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Background In utero exposure to infections might set the stage for a chain of events leading to a wide spectrum of long-term health outcomes observed in children and adolescents. This proposal aims to investigate whether syphilis, zika, dengue and chikungunya during pregnancy can increase the risk of the offspring developing a non-infectious chronic condition during childhood and adolescence. Objectives 1) Estimate the risk of non-infectious chronic conditions associated to syphilis, zika, dengue and chikungunya during pregnancy and when appropriate, explore if the risk varies by timing during pregnancy when the infection is acquired (first, second or third trimester) and severity (such as severe or mild dengue); 2) Investigate whether in uterus exposure to maternal infection affects the growth pattern of children and adolescents; 3) Examine the extent to which the relationship between maternal infection and non-infectious chronic outcomes are mediated by intrauterine growth restriction and preterm birth. Methods We will compare health outcomes and growth trajectories of children and adolescents born to mothers with and without specific infections during pregnancy using conventional multivariable regression in the whole study population, in a within sibship design, using the subgroup of offspring with at least one sibling who is not exposed to the infection, and negative control outcome. Then we will decompose the direct and mediated effects (by preterm birth and small for gestational age) of maternal infection on chronic disorders. Results and Conclusions The results from this study will advance our understanding of the relationship between infections during pregnancy and chronic disorders, with widespread implications enabling targeting of critical points along the path from in utero exposure to outcomes to avoid or mitigate illness and disability over the life course.

BackgroundStroke prevention guidance for patients with atrial fibrillation (AF) uses evidence generated from randomised controlled trials (RCTs). However, applicability to patient groups excluded from trials remains unknown. Real-world patient data provide an opportunity to evaluate outcomes in a trial analogous population of direct oral anticoagulants (DOACs) users and in patients otherwise excluded from RCTs; however, there remains uncertainty on the validity of methods and suitability of the data. Successful reference trial emulation can support the generation of evidence around treatment effects in groups excluded or underrepresented in trials. We used linked United Kingdom primary care data to investigate whether we could emulate the pivotal ARISTOTLE trial (apixaban versus warfarin) and extend the analysis to investigate the impact of warfarin time in therapeutic range (TTR) on results.Methods and findingsPatients with AF in the UK Clinical Practice Research Datalink (CPRD Aurum) prescribed apixaban or warfarin from 1 January 2013 to 31 July 2019 were selected. ARISTOTLE eligibility criteria were applied to this population and matched to the RCT apixaban arm on baseline characteristics creating a trial-analogous apixaban cohort; this was propensity-score matched to warfarin users in the CPRD Aurum. ARISTOTLE outcomes were assessed using Cox proportional hazards regression stratified by prior warfarin exposure status during 2.5 years of patient follow-up and results benchmarked against the trial results before treatment effectiveness was further evaluated based on (warfarin) TTR. The dataset comprised 8,734 apixaban users and propensity-score matched 8,734 warfarin users. Results [hazard ratio (95% confidence interval)] confirmed apixaban noninferiority for stroke or systemic embolism (SE) [CPRD 0.98 (0.82,1.19) versus trial 0.79 (0.66,0.95)] and death from any cause [CPRD 1.03 (0.93,1.14) versus trial 0.89 (0.80,0.998)] but did not indicate apixaban superiority. Absolute event rates for stroke/SE were similar for apixaban in CPRD Aurum and ARISTOTLE (1.27%/year), whereas a lower event rate was observed for warfarin (CPRD Aurum 1.29%/year, ARISTOTLE 1.60%/year). Analysis by TTR suggested similar effectiveness of apixaban compared with poorly controlled warfarin (TTR < 0.75) for stroke/SE [0.91 (0.73, 1.14)], all-cause death [0.94 (0.84, 1.06)], and superiority for major bleeding [0.74 (0.63, 0.86)]. However, when compared with well-controlled warfarin (TTR ≥ 0.75), apixaban was associated with an increased hazard for all-cause death [1.20 (1.04, 1.37)], and there was no significant benefit for major bleeding [1.08 (0.90, 1.30)]. The main limitation of the study's methodology are the risk of residual confounding, channelling bias and attrition bias in the warfarin arm, and selection bias and misclassification in the analysis by TTR.ConclusionsAnalysis of noninterventional data generated results demonstrating noninferiority of apixaban versus warfarin consistent with prespecified benchmarking criteria. Unlike in ARISTOTLE, superiority of apixaban versus warfarin was not seen, possible due to the lower proportion of Asian patients and higher proportion of patients with well-controlled warfarin compared to ARISTOTLE. This methodological template can be used to investigate treatment effects of oral anticoagulants in patient groups excluded from or underrepresented in trials and provides a framework that can be adapted to investigate treatment effects for other conditions.

Introduction We undertook phenotypic characterization of early-onset and late-onset type 2 diabetes (T2D) in adult black African and white European populations with recently diagnosed T2D to explore ethnic differences in the manifestation of early-onset T2D.Research design and methods Using the Uganda Diabetes Phenotype study cohort of 500 adult Ugandans and the UK StartRight study cohort of 714 white Europeans with recently diagnosed islet autoantibody-negative T2D, we compared the phenotypic characteristics of participants with early-onset T2D (diagnosed at

Objectives Long-term sickness absence from employment has negative consequences for the economy and can lead to widened health inequalities. Sick notes (also called ‘fit notes’) are issued by general practitioners when a person cannot work for health reasons for more than 7 days. We quantified the sick note rate in people with evidence of COVID-19 in 2020, 2021 and 2022, as an indication of the burden for people recovering from COVID-19.Design Cohort study.Setting With National Health Service (NHS) England approval, we used routine clinical data (primary care, hospital and COVID-19 testing records) within the OpenSAFELY-TPP database.Participants People 18–64 years with a recorded positive test or diagnosis of COVID-19 in 2020 (n=365 421), 2021 (n=1 206 555) or 2022 (n=1 321 313); general population matched in age, sex and region in 2019 (n=3 140 326), 2020 (n=3 439 534), 2021 (n=4 571 469) and 2022 (n=4 818 870); people hospitalised with pneumonia in 2019 (n=29 673).Primary outcome measure Receipt of a sick note in primary care.Results Among people with a positive SARS-CoV-2 test or COVID-19 diagnosis, the sick note rate was 4.88 per 100 person-months (95% CI 4.83 to 4.93) in 2020, 2.66 (95% CI 2.64 to 2.67) in 2021 and 1.73 (95% CI 1.72 to 1.73) in 2022. Compared with the age, sex and region-matched general population, the adjusted HR for receipt of a sick note over the entire follow-up period (up to 10 months) was 4.07 (95% CI 4.02 to 4.12) in 2020 decreasing to 1.57 (95% CI 1.56 to 1.58) in 2022. The HR was highest in the first 30 days postdiagnosis in all years. Among people hospitalised with COVID-19, after adjustment, the sick note rate was lower than in people hospitalised with pneumonia.Conclusions Given the under-recording of postacute COVID-19-related symptoms, these findings contribute a valuable perspective on the long-term effects of COVID-19. Despite likely underestimation of the sick note rate, sick notes were issued more frequently to people with COVID-19 compared with those without, even in an era when most people are vaccinated. Most sick notes occurred in the first 30 days postdiagnosis, but the increased risk several months postdiagnosis may provide further evidence of the long-term impact.

Background Electronic health records (EHRs) have the potential to be used to produce detailed disease burden estimates. In this study we created disease estimates using national EHR for three high burden conditions, compared estimates between linked and unlinked datasets and produced stratified estimates by age, sex, ethnicity, socio-economic deprivation and geographical region. Methods EHRs containing primary care (Clinical Practice Research Datalink), secondary care (Hospital Episode Statistics) and mortality records (Office for National Statistics) were used. We used existing disease phenotyping algorithms to identify cases of cancer (breast, lung, colorectal and prostate), type 1 and 2 diabetes, and lower back pain. We calculated age-standardised incidence of first cancer, point prevalence for diabetes, and primary care consultation prevalence for low back pain. Results 7.2 million people contributing 45.3 million person-years of active follow-up between 2000–2014 were included. CPRD-HES combined and CPRD-HES-ONS combined lung and bowel cancer incidence estimates by sex were similar to cancer registry estimates. Linked CPRD-HES estimates for combined Type 1 and Type 2 diabetes were consistently higher than those of CPRD alone, with the difference steadily increasing over time from 0.26% (2.99% for CPRD-HES vs. 2.73 for CPRD) in 2002 to 0.58% (6.17% vs. 5.59) in 2013. Low back pain prevalence was highest in the most deprived quintile and when compared to the least deprived quintile the difference in prevalence increased over time between 2000 and 2013, with the largest difference of 27% (558.70 per 10,000 people vs 438.20) in 2013. Conclusions We use national EHRs to produce estimates of burden of disease to produce detailed estimates by deprivation, ethnicity and geographical region. National EHRs have the potential to improve disease burden estimates at a local and global level and may serve as more automated, timely and precise inputs for policy making and global burden of disease estimation.

