However, reanalysis of previous unpublished data reveals that ribavirin may actually be harmful in some Lassa fever patients. An urgent reevaluation of ribavirin is therefore needed.

ObjectiveTo compare the effectiveness of the BNT162b2 mRNA (Pfizer-BioNTech) and the ChAdOx1 (Oxford-AstraZeneca) covid-19 vaccines against infection and covid-19 disease in health and social care workers.DesignCohort study, emulating a comparative effectiveness trial, on behalf of NHS England.SettingLinked primary care, hospital, and covid-19 surveillance records available within the OpenSAFELY-TPP research platform, covering a period when the SARS-CoV-2 Alpha variant was dominant.Participants317 341 health and social care workers vaccinated between 4 January and 28 February 2021, registered with a general practice using the TPP SystmOne clinical information system in England, and not clinically extremely vulnerable.InterventionsVaccination with either BNT162b2 or ChAdOx1 administered as part of the national covid-19 vaccine roll-out.Main outcome measuresRecorded SARS-CoV-2 positive test, or covid-19 related attendance at an accident and emergency (A&E) department or hospital admission occurring within 20 weeks of receipt of the first vaccine dose.ResultsOver the duration of 118 771 person-years of follow-up there were 6962 positive SARS-CoV-2 tests, 282 covid-19 related A&E attendances, and 166 covid-19 related hospital admissions. The cumulative incidence of each outcome was similar for both vaccines during the first 20 weeks after vaccination. The cumulative incidence of recorded SARS-CoV-2 infection 20 weeks after first-dose vaccination with BNT162b2 was 21.7 per 1000 people (95% confidence interval 20.9 to 22.4) and with ChAdOx1 was 23.7 (21.8 to 25.6), representing a difference of 2.04 per 1000 people (0.04 to 4.04). The difference in the cumulative incidence per 1000 people of covid-19 related A&E attendance at 20 weeks was 0.06 per 1000 people (95% CI −0.31 to 0.43). For covid-19 related hospital admission, this difference was 0.11 per 1000 people (−0.22 to 0.44).ConclusionsIn this cohort of healthcare workers where we would not anticipate vaccine type to be related to health status, we found no substantial differences in the incidence of SARS-CoV-2 infection or covid-19 disease up to 20 weeks after vaccination. Incidence dropped sharply at 3-4 weeks after vaccination, and there were few covid-19 related hospital attendance and admission events after this period. This is in line with expected onset of vaccine induced immunity and suggests strong protection against Alpha variant covid-19 disease for both vaccines in this relatively young and healthy population of healthcare workers.

BackgroundMany studies have examined ‘non-specific’ vaccine effects on infant mortality: attention has been particularly drawn to diphtheria-tetanus-pertussis (DTP) vaccine, which has been proposed to be associated with an increased mortality risk. Both right and left censoring are common in such studies.MethodsWe conducted simulation studies examining right censoring (at measles vaccination) and left censoring (by excluding early follow-up) in a variety of scenarios in which confounding was and was not present. We estimated both unadjusted and adjusted hazard ratios (HRs), averaged across simulations.ResultsWe identified scenarios in which right-censoring at measles vaccination was informative and so introduced bias in the direction of a detrimental effect of DTP vaccine. In some, but not all, situations, adjusting for confounding by health status removed the bias caused by censoring. However, such adjustment will not always remove bias due to informative censoring: inverse probability weighting was required in one scenario. Bias due to left censoring arose when both health status and DTP vaccination were associated with mortality during the censored early follow-up and was in the direction of attenuating a beneficial effect of DTP on mortality. Such bias was more severe when the effect of DTP changed over time.ConclusionsEstimates of non-specific effects of vaccines may be biased by informative right or left censoring. Authors of studies estimating such effects should consider the potential for such bias and use appropriate statistical approaches to control for it. Such approaches require measurement of prognostic factors that predict censoring.

