Factors associated with COVID-19-related death using OpenSAFELY.
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ABSTRACT:
SUBMITTER: Williamson EJ
PROVIDER: S-EPMC7611074 | biostudies-literature | 2020 Aug
REPOSITORIES: biostudies-literature
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Factors associated with COVID-19-related death using OpenSAFELY.
Williamson Elizabeth J EJ Walker Alex J AJ Bhaskaran Krishnan K Bacon Seb S Bates Chris C Morton Caroline E CE Curtis Helen J HJ Mehrkar Amir A Evans David D Inglesby Peter P Cockburn Jonathan J McDonald Helen I HI MacKenna Brian B Tomlinson Laurie L Douglas Ian J IJ Rentsch Christopher T CT Mathur Rohini R Wong Angel Y S AYS Grieve Richard R Harrison David D Forbes Harriet H Schultze Anna A Croker Richard R Parry John J Hester Frank F Harper Sam S Perera Rafael R Evans Stephen J W SJW Smeeth Liam L Goldacre Ben B
Nature 20200708 7821
Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide<sup>1</sup>. There is unprecedented urgency to understand who is most at risk of severe outcomes, and this requires new approaches for the timely analysis of large datasets. Working on behalf of NHS England, we created OpenSAFELY-a secure health analytics platform that covers 40% of all patients in England and holds patient data within the existing data centre of a major vendor of primary care electronic health records. ...[more]
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Project description:BackgroundObtaining 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.MethodsWe 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.ResultsPrediction 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.ConclusionsOur 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.
| S-EPMC8865947 | biostudies-literature
Project description:ObjectiveTo characterise factors associated with COVID-19 vaccine uptake among people with kidney disease in England.DesignRetrospective cohort study using the OpenSAFELY-TPP platform, performed with the approval of NHS England.SettingIndividual-level routine clinical data from 24 million people across GPs in England using TPP software. Primary care data were linked directly with COVID-19 vaccine records up to 31 August 2022 and with renal replacement therapy (RRT) status via the UK Renal Registry (UKRR).ParticipantsA cohort of adults with stage 3-5 chronic kidney disease (CKD) or receiving RRT at the start of the COVID-19 vaccine roll-out was identified based on evidence of reduced estimated glomerular filtration rate (eGFR) or inclusion in the UKRR.Main outcome measuresDose-specific vaccine coverage over time was determined from 1 December 2020 to 31 August 2022. Individual-level factors associated with receipt of a 3-dose or 4-dose vaccine series were explored via Cox proportional hazards models.Results992 205 people with stage 3-5 CKD or receiving RRT were included. Cumulative vaccine coverage as of 31 August 2022 was 97.5%, 97.0% and 93.9% for doses 1, 2 and 3, respectively, and 81.9% for dose 4 among individuals with one or more indications for eligibility. Delayed 3-dose vaccine uptake was associated with younger age, minority ethnicity, social deprivation and severe mental illness-associations that were consistent across CKD severity subgroups, dialysis patients and kidney transplant recipients. Similar associations were observed for 4-dose uptake.ConclusionAlthough high primary vaccine and booster dose coverage has been achieved among people with kidney disease in England, key disparities in vaccine uptake remain across clinical and demographic groups and 4-dose coverage is suboptimal. Targeted interventions are needed to identify barriers to vaccine uptake among under-vaccinated subgroups identified in the present study.
| S-EPMC9890277 | biostudies-literature
Project description:BackgroundEarly descriptions of patients admitted to hospital during the COVID-19 pandemic showed a lower prevalence of asthma and chronic obstructive pulmonary disease (COPD) than would be expected for an acute respiratory disease like COVID-19, leading to speculation that inhaled corticosteroids (ICSs) might protect against infection with severe acute respiratory syndrome coronavirus 2 or the development of serious sequelae. We assessed the association between ICS and COVID-19-related death among people with COPD or asthma using linked electronic health records (EHRs) in England, UK.MethodsIn this observational study, we analysed patient-level data for people with COPD or asthma from primary care EHRs linked with death data from the Office of National Statistics using the OpenSAFELY platform. The index date (start of follow-up) for both cohorts was March 1, 2020; follow-up lasted until May 6, 2020. For the COPD cohort, individuals were eligible if they were aged 35 years or older, had COPD, were a current or former smoker, and were prescribed an ICS or long-acting β agonist plus long-acting muscarinic antagonist (LABA-LAMA) as combination therapy within the 4 months before the index date. For the asthma cohort, individuals were eligible if they were aged 18 years or older, had been diagnosed with asthma within 3 years of the index date, and were prescribed an ICS or short-acting β agonist (SABA) only within the 4 months before the index date. We compared the outcome of COVID-19-related death between people prescribed an ICS and those prescribed alternative respiratory medications: ICSs versus LABA-LAMA for the COPD cohort, and low-dose or medium-dose and high-dose ICSs versus SABAs only in the asthma cohort. We used Cox regression models to estimate hazard ratios (HRs) and 95% CIs for the association between exposure categories and the outcome in each population, adjusted for age, sex, and all other prespecified covariates. We calculated e-values to quantify the effect of unmeasured confounding on our results.FindingsWe identified 148 557 people with COPD and 818 490 people with asthma who were given relevant respiratory medications in the 4 months before the index date. People with COPD who were prescribed ICSs were at increased risk of COVID-19-related death compared with those prescribed LABA-LAMA combinations (adjusted HR 1·39 [95% CI 1·10-1·76]). Compared with those prescribed SABAs only, people with asthma who were prescribed high-dose ICS were at an increased risk of death (1·55 [1·10-2·18]), whereas those given a low or medium dose were not (1·14 [0·85-1·54]). Sensitivity analyses showed that the apparent harmful association we observed could be explained by relatively small health differences between people prescribed ICS and those not prescribed ICS that were not recorded in the database (e value lower 95% CI 1·43).InterpretationOur results do not support a major role for regular ICS use in protecting against COVID-19-related death among people with asthma or COPD. Observed increased risks of COVID-19-related death can be plausibly explained by unmeasured confounding due to disease severity.FundingUK Medical Research Council.