Summary: Background: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. Methods: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. Findings: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5–179) and 100.5 in men (99.5–102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. Interpretation: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Background: Type 2 diabetes is common in relatively lean individuals in sub-Saharan Africa. It is unclear whether phenotypic differences exist between underweight and normal-weight African patients with type 2 diabetes. This study compared specific characteristics between underweight (body mass index

Summary: Background: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems. Methods: With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. Findings: The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72–5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37–30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. Interpretation: We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease. Funding: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073).

Abstract Adult-onset diabetes mellitus (here: aDM) is not a uniform disease entity. In European populations, five diabetes subgroups have been identified by cluster analysis using simple clinical variables; these may elucidate diabetes aetiology and disease prognosis. We aimed at reproducing these subgroups among Ghanaians with aDM, and establishing their importance for diabetic complications in different health system contexts. We used data of 541 Ghanaians with aDM (age: 25–70 years; male sex: 44%) from the multi-center, cross-sectional Research on Obesity and Diabetes among African Migrants (RODAM) Study. Adult-onset DM was defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L, documented use of glucose-lowering medication or self-reported diabetes, and age of onset ≥ 18 years. We derived subgroups by cluster analysis using (i) a previously published set of variables: age at diabetes onset, HbA1c, body mass index, HOMA-beta, HOMA-IR, positivity of glutamic acid decarboxylase autoantibodies (GAD65Ab), and (ii) Ghana-specific variables: age at onset, waist circumference, FPG, and fasting insulin. For each subgroup, we calculated the clinical, treatment-related and morphometric characteristics, and the proportions of objectively measured and self-reported diabetic complications. We reproduced the five subgroups: cluster 1 (obesity-related, 73%) and cluster 5 (insulin-resistant, 5%) with no dominant diabetic complication patterns; cluster 2 (age-related, 10%) characterized by the highest proportions of coronary artery disease (CAD, 18%) and stroke (13%); cluster 3 (autoimmune-related, 5%) showing the highest proportions of kidney dysfunction (40%) and peripheral artery disease (PAD, 14%); and cluster 4 (insulin-deficient, 7%) characterized by the highest proportion of retinopathy (14%). The second approach yielded four subgroups: obesity- and age-related (68%) characterized by the highest proportion of CAD (9%); body fat-related and insulin-resistant (18%) showing the highest proportions of PAD (6%) and stroke (5%); malnutrition-related (8%) exhibiting the lowest mean waist circumference and the highest proportion of retinopathy (20%); and ketosis-prone (6%) with the highest proportion of kidney dysfunction (30%) and urinary ketones (6%). With the same set of clinical variables, the previously published aDM subgroups can largely be reproduced by cluster analysis in this Ghanaian population. This method may generate in-depth understanding of the aetiology and prognosis of aDM, particularly when choosing variables that are clinically relevant for the target population.

Introduction 4.2 million individuals in the UK have type 2 diabetes, a known risk factor for dementia and mild cognitive impairment (MCI). Diabetes treatment may modify this association, but existing evidence is conflicting. We therefore aimed to assess the association between metformin therapy and risk of incident all-cause dementia or MCI compared with other oral glucose-lowering therapies (GLTs).Research design and methods We conducted an observational cohort study using the Clinical Practice Research Datalink among UK adults diagnosed with diabetes at ≥40 years between 1990 and 2019. We used an active comparator new user design to compare risks of dementia and MCI among individuals initially prescribed metformin versus an alternative oral GLT using Cox proportional hazards regression controlling for sociodemographic, lifestyle and clinical confounders. We assessed for interaction by age and sex. Sensitivity analyses included an as-treated analysis to mitigate potential exposure misclassification.Results We included 211 396 individuals (median age 63 years; 42.8% female), of whom 179 333 (84.8%) initiated on metformin therapy. Over median follow-up of 5.4 years, metformin use was associated with a lower risk of dementia (adjusted HR (aHR) 0.86 (95% CI 0.79 to 0.94)) and MCI (aHR 0.92 (95% CI 0.86 to 0.99)). Metformin users aged under 80 years had a lower dementia risk (aHR 0.77 (95% CI 0.68 to 0.85)), which was not observed for those aged ≥80 years (aHR 0.95 (95% CI 0.87 to 1.05)). There was no interaction with sex. The as-treated analysis showed a reduced effect size compared with the main analysis (aHR 0.90 (95% CI 0.83 to 0.98)).Conclusions Metformin use was associated with lower risks of incident dementia and MCI compared with alternative GLT among UK adults with diabetes. While our findings are consistent with a neuroprotective effect of metformin against dementia, further research is needed to reduce risks of confounding by indication and assess causality.

[This corrects the article DOI: 10.1371/journal.pgph.0002601.].

Background: We investigated perinatal outcomes among live births from international migrant and local-born mothers in a cohort of low-income individuals in Brazil. Methods: We linked nationwide birth registries to mortality records and socioeconomic data from the CIDACS Birth Cohort and studied singleton live births of women aged 10–49 years from 1st January 2011 to 31st December 2018. We used logistic regressions to investigate differences in antenatal care, adverse pregnancy outcomes, and neonatal (i.e., ≤28 days) mortality among international migrants compared to non-migrants in Brazil; and explored the interaction between migration, race/ethnicity and living in international border municipalities. Results: We studied 10,279,011 live births, of which 9469 (0.1 %) were born to international migrants. Migrant women were more likely than their Brazilian-born counterparts to have a previous foetal loss (ORadj: 1.16, 1.11–1.22), a delayed start of antenatal care (i.e., beyond 1st trimester) (1.22, 95%CI:1.16–1.28), a newborn who is large for gestational age (1.29, 1.22–1.36), or a newborn with congenital anomalies (1.37, 1.14–1.65). Conversely, migrant women were less likely to deliver prematurely (0.89, 0.82–0.95) or have a low birth weight infant (0.74, 0.68–0.81). There were no differences in neonatal mortality rates between migrants and non-migrants. Our analyses also showed that, when disparities in perinatal outcomes were present, disparities were mostly concentrated among indigenous mothers in international borders and among live births of Black mothers in non-borders. Conclusion: Although live births of international migrants generally have lower rates of adverse birth outcomes, our results suggest that indigenous and Black migrant mothers may face disproportionate barriers to accessing antenatal care.

Background: Non-invasive diabetes risk models are a cost-effective tool in large-scale population screening to identify those who need confirmation tests, especially in resource-limited settings. Aims: This study aimed to evaluate the ability of six non-invasive risk models (Cambridge, FINDRISC, Kuwaiti, Omani, Rotterdam, and SUNSET model) to identify screen-detected diabetes (defined by HbA1c) among Ghanaian migrants and non-migrants. Study design: A multicentered cross-sectional study. Methods: This analysis included 4843 Ghanaian migrants and non-migrants from the Research on Obesity and Diabetes among African Migrants (RODAM) Study. Model performance was assessed using the area under the receiver operating characteristic curves (AUC), Hosmer-Lemeshow statistics, and calibration plots. Results: All six models had acceptable discrimination (0.70 ≤ AUC

Background The long-term impact of elevated blood pressure on mortality outcomes has been recently revisited due to proposed changes in cut-offs for hypertension. This study aimed at assessing the association between high blood pressure levels and 10-year mortality using the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC-7) and the American College of Cardiology and the American Heart Association (ACC/AHA) 2017 blood pressure guidelines. Methods Data analysis of the PERU MIGRANT Study, a prospective ongoing cohort, was used. The outcome of interest was 10-year all-cause mortality, and exposures were blood pressure categories according to the JNC-7 and ACC/AHA 2017 guidelines. Log-rank test, Kaplan-Meier and Cox regression models were used to assess the associations of interest controlling for confounders. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated. Results A total of 976 records, mean age of 60.4 (SD: 11.4), 513 (52.6%) women, were analyzed. Hypertension prevalence at baseline almost doubled from 16.0% (95% CI 13.7%–18.4%) to 31.3% (95% CI 28.4%–34.3%), using the JNC-7 and ACC/AHA 2017 definitions, respectively. Sixty-three (6.4%) participants died during the 10-year follow-up, equating to a mortality rate of 3.6 (95% CI 2.4–4.7) per 1000 person-years. Using JNC-7, and compared to those with normal blood pressure, those with pre-hypertension and hypertension had 2.1-fold and 5.1-fold increased risk of death, respectively. Similar mortality effect sizes were estimated using ACC/AHA 2017 for stage-1 and stage-2 hypertension. Conclusions Blood pressure levels under two different definitions increased the risk of 10-year all-cause mortality. Hypertension prevalence doubled using ACC/AHA 2017 compared to JNC-7. The choice of blood pressure cut-offs to classify hypertension categories need to be balanced against the patients benefit and the capacities of the health system to adequately handle a large proportion of new patients.