Rationale: Puberty may influence lung function, but the precise role of pubertal height growth in lung development is unclear. Objectives: To examine associations of timing of puberty and peak velocity of pubertal height growth with lung function in adolescence and early-adulthood. Methods: Longitudinal analyses of repeat height measurements from age 5-20 years for a British birth cohort with 4,772 males and 4,849 females were conducted to characterise height growth trajectories, and derive pubertal age and peak height velocity using the validated SuperImposition by Translation and Rotation (SITAR) model. Association of these estimates with pre-bronchodilator and post-bronchodilator spirometry measures: FEV1; FVC; FEV1/FVC; FEF25-75 at age 15 and 24 years were investigated using multivariable regression models adjusted for lung function at age 8 years, height and age at time of outcome measurements, and potential confounders. Measurements and Main Results: Later pubertal age and greater peak velocity were associated with higher FEV1 and FVC at 24 years in both sexes. A 1-year advanced pubertal age was associated with a 263 ml higher FVC (95% confidence interval: 167, 360) for males (n=567), 100 ml (50, 150) for females (n=990). A 1-cm/year increase in peak velocity was associated with 145 ml (56, 234) and 50 ml (2, 99) increase in FVC for males and females respectively. No associations were found with FEV1/FVC. Conclusions: Later onset and greater peak velocity of height growth in puberty are associated with increased FEV1 and FVC in young adults but there was no evidence of dysanapsis of pubertal lung growth.

ObjectivesDescribe a new England-wide electronic health record (EHR) resource enabling whole population research on Covid-19 and cardiovascular disease whilst ensuring data security and privacy and maintaining public trust.DesignCohort comprising linked person-level records from national healthcare settings for the English population accessible within NHS Digital’s new Trusted Research Environment.SettingEHRs from primary care, hospital episodes, death registry, Covid-19 laboratory test results and community dispensing data, with further enrichment planned from specialist intensive care, cardiovascular and Covid-19 vaccination data.Participants54.4 million people alive on 1st January 2020 and registered with an NHS general practitioner in England.Main measures of interestConfirmed and suspected Covid-19 diagnoses, exemplar cardiovascular conditions (incident stroke or transient ischaemic attack (TIA) and incident myocardial infarction (MI)) and all-cause mortality between 1st January and 31st October 2020.ResultsThe linked cohort includes over 96% of the English population. By combining person-level data across national healthcare settings, data on age, sex and ethnicity are complete for over 95% of the population. Among 53.2M people with no prior diagnosis of stroke/TIA, 98,721 had an incident stroke/TIA, of which 30% were recorded only in primary care and 4% only in death registry records. Among 53.1M people with no prior history of MI, 62,966 had an incident MI, of which 8% were recorded only in primary care and 12% only in death records. A total of 959,067 people had a confirmed or suspected Covid-19 diagnosis (714,162 in primary care data, 126,349 in hospital admission records, 776,503 in Covid-19 laboratory test data and 48,433 participants in death registry records). While 58% of these were recorded in both primary care and Covid-19 laboratory test data, 15% and 18% respectively were recorded in only one.ConclusionsThis population-wide resource demonstrates the importance of linking person-level data across health settings to maximize completeness of key characteristics and to ascertain cardiovascular events and Covid-19 diagnoses. Although established initially to support research on Covid-19 and cardiovascular disease to benefit clinical care and public health and to inform health care policy, it can broaden further to enable a very wide range of research.

IntroductionSmoking tobacco and unhealthy alcohol use may negatively influence HIV care continuum outcomes but have not been examined in combination.MethodsParticipants were people with HIV (PWH) in Kaiser Permanente Northern California. Predictors included smoking status and unhealthy alcohol use (exceeding daily and/or weekly limits) reported by patients during primary care screening (index date). Outcomes were based on not achieving the following steps in the care continuum: linkage to HIV care (≥1 visit within 90 days of newly identified HIV diagnosis), retention (2+ in-person visits, 60+ days apart) and HIV RNA control (ResultsThe overall sample (N = 8958) had a mean age of 48.0 years; was 91.3 % male; 54.0 % white, 17.6 % Latino, 15.1 % black, and 9.6 % other race/ethnicity. Smoking was associated with higher odds of not being linked to HIV care (OR = 1.60 [95 % CI 1.03−2.48]), not retained (OR = 1.30 [95 % CI 1.13−1.50]), and HIV RNA not in control (OR = 1.91 [95 % CI 1.60−2.27]). Alcohol measures were not independently associated with outcomes. The combination of unhealthy alcohol use and smoking (versus neither) was associated with higher odds of not being linked to care (OR = 2.83 [95 % CI 1.40−5.71]), although the interaction did not reach significance (p = 0.18).ConclusionsIn this large sample of PWH in an integrated health care system, smoking, both independently and in combination with unhealthy alcohol use, was associated with worse HIV care continuum outcomes.