Abstract Objective To investigate whether herpes simplex virus type 1 (HSV‐1) infection was associated with rates of cognitive decline or whole brain atrophy among individuals from the Dominantly Inherited Alzheimer Network (DIAN). Methods Among two subsets of the DIAN cohort (age range 19.6–66.6 years; median follow‐up 3.0 years) we examined (i) rate of cognitive decline (N = 164) using change in mini‐mental state examination (MMSE) score, (ii) rate of whole brain atrophy (N = 149), derived from serial MR imaging, calculated using the boundary shift integral (BSI) method. HSV‐1 antibodies were assayed in baseline sera collected from 2009–2015. Linear mixed‐effects models were used to compare outcomes by HSV‐1 seropositivity and high HSV‐1 IgG titres/IgM status. Results There was no association between baseline HSV‐1 seropositivity and rates of cognitive decline or whole brain atrophy. Having high HSV‐1 IgG titres/IgM was associated with a slightly greater decline in MMSE points per year (difference in slope − 0.365, 95% CI: −0.958 to −0.072), but not with rate of whole brain atrophy. Symptomatic mutation carriers declined fastest on both MMSE and BSI measures, however, this was not influenced by HSV‐1. Among asymptomatic mutation carriers, rates of decline on MMSE and BSI were slightly greater among those who were HSV‐1 seronegative. Among mutation‐negative individuals, no differences were seen by HSV‐1. Stratifying by APOE4 status yielded inconsistent results. Interpretation We found no evidence for a major role of HSV‐1, measured by serum antibodies, in cognitive decline or whole brain atrophy among individuals at high risk of early‐onset AD.

Abstract While there is growing evidence of associations between infections and dementia risk, associations with cognitive impairment and potential structural correlates of cognitive decline remain underexplored. Here we aimed to investigate the presence and nature of any associations between common infections, cognitive decline and neuroimaging parameters. The UK Biobank is a large volunteer cohort (over 500,000 participants recruited aged 40–69) with linkage to primary and secondary care records. Using linear mixed effects models, we compared participants with and without a history of infections for changes in cognitive function during follow-up. Linear regression models were used to investigate the association of infections with hippocampal and white matter hyperintensity (WMH) volume. 16,728 participants (median age 56.0 years [IQR 50.0–61.0]; 51.3% women) had baseline and follow-up cognitive measures. We found no evidence of an association between the presence of infection diagnoses and cognitive decline for mean correct response time (slope difference [infections versus no infections] = 0.40 ms, 95% CI: −0.17–0.96 per year), visual memory (slope difference 0.0004 log errors per year, 95% CI: −0.003–0.004, fluid intelligence (slope difference 0.007, 95% CI: −0.010–0.023) and prospective memory (OR 0.88, 95% CI: 0.68–1.14). No evidence of an association was found between infection site, setting or frequency and cognitive decline except for small associations on the visual memory test. We found no association between infections and hippocampal or WMH volume. Limitations of our study include selection bias, potential practice effects and the relatively young age of our cohort. Our findings do not support a major role for common midlife infections in contributing to cognitive decline for this cohort. Further research is warranted in individuals with more severe infections, for infections occurring later in life.

Background: Five-alpha reductase inhibitors (5ARIs) are used in the management of benign prostatic hyperplasia (BPH). 5ARIs prevent the conversion of testosterone to dihydrotestosterone, which is important in prostate development. It has been suggested that 5ARIs can be used a chemopreventative agent for prostate cancer. The aim of this study was to assess the risk of prostate cancer associated with 5ARI use among men with BPH. Methods: Using Clinical Practice Research Datalink (CPRD) from 1992 to 2011 in UK, prostate cancer risk was retrospectively compared in men with a new diagnosis of BPH, with no history of prostate cancer who were treated with 5ARIs, to men treated with alpha blockers (ABs) and those given no pharmacological treatment. Incidence rate of prostate cancer was calculated by treatment group; the association between BPH treatment group and prostate cancer was estimated by a multivariate Cox model. Results: 77,494 men with newly diagnosed BPH were included. The crude incidence rate of prostate cancer was 892.4 cases per 100,000 person-years amongst those treated with 5ARIs, compared with 1209.0 and 1542.9 in those treated with ABs and untreated individuals, respectively. The HR adjusted for potential confounders was 0.79 (0.72-0.86) for 5ARI vs ABs and 0.72 (0.66-0.79) for 5ARI vs untreated. After excluding the first year after BPH diagnosis, adjusted HRs attenuated to 0.87 (0.79-0.97) for 5ARI vs ABs and 0.97 (0.87-1.08) for 5ARI vs untreated. Conclusion: Among men diagnosed with BPH, we found evidence of lower risks of subsequent prostate cancer in those treated with 5ARIs, but this appeared to be driven by cases diagnosed within a year of BPH, possibly reflecting prevalent prostate cancers that were initially misdiagnosed. After excluding the first year after BPH diagnosis, there was little evidence of a reduced prostate cancer risk in those taking 5ARIs.

Summary: Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding: LSHTM COVID-19 Response Grant (DONAT15912).

Abstract Background While the vaccines against COVID-19 are highly effective, COVID-19 vaccine breakthrough is possible despite being fully vaccinated. With SARS-CoV-2 variants still circulating, describing the characteristics of individuals who have experienced COVID-19 vaccine breakthroughs could be hugely important in helping to determine who may be at greatest risk. Methods With the approval of NHS England, we conducted a retrospective cohort study using routine clinical data from the OpenSAFELY-TPP database of fully vaccinated individuals, linked to secondary care and death registry data and described the characteristics of those experiencing COVID-19 vaccine breakthroughs. Results As of 1st November 2021, a total of 15,501,550 individuals were identified as being fully vaccinated against COVID-19, with a median follow-up time of 149 days (IQR: ​107–179). From within this population, a total of 579,780 (

Abstract Objective This study aims to describe clinical findings and determine the medium-term survival of congenital zika syndrome (CZS) suspected cases. Methods A retrospective cohort study using routine register-based linked data. It included all suspected cases of CZS born in Brazil from January 1, 2015, to December 31, 2018, and followed up from birth until death, 36 months, or December 31, 2018, whichever came first. Latent class analysis was used to cluster unconfirmed cases into classes with similar combinations of anthropometry at birth, imaging findings, maternally reported rash, region, and year of birth. Kaplan–Meier curves were plotted, and Cox proportional hazards models were fitted to determine mortality up to 36 months. Results We followed 11,850 suspected cases of CZS, of which 28.3% were confirmed, 9.3% inconclusive and 62.4% unconfirmed. Confirmed cases had almost two times higher mortality when compared with unconfirmed cases. Among unconfirmed cases, we identified three distinct clusters with different mortality trajectories. The highest mortality risk was observed in those with abnormal imaging findings compatible with congenital infections (HR = 12.6; IC95%8.8–18.0) and other abnormalities (HR = 11.6; IC95%8.6–15.6) compared with those with normal imaging findings. The risk was high in those with severe microcephaly (HR = 8.2; IC95%6.4–10.6) and macrocephaly (HR = 6.6; IC95%4.5–9.7) compared with normal head size. Conclusion Abnormal imaging and head circumference appear to be the main drivers of the increased mortality among suspected cases of CZS. We suggest identifying children who are more likely to die and have a greater need to optimise interventions and resource allocation regardless of the final diagnoses.

BackgroundCongenital syphilis (CS) is a major and avoidable cause of neonatal death worldwide. In this study, we aimed to estimate excess all-cause mortality in children under 5 years with CS compared to those without CS.Methods and findingsIn this population-based cohort study, we used linked, routinely collected data from Brazil from January 2011 to December 2017. Cox survival models were adjusted for maternal region of residence, maternal age, education, material status, self-declared race and newborn sex, and year of birth and stratified according to maternal treatment status, non-treponemal titers and presence of signs and symptoms at birth. Over 7 years, a total of 20 057 013 live-born children followed up (through linkage) to 5 years of age, 93 525 were registered with CS, and 2 476 died. The all-cause mortality rate in the CS group was 7·84/1 000 person-years compared with 2·92/1 000 person-years in children without CS, crude hazard ratio (HR) = 2·41 (95% CI 2·31 to 2·50). In the fully adjusted model, the highest under-five mortality risk was observed among children with CS from untreated mothers HR = 2·82 (95% CI 2·63 to 3·02), infants with non-treponemal titer higher than 1:64 HR = 8·87 (95% CI 7·70 to 10·22), and children with signs and symptoms at birth HR = 7·10 (95% CI 6·60 to 7·63). Among children registered with CS, CS was recorded as the underlying cause of death in 33% (495/1 496) of neonatal, 11% (85/770) of postneonatal, and 2·9% (6/210) of children 1 year of age. The main limitations of this study were the use of a secondary database without additional clinical information and the potential misclassification of exposure status.ConclusionsThis study showed an increased mortality risk among children with CS that goes beyond the first year of life. It also reinforces the importance of maternal treatment that infant non-treponemal titers and the presence of signs and symptoms of CS at birth are strongly associated with subsequent mortality.Trial registrationObservational study.

Summary: Background: While cardiovascular disease (CVD) is a risk factor for severe COVID-19, the association between predicted cardiovascular risk and severe COVID-19 among people without diagnosed CVD is unclear. Methods: We carried out historical, population-based cohort studies among adults aged 40–84 years in England using linked data from the Clinical Practice Research Datalink. Individuals were categorized into: existing CVD, raised cardiovascular risk (defined using QRISK3 score ≥10%) and low risk (QRISK3 score

Summary: Background: To understand if migrants living in poverty in low and middle-income countries (LMICs) have mortality advantages over the non-migrant population, we investigated mortality risk patterns among internal and international migrants in Brazil over their life course. Methods: We linked socio-economic and mortality data from 1st January 2011 to 31st December 2018 in the 100 Million Brazilian Cohort and calculated all-cause and cause-specific age-standardised mortality rates according to individuals' migration status for men and women. Using Cox regression models, we estimated the age- and sex-adjusted mortality hazard ratios (HR) for internal migrants (i.e., Brazilian-born individuals living in a different Brazilian state than their birth) compared to Brazilian-born non-migrants; and for international migrants (i.e., people born in another country) compared to Brazilian-born individuals. Findings: The study followed up 45,051,476 individuals, of whom 6,057,814 were internal migrants, and 277,230 were international migrants. Internal migrants had similar all-cause mortality compared to Brazilian non-migrants (aHR = 0.99, 95% CI = 0.98–0.99), marginally higher mortality for ischaemic heart diseases (aHR = 1.04, 95% CI = 1.03–1.05) and higher for stroke (aHR = 1.11, 95% CI = 1.09–1.13). Compared to Brazilian-born individuals, international migrants had 18% lower all-cause mortality (aHR = 0.82, 95% CI = 0.80–0.84), with up to 50% lower mortality from interpersonal violence among men (aHR = 0.50, 95% CI = 0.40–0.64), but higher mortality from avoidable causes related to maternal health (aHR = 2.17, 95% CI = 1.17–4.05). Interpretation: Although internal migrants had similar all-cause mortality, international migrants had lower all-cause mortality compared to non-migrants. Further investigations using intersectional approaches are warranted to understand the marked variations by migration status, age, and sex for specific causes of death, such as elevated maternal mortality and male lower interpersonal violence-related mortality among international migrants. Funding: The Wellcome Trust.

Abstract Objective To investigate whether herpes zoster (HZ) was associated with subsequent increased risk of dementia diagnosis. Methods We conducted a historical cohort study using primary care electronic health records from the Clinical Practice Research Datalink in the United Kingdom. Individuals with incident HZ aged ≥40 years from 2000 to 2017 were matched with up to four individuals without HZ by age, sex, primary care practise and calendar time. The primary outcome was a new diagnosis of all‐cause dementia. We used the Cox proportional hazards regression adjusting for demographic, lifestyle and clinical confounders to assess any association between HZ and dementia. We investigated interactions with sex, frailty index and antiviral treatment and conducted various sensitivity analyses. Results The cohort comprised 177,144 individuals with HZ and 706,901 matched unexposed individuals (median age 65 years (IQR 55.1–75.0), 40% male) followed for a median duration of 4.6 years (IQR 2.0–8.1). In total, 26,585 (3%) patients had an incident dementia diagnosis recorded and 113,056 patients died (12.8%). HZ was associated with a small reduction in dementia diagnosis (adjusted HR 0.92 (95% CI 0.89–0.95)), occurring predominantly in frail individuals and females. For patients who were fit (578,115, 65%), no association was seen (adjusted HR 0.97, 95% CI 0.92–1.02). There was no association between HZ and a composite outcome of dementia or death (adjusted HR 1.00, 95% CI 0.99–1.02). Dementia risk did not vary by prescription of antiviral agents. Sensitivity analyses showed consistent results. Interpretation HZ was not associated with increased dementia diagnosis in a UK primary care‐based cohort.

Abstract Background Obtaining accurate estimates of the risk of COVID-19-related death in the general population is challenging in the context of changing levels of circulating infection. Methods We propose a modelling approach to predict 28-day COVID-19-related death which explicitly accounts for COVID-19 infection prevalence using a series of sub-studies from new landmark times incorporating time-updating proxy measures of COVID-19 infection prevalence. This was compared with an approach ignoring infection prevalence. The target population was adults registered at a general practice in England in March 2020. The outcome was 28-day COVID-19-related death. Predictors included demographic characteristics and comorbidities. Three proxies of local infection prevalence were used: model-based estimates, rate of COVID-19-related attendances in emergency care, and rate of suspected COVID-19 cases in primary care. We used data within the TPP SystmOne electronic health record system linked to Office for National Statistics mortality data, using the OpenSAFELY platform, working on behalf of NHS England. Prediction models were developed in case-cohort samples with a 100-day follow-up. Validation was undertaken in 28-day cohorts from the target population. We considered predictive performance (discrimination and calibration) in geographical and temporal subsets of data not used in developing the risk prediction models. Simple models were contrasted to models including a full range of predictors. Results Prediction models were developed on 11,972,947 individuals, of whom 7999 experienced COVID-19-related death. All models discriminated well between individuals who did and did not experience the outcome, including simple models adjusting only for basic demographics and number of comorbidities: C-statistics 0.92–0.94. However, absolute risk estimates were substantially miscalibrated when infection prevalence was not explicitly modelled. Conclusions Our proposed models allow absolute risk estimation in the context of changing infection prevalence but predictive performance is sensitive to the proxy for infection prevalence. Simple models can provide excellent discrimination and may simplify implementation of risk prediction tools.

BackgroundChildren with congenital Zika syndrome (CZS) have severe damage to the peripheral and central nervous system (CNS), greatly increasing the risk of death. However, there is no information on the sequence of the underlying, intermediate, immediate, and contributing causes of deaths among these children. The aims of this study are describe the sequence of events leading to death of children with CZS up to 36 months of age and their probability of dying from a given cause, 2015 to 2018.Methods and findingsIn a population-based study, we linked administrative data on live births, deaths, and cases of children with CZS from the SINASC (Live Birth Information System), the SIM (Mortality Information System), and the RESP (Public Health Event Records), respectively. Confirmed and probable cases of CZS were those that met the criteria established by the Brazilian Ministry of Health. The information on causes of death was collected from death certificates (DCs) using the World Health Organization (WHO) DC template. We estimated proportional mortality (PM%) among children with CZS and among children with non-Zika CNS congenital anomalies (CA) by 36 months of age and proportional mortality ratio by cause (PMRc). A total of 403 children with confirmed and probable CZS who died up to 36 months of age were included in the study; 81.9% were younger than 12 months of age. Multiple congenital malformations not classified elsewhere, and septicemia unspecified, with 18 (PM = 4.5%) and 17 (PM = 4.2%) deaths, respectively, were the most attested underlying causes of death. Unspecified septicemia (29 deaths and PM = 11.2%) and newborn respiratory failure (40 deaths and PM = 12.1%) were, respectively, the predominant intermediate and immediate causes of death. Fetuses and newborns affected by the mother's infectious and parasitic diseases, unspecified cerebral palsy, and unspecified severe protein-caloric malnutrition were the underlying causes with the greatest probability of death in children with CZS (PMRc from 10.0 to 17.0) when compared to the group born with non-Zika CNS anomalies. Among the intermediate and immediate causes of death, pneumonitis due to food or vomiting and unspecified seizures (PMRc = 9.5, each) and unspecified bronchopneumonia (PMRc = 5.0) were notable. As contributing causes, fetus and newborn affected by the mother's infectious and parasitic diseases (PMRc = 7.3), unspecified cerebral palsy, and newborn seizures (PMRc = 4.5, each) were more likely to lead to death in children with CZS than in the comparison group. The main limitations of this study were the use of a secondary database without additional clinical information and potential misclassification of cases and controls.ConclusionThe sequence of causes and circumstances involved in the deaths of the children with CZS highlights the greater vulnerability of these children to infectious and respiratory conditions compared to children with abnormalities of the CNS not related to Zika.

Introduction The impact of long COVID on health-related quality of-life (HRQoL) and productivity is not currently known. It is important to understand who is worst affected by long COVID and the cost to the National Health Service (NHS) and society, so that strategies like booster vaccines can be prioritised to the right people. OpenPROMPT aims to understand the impact of long COVID on HRQoL in adults attending English primary care.Methods and analysis We will ask people to participate in this cohort study through a smartphone app (Airmid), and completing a series of questionnaires held within the app. Questionnaires will ask about HRQoL, productivity and symptoms of long COVID. Participants will be asked to fill in the questionnaires once a month, for 90 days. Questionnaire responses will be linked, where possible, to participants’ existing health records from primary care, secondary care, and COVID testing and vaccination data. Analysis will take place using the OpenSAFELY data platform and will estimate the impact of long COVID on HRQoL, productivity and cost to the NHS.Ethics and dissemination The Proportionate Review Sub-Committee of the South Central—Berkshire B Research Ethics Committee has reviewed and approved the study and have agreed that we can ask people to take part (22/SC/0198). Our results will provide information to support long-term care, and make recommendations for prevention of long COVID in the future.Trial registration number NCT05552612.