Hongchao Pan (University of Oxford. Nuffield Department of Population Health. Medical Research Council Population Health Research Unit. Oxford, United Kingdom); Richard Peto (University of Oxford. Nuffield Department of Population Health. Medical Research Council Population Health Research Unit. Oxford, United Kingdom); Ana-Maria Henao-Restrepo (World Health Organization. Geneva, Switzerland); Marie-Pierre Preziosi (World Health Organization. Geneva, Switzerland); Vasee Sathiyamoorthy (World Health Organization. Geneva, Switzerland); Quarraisha Abdool Karim (Centre for the AIDS Programme of Research in South Africa. Durban, South Africa); Marissa M. Alejandria (University of the Philippines. National Institutes of Health. Institute of National Epidemiology. Manila, Philippines); Cesar Hernandez Garcia (Spanish Agency of Medicines and Medical Devices. Madrid, Spain / Hospital Clinico San Carlos. Madrid, Spain); Marie-Paule Kieny (Institut National de la Sante et de la Recherche Medicale. Paris, France); Reza Malekzadeh (Tehran University of Medical Sciences. Digestive Disease Research Institute. Tehran, Iran); Srinivas Murthy (University of British Columbia. Vancouver, Canada); K. Srinath Reddy (Public Health Foundation of India. New Delhi, India); Mirta Roses Periago (National Academy of Sciences of Buenos Aires. Buenos Aires, Argentina); Pierre Abi Hanna (Rafic Hariri University Hospital. Beirut, Lebanon); Florence Ader (Hospices Civils de Lyon. Lyon, France); Abdullah M. Al-Bader (Ministry of Health. Kuwait City, Kuwait); Almonther Alhasawi (Infectious Diseases Hospital. Kuwait City, Kuwait); Emma Allum (University of Bristol. Bristol, United Kingdom); Athari Alotaibi (Ministry for Preventive Health. Riyadh, Saudi Arabia); Carlos A. Alvarez-Moreno (Universidad Nacional de Colombia. Bogota, Colombia / Clinica Colsanitas. Bogota, Colombia); Sheila Appadoo (University of Bern. Bern, Switzerland); Abdullah Asiri (Ministry for Preventive Health. Riyadh, Saudi Arabia); Pal Aukrust (Oslo University Hospital. Oslo, Norway); Andreas Barratt-Due (Oslo University Hospital. Oslo, Norway); Samir Bellani (University of Bristol. Bristol, United Kingdom); Mattia Branca (University of Bern. Bern, Switzerland); Heike B.C. Cappel-Porter (University of Bristol. Bristol, United Kingdom); Nery Cerrato (Secretaria de Salud de Honduras. Tegucigalpa, Honduras); Ting S. Chow (Penang Hospital. Penang, Malaysia); Najada Como (University Hospital Center "Mother Teresa". Tirana, Albania); Joe Eustace (University College Cork. HRB Clinical Research Facility. Cork, Ireland); Patricia J. Garcia (Universidad Peruana Cayetano Heredia. Lima, Peru); Sheela Godbole (Indian Council of Medical Research. New Delhi, India / National AIDS Research Institute. Pune, Maharashtra, India); Eduardo Gotuzzo (Universidad Peruana Cayetano Heredia. Lima, Peru); Laimonas Griskevicius (Vilnius University Hospital Santaros Klinikos. Vilnius, Lithuania); Rasha Hamra (Ministry of Public Health. Beirut, Lebanon); Mariam Hassan (Shaukat Khanum Memorial Cancer Hospital and Research Centre. Lahore, Pakistan); Mohamed Hassany (National Hepatology and Tropical Medicine Research Institute. Cairo, Egypt); David Hutton (University of Bristol. Bristol, United Kingdom); Irmansyah Irmansyah (National Institute of Health Research and Development. Jakarta, Indonesia); Ligita Jancoriene (Vilnius University. Faculty of Medicine. Institute of Clinical Medicine. Vilnius, Lithuania); Jana Kirwan (University of Bristol. Bristol, United Kingdom); Suresh Kumar (Sungai Buloh Hospital. Selangor, Malaysia / Jalan Hospital. Selangor, Malaysia); Peter Lennon (Department of Health and Children. Dublin, Ireland); Gustavo Lopardo (Fundacion del Centro de Estudios Infectologicos. Buenos Aires, Argentina); Patrick Lydon (World Health Organization. Geneva, Switzerland); Nicola Magrini (Italian Medicines Agency. Rome, Italy); Teresa Maguire (Department of Health and Children. Dublin, Ireland); Suzana Manevska (Ministry of Health. Skopje, North Macedonia); Oriol Manuel (Lausanne University Hospital. Lausanne, Switzerland); Sibylle McGinty (University of Bern. Bern, Switzerland); Marco T. Medina (Universidad Nacional Autonoma de Honduras. Tegucigalpa, Honduras); Maria L. Mesa Rubio (Ministry of Health. Bogota, Colombia); Maria C. Miranda-Montoya (World Health Organization. Geneva, Switzerland); Jeremy Nel (University of the Witwatersrand. Johannesburg, South Africa); Estevao Portela Nunes (Fundacao Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil); Markus Perola (National Institute for Health and Welfare of Finland. Helsinki, Finland / University of Finland. Helsinki, Finland); Antonio Portoles (Universidade Complutense de Madrid. Madrid, Spain / Spanish Clinical Research Network. Madrid, Spain / Hospital Clinico San Carlos. Instituto de Investigacion Sanitaria San Carlos. Madrid, Spain); Menaldi R. Rasmin (Rumah Sakit Umum Pusat Persahabatan. Jakarta, Indonesia); Aun Raza (Shaukat Khanum Memorial Cancer Hospital and Research Centre. Lahore, Pakistan); Helen Rees (Wits Reproductive Health and HIV Institute. Johannesburg, South Africa); Paula P. S. Reges (Fundacao Oswaldo Cruz. Instituto Nacional de Infectologia Evandro Chagas. Rio de Janeiro, RJ, Brasil); Chris A. Rogers (University of Bristol. Bristol, United Kingdom); Kolawole Salami (World Health Organization. Geneva, Switzerland); Marina I. Salvadori (Public Health Agency of Canada. Ottawa, Canada); Narvina Sinani (National Agency for Medicines and Medical Devices. Tirana, Albania); Jonathan A. C. Sterne (University of Bristol. Bristol, United Kingdom); Milena Stevanovikj (University Clinic of Infectious Diseases and Febrile Conditions. Skopje, North Macedonia); Evelina Tacconelli (University of Verona. Verona, Italy); Kari A. O. Tikkinen (Helsinki University Hospital. Helsinki, Finland / South Karelian Central Hospital. Lappeenranta, Finland); Sven Trelle (University of Bern. Bern, Switzerland); Hala Zaid (Ministry of Health and Population. Cairo, Egypt); John-Arne Rottingen (Research Council of Norway. Oslo, Norway); Soumya Swaminathan (World Health Organization. Geneva, Switzerland).