The COVID-19 pandemic has brought about valuable insights regarding models, data, and experiments. In this narrative review, we summarised the existing literature on these three themes, exploring the challenges of providing forecasts, the requirement for real-time linkage of health-related datasets, and the role of 'experimentation' in evaluating interventions. This literature review encourages us to broaden our perspective for the future, acknowledging the significance of investing in models, data, and experimentation, but also to invest in areas that are conceptually more abstract: the value of 'team science', the need for public trust in science, and in establishing processes for using science in policy. Policy-makers rely on model forecasts early in a pandemic when there is little data, and it is vital to communicate the assumptions, limitations, and uncertainties (theme 1). Linked routine data can provide critical information, for example, in establishing risk factors for adverse outcomes but are often not available quickly enough to make a real-time impact. The interoperability of data resources internationally is required to facilitate sharing across jurisdictions (theme 2). Randomised controlled trials (RCTs) provided timely evidence on the efficacy and safety of vaccinations and pharmaceuticals but were largely conducted in higher income countries, restricting generalisability to low- and middle-income countries (LMIC). Trials for non-pharmaceutical interventions (NPIs) were almost non-existent which was a missed opportunity (theme 3). Building on these themes from the narrative review, we underscore the importance of three other areas that need investment for effective evidence-driven policy-making. The COVID-19 response relied on strong multidisciplinary research infrastructures, but funders and academic institutions need to do more to incentivise team science (4). To enhance public trust in the use of scientific evidence for policy, researchers and policy-makers must work together to clearly communicate uncertainties in current evidence and any need to change policy as evidence evolves (5). Timely policy decisions require an established two-way process between scientists and policy makers to make the best use of evidence (6). For effective preparedness against future pandemics, it is essential to establish models, data, and experiments as fundamental pillars, complemented by efforts in planning and investment towards team science, public trust, and evidence-based policy-making across international communities. The paper concludes with a 'call to actions' for both policy-makers and researchers.

Abstract Objective To estimate the association between the aggregation and pair-wise combination of selected cardiovascular risk factors (CVRF) and 10-year all-cause mortality. Methods Secondary data analysis of the PERU MIGRANT study, a prospective population-based cohort. Ten-year all-cause mortality was determined for participants originally enrolled in the PERU MIGRANT Study (baseline in 2007) through the National Registry of Identification and Civil Status. The CVRF included hypertension, type 2 diabetes mellitus, hypercholesterolemia, and overweight/obesity. Exposures were composed of both the aggregation of the selected CVRF (one, two, and three or more CVRF) and pair-wise combinations of CVRF. Cox regression models were used to calculate hazard ratios (HR) and 95% confidence intervals (95% CI). Findings Of the 989 participants evaluated at baseline, 976 (98.8%) had information about vital status at 10 years of follow-up (9992.63 person-years), and 63 deaths were recorded. In the multivariable model, adjusting for sociodemographic and lifestyle variables, participants with two CVRF (HR: 2.48, 95% CI: 1.03–5.99), and those with three or more CVRF (HR: 3.93, 95% CI: 1.21–12.74) had higher all-cause mortality risk, compared to those without any CVRF. The pair-wise combinations associated with the highest risk of all-cause mortality, compared to those without such comorbidities, were hypertension with type 2 diabetes (HR: 11.67, 95% CI: 3.67–37.10), and hypertension with overweight/obesity (HR: 2.76, 95% CI: 1.18–6.71). Conclusions The aggregation of two or more CVRF and the combination of hypertension with type 2 diabetes or overweight/obesity were associated with an increased risk of 10-year all-cause mortality. These risk profiles will inform primary and secondary prevention strategies to delay mortality from cardiovascular risk factors.

Abstract Background Thromboembolism has been reported as a consequence of severe COVID-19. Although warfarin is a commonly used anticoagulant, it acts by antagonising vitamin K, which is low in patients with severe COVID-19. To date, the clinical evidence on the impact of regular use of warfarin on COVID-19-related thromboembolism is lacking. Methods On behalf of NHS England, we conducted a population-based cohort study investigating the association between warfarin and COVID-19 outcomes compared with direct oral anticoagulants (DOACs). We used the OpenSAFELY platform to analyse primary care data and pseudonymously linked SARS-CoV-2 antigen testing data, hospital admissions and death records from England. We used Cox regression to estimate hazard ratios (HRs) for COVID-19-related outcomes comparing warfarin with DOACs in people with non-valvular atrial fibrillation. We also conducted negative control outcome analyses (being tested for SARS-CoV-2 and non-COVID-19 death) to assess the potential impact of confounding. Results A total of 92,339 warfarin users and 280,407 DOAC users were included. We observed a lower risk of all outcomes associated with warfarin versus DOACs [testing positive for SARS-CoV-2, HR 0.73 (95% CI 0.68–0.79); COVID-19-related hospital admission, HR 0.75 (95% CI 0.68–0.83); COVID-19-related deaths, HR 0.74 (95% CI 0.66–0.83)]. A lower risk of negative control outcomes associated with warfarin versus DOACs was also observed [being tested for SARS-CoV-2, HR 0.80 (95% CI 0.79–0.81); non-COVID-19 deaths, HR 0.79 (95% CI 0.76–0.83)]. Conclusions Overall, this study shows no evidence of harmful effects of warfarin on severe COVID-19 disease.

While it is well known that socioeconomic markers are associated with a higher risk of arbovirus infections, research on the relationship between socioeconomic factors and congenital Zika syndrome (CZS) remains limited. This study investigates the relationship between socioeconomic risk markers and live births with CZS in Brazil. We conducted a population-based study using data from all registered live births in Brazil (Live Births Information System) linked with the Public Health Event Record from 1 January 2015 to 31 December 2018. We used logistic regression models to estimate the OR and 95% CIs of CZS based on a three-level framework. In an analysis of 11 366 686 live births, of which 3353 had CZS, we observed that live births of self-identified black or mixed race/brown mothers (1.72 (95% CI 1.47 to 2.01) and 1.37 (95% CI 1.24 to 1.51)) were associated with a higher odds of CZS. Live births from single women compared with married women and those from women with less than 12 years of education compared with those with more than 12 years of education also had higher odds of CZS. In addition, live births following fewer prenatal care appointments had increased odds of CZS in the nationwide data. However, in the analyses conducted in the Northeast region (where the microcephaly epidemic started before the link with Zika virus was established and before preventive measures were known or disseminated), no statistical association was found between the number of prenatal care appointments and the odds of CZS. This study shows that live births of the most socially vulnerable women in Brazil had the greatest odds of CZS. This disproportionate distribution of risk places an even greater burden on already socioeconomically disadvantaged groups, and the lifelong disabilities caused by this syndrome may reinforce existing social and health inequalities.

Abstract Background Applying the Robson classification to all births in Brazil, the objectives of our study were to estimate the rates of caesarean section delivery, assess the extent to which caesarean sections were clinically indicated, and identify variation across socioeconomic groups. Methods We conducted a population-based study using routine records of the Live Births Information System in Brazil from January 1, 2011, to December 31, 2017. We calculated the relative size of each Robson group; the caesarean section rate; and the contribution to the overall caesarean section rate. We categorised Brazilian municipalities using the Human Development Index to explore caesarean section rates further. We estimated the time trend in caesarean section rates. Results The rate of caesarean sections was higher in older and more educated women. Prelabour caesarean sections accounted for more than 54 % of all caesarean deliveries. Women with a previous caesarean section (Group 5) made up the largest group (21.7 %). Groups 6–9, for whom caesarean sections would be indicated in most cases, all had caesarean section rates above 82 %, as did Group 5. The caesarean section rates were higher in municipalities with a higher HDI. The general Brazilian caesarean section rate remained stable during the study period. Conclusions Brazil is a country with one of the world’s highest caesarean section rates. This nationwide population-based study provides the evidence needed to inform efforts to improve the provision of clinically indicated caesarean sections. Our results showed that caesarean section rates were lower among lower socioeconomic groups even when clinically indicated, suggesting sub-optimal access to surgical care.

Abstract Molecular mechanisms at the intersection of inflammation and cardiovascular diseases (CVD) among Africans are still unknown. We performed an epigenome-wide association study to identify loci associated with serum C-reactive protein (marker of inflammation) among Ghanaians and further assessed whether differentially methylated positions (DMPs) were linked to CVD in previous reports, or to estimated CVD risk in the same population. We used the Illumina Infinium® HumanMethylation450 BeadChip to obtain DNAm profiles of blood samples in 589 Ghanaians from the RODAM study (without acute infections, not taking anti-inflammatory medications, CRP levels

BackgroundIn addition to their direct pathogenic effects, arthropod-borne (arboviruses) have been hypothesized to indirectly contribute to hospitalizations and death through decompensation of pre-existing comorbidities. Using nationwide data routinely collected from 1 January 2014 to 31 December 2019 in Brazil, we investigated whether local increases in arbovirus notifications were associated with excess hospitalization.MethodsWe estimated the relative risks for the association between municipality- and state-level increases in arboviral case notifications and age-standardized hospitalization rates (i.e., classified as direct or indirect based on ICD-10 codes) using Bayesian multilevel models with random effects accounting for temporal and geographic correlations. For municipality-level analyses, we excluded municipalities with ResultsFrom 2014 to 2019, Brazil registered 7,566,330 confirmed dengue cases, 159,029 confirmed ZIKV cases, and 433,887 confirmed CHIKV cases. Dengue notifications have an endemic and seasonal pattern, with cases present in 5334 of the 5570 (95.8%) Brazilian municipalities and most (69.5%) registered between February and May. Chikungunya notifications followed a similar seasonal pattern to DENV but with a smaller incidence and were restricted to 4390 (78.8%) municipalities. ZIKV was only notified in 2581 (46.3%) municipalities. Increases in dengue and chikungunya notifications were associated with small increases in age-standardized arbovirus-related hospitalizations, but no consistent association was found with all-cause or other specific indirect causes of hospitalization. Zika was associated to increases in hospitalizations by neurological diseases.ConclusionsAlthough we found no clear association between increased incidence of the three arboviruses and excess risks of all-cause or indirect hospitalizations at the municipality- and state-levels, follow-up investigations at the individual-level are warranted to define any potential role of acute arbovirus infection in exacerbating risks of hospitalization from underlying conditions.

Abstract Background Characterising the size and distribution of the population at risk of severe COVID-19 is vital for effective policy and planning. Older age, and underlying health conditions, are associated with higher risk of death from COVID-19. This study aimed to describe the population at risk of severe COVID-19 due to underlying health conditions across the United Kingdom. Methods We used anonymised electronic health records from the Clinical Practice Research Datalink GOLD to estimate the point prevalence on 5 March 2019 of the at-risk population following national guidance. Prevalence for any risk condition and for each individual condition is given overall and stratified by age and region with binomial exact confidence intervals. We repeated the analysis on 5 March 2014 for full regional representation and to describe prevalence of underlying health conditions in pregnancy. We additionally described the population of cancer survivors, and assessed the value of linked secondary care records for ascertaining COVID-19 at-risk status. Results On 5 March 2019, 24.4% of the UK population were at risk due to a record of at least one underlying health condition, including 8.3% of school-aged children, 19.6% of working-aged adults, and 66.2% of individuals aged 70 years or more. 7.1% of the population had multimorbidity. The size of the at-risk population was stable over time comparing 2014 to 2019, despite increases in chronic liver disease and diabetes and decreases in chronic kidney disease and current asthma. Separately, 1.6% of the population had a new diagnosis of cancer in the past 5 y. Conclusions The population at risk of severe COVID-19 (defined as either aged ≥70 years, or younger with an underlying health condition) comprises 18.5 million individuals in the UK, including a considerable proportion of school-aged and working-aged individuals. Our national estimates broadly support the use of Global Burden of Disease modelled estimates in other countries. We provide age- and region- stratified prevalence for each condition to support effective modelling of public health interventions and planning of vaccine resource allocation. The high prevalence of health conditions among older age groups suggests that age-targeted vaccination strategies may efficiently target individuals at higher risk of severe COVID-19.

Abstract Background Leprosy continues to be an important cause of physical disability in endemic countries such as Brazil. Knowledge of determinants of these events may lead to better control measures and targeted interventions to mitigate its impact on affected individuals. This study investigated such factors among the most vulnerable portion of the Brazilian population. Methods A large cohort was built from secondary data originated from a national registry of applicants to social benefit programs, covering the period 2001–2015, including over 114 million individuals. Data were linked to the leprosy notification system utilizing data from 2007 until 2014. Descriptive and bivariate analyses lead to a multivariate analysis using a multinomial logistic regression model with cluster-robust standard errors. Associations were reported as Odds Ratios with their respective 95% confidence intervals. Results Among the original cohort members 21,565 new leprosy cases were identified between 2007 and 2014. Most of the cases (63.1%) had grade zero disability. Grades 1 and 2 represented 21 and 6%, respectively. Factors associated with increasing odds of grades 1 and 2 disability were age over 15 years old (ORs 2.39 and 1.95, respectively), less schooling (with a clear dose response effect) and being a multibacillary patient (ORs 3.5 and 8.22). Protective factors for both grades were being female (ORs 0.81 and 0.61) and living in a high incidence municipality (ORs 0.85 and 0.67). Conclusions The findings suggest that the developing of physical disabilities remains a public health problem which increases the burden of leprosy, mainly for those with severe clinical features and worse socioeconomic conditions. Early diagnosis is paramount to decrease the incidence of leprosy-related disability and our study points to the need for strengthening control actions in non-endemic areas in Brazil, where cases may be missed when presented at early stages in disease. Both actions are needed, to benefit patients and to achieve the WHO goal in reducing physical disabilities among new cases of leprosy.

Background: Patients surviving hospitalisation for COVID-19 are thought to be at high risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in people after discharge from hospital with COVID-19. Methods: Working on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following pre-pandemic hospitalisation with pneumonia, and a frequency-matched cohort from the general population in 2019. We studied seven outcomes: deep vein thrombosis (DVT), pulmonary embolism (PE), ischaemic stroke, myocardial infarction (MI), heart failure, AKI and new type 2 diabetes mellitus (T2DM) diagnosis. Absolute rates were measured in each cohort and Fine and Gray models were used to estimate age/sex adjusted subdistribution hazard ratios comparing outcome risk between discharged COVID-19 patients and the two comparator cohorts. Results: Amongst the population of 77,347 patients discharged following hospitalisation with COVID-19, rates for the majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly higher risk of all outcomes compared to matched controls from the 2019 general population. Across the whole study period, the risk of outcomes was more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had higher risk of T2DM (15.2 versus 37.2 [rate per 1,000-person-years for COVID-19 versus pneumonia, respectively]; SHR, 1.46 [95% CI: 1.31 - 1.63]). Conclusions: Risk of cardiometabolic and pulmonary adverse outcomes is markedly raised following discharge from hospitalisation with COVID-19 compared to the general population. However, excess risks were similar to those seen following discharge post-pneumonia. Overall, this suggests a large additional burden on healthcare resources.

Objective To determine the association between baseline kidney function and subsequent all-cause mortality.Design and setting A general population-based cohort study from rural Uganda.Participants People aged 18 years and above with measured baseline estimated glomerular filtration rate (eGFR), recruited from survey rounds in 2011–2012 or 2014–2015 and followed up to March 2019.Outcome measure The primary outcome was all-cause mortality, identified through reports from community health workers and verified by verbal autopsy. The association between baseline eGFR category and mortality was determined using multivariable Cox regression.Results Of 5812 participants in both rounds, we included 5678 (97.7%) participants with kidney function and mortality data; the median age was 36 years (IQR 24–50), 60.7% were female, 10.3% were hypertensive, 9.8% were HIV-positive and 1.5% were diabetic. During a median follow-up of 5.0 years (IQR 3.7–6.0) there were 140 deaths. In age-adjusted and sex-adjusted analyses, eGFR 90 mL/min/1.73 m2. After inclusion of additional confounders (HIV, body mass index, diabetes, hypertension, alcohol and smoking status) into the model, eGFR

Summary: Background: Residents in care homes have been severely impacted by COVID-19. We describe trends in the mortality risk among residents of care homes compared to private homes. Methods: On behalf of NHS England we used OpenSAFELY-TPP to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to Care and Quality Commission data. Findings: We included 4,340,648 people aged 65 years or older on the 1st of February 2019, 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to those in private housing in February 2019: comparative mortality figure (CMF) = 10.59 (95%CI = 9.51, 11.81) among women, and 10.87 (9.93, 11.90) among men. By April 2020 these relative differences had increased to more than 17 times with CMFs of 17.57 (16.43, 18.79) among women and 18.17 (17.22, 19.17) among men. CMFs did not increase during the second wave, despite a rise in the absolute age-standardised COVID-19 mortality risks. Interpretation: COVID-19 has had a disproportionate impact on the mortality of care home residents in England compared to older residents of private homes, but only in the first wave. This may be explained by a degree of acquired immunity, improved protective measures or changes in the underlying frailty of the populations. The care home population should be prioritised for measures aimed at controlling COVID-19. Funding: Medical Research Council MR/V015737/1