ObjectiveTo monitor hospital activity for presentation, diagnosis and treatment of cardiovascular diseases during the COVID-19) pandemic to inform on indirect effects.MethodsRetrospective serial cross-sectional study in nine UK hospitals using hospital activity data from 28 October 2019 (pre-COVID-19) to 10 May 2020 (pre-easing of lockdown) and for the same weeks during 2018–2019. We analysed aggregate data for selected cardiovascular diseases before and during the epidemic. We produced an online visualisation tool to enable near real-time monitoring of trends.ResultsAcross nine hospitals, total admissions and emergency department (ED) attendances decreased after lockdown (23 March 2020) by 57.9% (57.1%–58.6%) and 52.9% (52.2%–53.5%), respectively, compared with the previous year. Activity for cardiac, cerebrovascular and other vascular conditions started to decline 1–2 weeks before lockdown and fell by 31%–88% after lockdown, with the greatest reductions observed for coronary artery bypass grafts, carotid endarterectomy, aortic aneurysm repair and peripheral arterial disease procedures. Compared with before the first UK COVID-19 (31 January 2020), activity declined across diseases and specialties between the first case and lockdown (total ED attendances relative reduction (RR) 0.94, 0.93–0.95; total hospital admissions RR 0.96, 0.95–0.97) and after lockdown (attendances RR 0.63, 0.62–0.64; admissions RR 0.59, 0.57–0.60). There was limited recovery towards usual levels of some activities from mid-April 2020.ConclusionsSubstantial reductions in total and cardiovascular activities are likely to contribute to a major burden of indirect effects of the pandemic, suggesting they should be monitored and mitigated urgently.