Abstract Background Record linkage is the process of identifying and combining records about the same individual from two or more different datasets. While there are many open source and commercial data linkage tools, the volume and complexity of currently available datasets for linkage pose a huge challenge; hence, designing an efficient linkage tool with reasonable accuracy and scalability is required. Methods We developed CIDACS-RL (Centre for Data and Knowledge Integration for Health – Record Linkage), a novel iterative deterministic record linkage algorithm based on a combination of indexing search and scoring algorithms (provided by Apache Lucene). We described how the algorithm works and compared its performance with four open source linkage tools (AtyImo, Febrl, FRIL and RecLink) in terms of sensitivity and positive predictive value using gold standard dataset. We also evaluated its accuracy and scalability using a case-study and its scalability and execution time using a simulated cohort in serial (single core) and multi-core (eight core) computation settings. Results Overall, CIDACS-RL algorithm had a superior performance: positive predictive value (99.93% versus AtyImo 99.30%, RecLink 99.5%, Febrl 98.86%, and FRIL 96.17%) and sensitivity (99.87% versus AtyImo 98.91%, RecLink 73.75%, Febrl 90.58%, and FRIL 74.66%). In the case study, using a ROC curve to choose the most appropriate cut-off value (0.896), the obtained metrics were: sensitivity = 92.5% (95% CI 92.07–92.99), specificity = 93.5% (95% CI 93.08–93.8) and area under the curve (AUC) = 97% (95% CI 96.97–97.35). The multi-core computation was about four times faster (150 seconds) than the serial setting (550 seconds) when using a dataset of 20 million records. Conclusion CIDACS-RL algorithm is an innovative linkage tool for huge datasets, with higher accuracy, improved scalability, and substantially shorter execution time compared to other existing linkage tools. In addition, CIDACS-RL can be deployed on standard computers without the need for high-speed processors and distributed infrastructures.

Abstract Background People with end-stage kidney disease have an increased risk of active tuberculosis (TB). Previous systematic reviews have demonstrated that patients with chronic kidney disease (CKD) have increased risk of severe community-acquired infections. We investigated the association between CKD (prior to renal replacement therapy) and incidence of TB in UK General Practice. Methods Using the UK Clinical Practice Research Datalink, 242,349 patients with CKD (stages 3-5) (estimated glomerular filtration rate

Abstract Introduction Beta‐cell autoantibodies are established markers of autoimmunity, which we compared between Ghanaian adults with or without diabetes, living in rural and urban Ghana and in three European cities. Methods In the multicenter cross‐sectional Research on Obesity and Diabetes among African Migrants (RODAM) study (N = 5898), we quantified autoantibodies against glutamic acid decarboxylase (GAD65Ab) by radioligand binding assay (RBA) and established cut‐offs for positivity by displacement analysis. In a subsample, we performed RBA for zinc transporter‐8 autoantibodies (ZnT8Ab). Associations of environmental, sociodemographic, and clinical factors with GAD65Ab were calculated. Results In this study population (age: 46.1 ± 11.9 years; female: 62%; Ghana‐rural: 1111; Ghana‐urban: 1455; Europe: 3332), 9.2% had diabetes with adult‐onset. GAD65Ab concentrations were the highest in Ghana‐rural (32.4; 10.8‐71.3 U/mL), followed by Ghana‐urban (26.0; 12.3‐49.1 U/mL) and Europe (11.9; 3.0‐22.8 U/mL) with no differences between European cities. These distributions were similar for ZnT8Ab. Current fever, history of fever, and higher concentrations of liver enzymes marginally explained site‐specific GAD65Ab concentrations. GAD65Ab positivity was as frequent in diabetes as in nondiabetes (5.4% vs 6.1%; P = .25). This was also true for ZnT8Ab positivity. Conclusion Geographic location determines the occurrence of GAD65Ab and ZnT8Ab more than the diabetes status. Beta‐cell autoimmunity may not be feasible to differentiate diabetes subgroups in this population.

Abstract Background The safety of restarting angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARB) after acute kidney injury (AKI) is unclear. There is concern that previous users do not restart ACEI/ARB despite ongoing indications. We sought to determine the risk of adverse events after an episode of AKI, comparing prior ACEI/ARB users who stop treatment to those who continue. Methods We conducted two parallel cohort studies in English and Swedish primary and secondary care, 2006–2016. We used multivariable Cox regression to estimate hazard ratios (HR) for hospital admission with heart failure (primary analysis), AKI, stroke, or death within 2 years after hospital discharge following a first AKI episode. We compared risks of admission between people who stopped ACEI/ARB treatment to those who were prescribed ACEI/ARB within 30 days of AKI discharge. We undertook sensitivity analyses, including propensity score-matched samples, to explore the robustness of our results. Results In England, we included 7303 people with AKI hospitalisation following recent ACEI/ARB therapy for the primary analysis. Four thousand three (55%) were classified as stopping ACEI/ARB based on no prescription within 30 days of discharge. In Sweden, we included 1790 people, of whom 1235 (69%) stopped treatment. In England, no differences were seen in subsequent risk of heart failure (HR 1.10; 95% confidence intervals (CI) 0.93–1.30), AKI (HR 0.90; 95% CI 0.77–1.05), or stroke (HR 0.99; 95% CI 0.71–1.38), but there was an increased risk of death (HR 1.27; 95% CI 1.15–1.41) in those who stopped ACEI/ARB compared to those who continued. Results were similar in Sweden: no differences were seen in risk of heart failure (HR 0.91; 95% CI 0.73–1.13) or AKI (HR 0.81; 95% CI 0.54–1.21). However, no increased risk of death was seen (HR 0.94; 95% CI 0.78–1.13) and stroke was less common in people who stopped ACEI/ARB (HR 0.56; 95% CI 0.34–0.93). Results were similar across all sensitivity analyses. Conclusions Previous ACEI/ARB users who continued treatment after an episode of AKI did not have an increased risk of heart failure or subsequent AKI compared to those who stopped the drugs.

Abstract Background Chronic kidney disease (CKD) is a substantial cause of morbidity and mortality worldwide with disproportionate effects in sub-Saharan Africa (SSA). The optimal methods to estimate glomerular filtration rate (GFR) and therefore to determine the presence of CKD in SSA are uncertain. We plan to measure iohexol excretion to accurately determine GFR in Malawi, South Africa and Uganda. We will then assess the performance of existing equations to estimate GFR and determine whether a modified equation can better improve estimation of GFR in sub-Saharan Africa. Methods The African Research on Kidney Disease (ARK) study is a three-country study embedded within existing cohorts. We seek to enrol 3000 adults > 18 years based on baseline serum creatinine. Study procedures include questionnaires on socio-demographics and established risk factors for kidney disease along with anthropometry, body composition, blood pressure, blood chemistry and urine microscopy and albuminuria. We will measure GFR (mGFR) by plasma clearance of iohexol at 120, 180 and 240 min. We will compare eGFR determined by established equations with mGFR using Bland-Altman plots. We will use regression methods to estimate GFR and compare the newly derived model with existing equations. Discussion Through the ARK study, we aim to establish the optimal approach to estimate GFR in SSA. The study has the advantage of drawing participants from three countries, which will increase the applicability of the findings across the region. It is also embedded within established cohorts that have longitudinal information and serial measures that can be used to characterize kidney disease over a period of time. This will help to overcome the limitations of previous research, including small numbers, selected population sub-groups, and lack of data on proteinuria. The ARK collaboration provides an opportunity for close working partnerships across different centres, using standardized protocols and measurements, and shared bio-repositories. We plan to build on the collaboration for this study for future work on kidney disease in sub-Saharan Africa, and welcome additional partners from across the continent.

AimsThis study aimed to investigate the frequency of islet autoantibody positivity in adult patients with recently diagnosed diabetes in Uganda and its associated characteristics.MethodsAutoantibodies to glutamic acid decarboxylase-65 (GADA), zinc transporter 8 (ZnT8-A), and tyrosine phosphatase (IA-2A) were measured in 534 adult patients with recently diagnosed diabetes. Islet autoantibody positivity was defined based on diagnostic thresholds derived from a local adult population without diabetes. The socio-demographic, clinical, and metabolic characteristics of islet autoantibody-positive and negative participants were then compared. The differences in these characteristics were analysed using the x2 test for categorical data and the Kruskal Wallis test for continuous data. Multivariate analysis was performed to identify predictors of islet autoantibody positivity.ResultsThirty four (6.4%) participants were positive for ≥1 islet autoantibody. GADA, IA-2A and ZnT8-A positivity was detected in 17 (3.2%), 10 (1.9%), and 7 (1.3%) participants, respectively. Compared with those negative for islet autoantibodies, participants positive for islet autoantibodies were more likely to live in a rural area (n = 18, 52.9% Vs n = 127, 25.5%, p = 0.005), to be initiated on insulin therapy (n = 19, 55.9% Vs n = 134, 26.8%, pConclusionThe prevalence of islet autoantibody positivity was relatively low, suggesting that pancreatic autoimmunity is a rare cause of new-onset diabetes in this adult Ugandan population. Living in a rural area and being initiated on insulin therapy were independently associated with islet autoantibody positivity in this study population.

Background Recent studies indicate that vitamin D supplementation may decrease respiratory tract infections, but the association between vitamin D and COVID-19 is still unclear. Objective To explore the association between vitamin D status and infections, hospitalisation, and mortality due to COVID-19. Methods We used UK Biobank, a nationwide cohort of 500,000 individuals aged between 40 and 69 years at recruitment between 2006 and 2010. We included people with at least one serum vitamin D test, living in England with linked primary care and inpatient records. The primary exposure was serum vitamin D status measured at recruitment, defined as deficiency at Results We included 307,512 participants (54.9% female, 55.9% over 70 years old) in our analysis. During summertime months, weak evidence existed that the vitamin D deficiency group had a lower hazard of being diagnosed with COVID-19 (hazard ratio [HR] = 0.86, 95% confidence interval [CI] = 0.77–0.95). During non-summertime, the vitamin D deficiency group had a higher hazard of COVID-19 compared with the vitamin D sufficient group (HR = 1.14, 95% CI = 1.01–1.30). No evidence was found that vitamin D deficiency or insufficiency was associated with either hospitalisation or mortality due to COVID-19 in any time strata. Conclusion We found no evidence of an association between historical vitamin D status and hospitalisation or mortality due to COVID-19, along with inconsistent results for any association between vitamin D and diagnosis of COVID-19. However, studies using more recent vitamin D measurements and systematic COVID-19 testing are needed.

Summary: Background: For five decades, blood pressure lowering treatment has been recommended for patients with hypertension (currently defined as blood pressure of ≥140/90 mm Hg). In the past 20 years, guidelines for treatment began incorporating predicted absolute cardiovascular disease risk (predicted risk) and reducing blood pressure thresholds. The blood pressure threshold at which to start treatment has become a secondary consideration in some countries. We aimed to provide descriptive data to assess the relative importance of blood pressure thresholds versus predicted risk on the subsequent rate of cardiovascular disease to inform treatment decisions. Methods: In this English population-based cohort study, we used linked data from the Clinical Practice Research Datalink (CPRD) GOLD, Hospital Episode Statistics Admitted Patient Care, and the Office for National Statistics mortality data, and area-based deprivation indices (Townsend scores). Eligible patients were aged 30–79 years on Jan 1, 2011 (cohort entry date) and could be linked to hospital, mortality, and deprivation data. Patients were followed up until death, end of CPRD follow-up, or Nov 31, 2018. We examined three outcomes: cardiovascular disease, markers of potential target organ damage, and incident dementia without a known cause. The rate of each outcome was estimated and stratified by systolic blood pressure and predicted 10-year risk of cardiovascular disease (QRISK2 algorithm). Findings: Between Jan 1, 2011, and Nov 31, 2018, 1 098 991 patients were included in the cohort and followed up for a median of 4·3 years (IQR 2·6–6·0; total follow-up of 4·6 million person-years). Median age at entry was 52 years (IQR 42–62) and 629 711 (57·3%) patients were female. There were 51 996 cardiovascular disease events and the overall rate of cardiovascular disease was 11·2 per 1000 person-years (95% CI 11·1–11·3). Median QRISK2 10-year predicted risk was 4·6% (IQR 1·4–12·0) and mean systolic blood pressure before cohort entry was 129·1 mm Hg (SD 15·7). Within strata of predicted risk, the effect of increasing systolic blood pressure on outcomes was small. For example, in the group with 10·0–19·9% predicted risk, rates of all cardiovascular disease rose from 20·1 to 23·6 per 1000 person-years between systolic blood pressures less than 110 mm Hg and 180 and higher mm Hg. But among patients with systolic blood pressure 140·0–149·9 mm Hg, rates rose from 6·9 to 52·3 per 1000 person-years between those with less than 10·0% risk and those with 30·0% or higher predicted risk. Interpretation: For a wide range of blood pressures, the rate of cardiovascular disease and effectiveness of blood pressure drug treatment was mainly determined by predicted risk, with blood pressure thresholds 140/90 mm Hg or 160/100 mm Hg—ubiquitous in most countries—adding little useful information. When medium-term predicted risk is low, there is no urgency to initiate drug treatment, allowing time to attempt non-pharmacological blood pressure reduction. Funding: National Institute for Health Research.

Summary: Background: Limited information exists about the incidence of first-ever stroke at the population level, particularly in low- and middle-income countries (LMIC). Longitudinal data from the CRONICAS Cohort Study includes both altitude and urbanization and allows a detailed assessment of stroke incidence in resource constrained settings. The aim of this study was to estimate the incidence and explore risk factors of first-ever stroke at the population level in Peru. Methods: Stroke was defined using a standardised approach based on information from cohort participants or family members. This information was adjudicated centrally by trained physicians using common definitions. Time of follow-up was calculated as the difference between date of enrolment and the reported date of the stroke event. Unstandardised and age-standardised, first-ever stroke incidence rate and 95% confidence intervals (95% CI) were calculated. Generalized linear models, assuming Poisson distribution and link log, were utilized to determine potential factors to develop stroke. Findings: 3,601 individuals were originally enrolled in the cohort and 2,471 provided data for the longitudinal analysis. The median time of follow-up was 7.0 (range: 1 - 9) years, accruing a total of 17,308 person-years. During follow-up, there were 25 incident cases of stroke, resulting in an age-standardised incidence of stroke of 98.8 (95% CI: 63.8–154.0) per 100,000 person-years. After adjustment by age and sex, stroke incidence was higher among people with hypertension (incidence risk ratio (IRR) = 5.18; 95% CI: 1.89 – 14.16), but lower among people living at high altitude (IRR = 0.09; 95% CI: 0.01 – 0.63). Interpretation: Our results indicate a high incidence of first-ever strokes in Peruvian general population. These results are consistent with the estimates found in previous LMIC reports. Our study also found a contributing role of hypertension, increasing the risk of having a first-ever stroke. This work further advances the field of stroke epidemiology by identifying high altitude as a factor related to lower incidence of stroke in a longitudinal study. However, this information needs to be considered with cautions because of the study limitations.

BackgroundThere is concern about medium to long-term adverse outcomes following acute Coronavirus Disease 2019 (COVID-19), but little relevant evidence exists. We aimed to investigate whether risks of hospital admission and death, overall and by specific cause, are raised following discharge from a COVID-19 hospitalisation.Methods and findingsWith the approval of NHS-England, we conducted a cohort study, using linked primary care and hospital data in OpenSAFELY to compare risks of hospital admission and death, overall and by specific cause, between people discharged from COVID-19 hospitalisation (February to December 2020) and surviving at least 1 week, and (i) demographically matched controls from the 2019 general population; and (ii) people discharged from influenza hospitalisation in 2017 to 2019. We used Cox regression adjusted for age, sex, ethnicity, obesity, smoking status, deprivation, and comorbidities considered potential risk factors for severe COVID-19 outcomes. We included 24,673 postdischarge COVID-19 patients, 123,362 general population controls, and 16,058 influenza controls, followed for ≤315 days. COVID-19 patients had median age of 66 years, 13,733 (56%) were male, and 19,061 (77%) were of white ethnicity. Overall risk of hospitalisation or death (30,968 events) was higher in the COVID-19 group than general population controls (fully adjusted hazard ratio [aHR] 2.22, 2.14 to 2.30, p < 0.001) but slightly lower than the influenza group (aHR 0.95, 0.91 to 0.98, p = 0.004). All-cause mortality (7,439 events) was highest in the COVID-19 group (aHR 4.82, 4.48 to 5.19 versus general population controls [p < 0.001] and 1.74, 1.61 to 1.88 versus influenza controls [p < 0.001]). Risks for cause-specific outcomes were higher in COVID-19 survivors than in general population controls and largely similar or lower in COVID-19 compared with influenza patients. However, COVID-19 patients were more likely than influenza patients to be readmitted or die due to their initial infection or other lower respiratory tract infection (aHR 1.37, 1.22 to 1.54, p < 0.001) and to experience mental health or cognitive-related admission or death (aHR 1.37, 1.02 to 1.84, p = 0.039); in particular, COVID-19 survivors with preexisting dementia had higher risk of dementia hospitalisation or death (age- and sex-adjusted HR 2.47, 1.37 to 4.44, p = 0.002). Limitations of our study were that reasons for hospitalisation or death may have been misclassified in some cases due to inconsistent use of codes, and we did not have data to distinguish COVID-19 variants.ConclusionsIn this study, we observed that people discharged from a COVID-19 hospital admission had markedly higher risks for rehospitalisation and death than the general population, suggesting a substantial extra burden on healthcare. Most risks were similar to those observed after influenza hospitalisations, but COVID-19 patients had higher risks of all-cause mortality, readmission or death due to the initial infection, and dementia death, highlighting the importance of postdischarge monitoring.