| S-EPMC7515601 | biostudies-literature
Project description:ObjectiveTo assess the association between learning disability and risk of hospital admission and death from covid-19 in England among adults and children.DesignPopulation based cohort study on behalf of NHS England using the OpenSAFELY platform.SettingPatient level data were obtained for more than 17 million people registered with a general practice in England that uses TPP software. Electronic health records were linked with death data from the Office for National Statistics and hospital admission data from NHS Secondary Uses Service.ParticipantsAdults (aged 16-105 years) and children (<16 years) from two cohorts: wave 1 (registered with a TPP practice as of 1 March 2020 and followed until 31 August 2020); and wave 2 (registered 1 September 2020 and followed until 8 February 2021). The main exposure group consisted of people on a general practice learning disability register; a subgroup was defined as those having profound or severe learning disability. People with Down's syndrome and cerebral palsy were identified (whether or not they were on the learning disability register).Main outcome measureCovid-19 related hospital admission and covid-19 related death. Non-covid-19 deaths were also explored.ResultsFor wave 1, 14 312 023 adults aged ≥16 years were included, and 90 307 (0.63%) were on the learning disability register. Among adults on the register, 538 (0.6%) had a covid-19 related hospital admission; there were 222 (0.25%) covid-19 related deaths and 602 (0.7%) non-covid deaths. Among adults not on the register, 29 781 (0.2%) had a covid-19 related hospital admission; there were 13 737 (0.1%) covid-19 related deaths and 69 837 (0.5%) non-covid deaths. Wave 1 hazard ratios for adults on the learning disability register (adjusted for age, sex, ethnicity, and geographical location) were 5.3 (95% confidence interval 4.9 to 5.8) for covid-19 related hospital admission and 8.2 (7.2 to 9.4) for covid-19 related death. Wave 2 produced similar estimates. Associations were stronger among those classified as having severe to profound learning disability, and among those in residential care. For both waves, Down's syndrome and cerebral palsy were associated with increased hazards for both events; Down's syndrome to a greater extent. Hazard ratios for non-covid deaths followed similar patterns with weaker associations. Similar patterns of increased relative risk were seen for children, but covid-19 related deaths and hospital admissions were rare, reflecting low event rates among children.ConclusionsPeople with learning disability have markedly increased risks of hospital admission and death from covid-19, over and above the risks observed for non-covid causes of death. Prompt access to covid-19 testing and healthcare is warranted for this vulnerable group, and prioritisation for covid-19 vaccination and other targeted preventive measures should be considered.
| S-EPMC8278652 | biostudies-literature
Project description:AimsThe COVID-19 pandemic created unprecedented pressure on healthcare services. This study investigates whether disease-modifying antirheumatic drug (DMARD) safety monitoring was affected during the COVID-19 pandemic.MethodsA population-based cohort study was conducted using the OpenSAFELY platform to access electronic health record data from 24.2 million patients registered at general practices using TPP's SystmOne software. Patients were included for further analysis if prescribed azathioprine, leflunomide or methotrexate between November 2019 and July 2022. Outcomes were assessed as monthly trends and variation between various sociodemographic and clinical groups for adherence with standard safety monitoring recommendations.ResultsAn acute increase in the rate of missed monitoring occurred across the study population (+12.4 percentage points) when lockdown measures were implemented in March 2020. This increase was more pronounced for some patient groups (70-79 year-olds: +13.7 percentage points; females: +12.8 percentage points), regions (North West: +17.0 percentage points), medications (leflunomide: +20.7 percentage points) and monitoring tests (blood pressure: +24.5 percentage points). Missed monitoring rates decreased substantially for all groups by July 2022. Consistent differences were observed in overall missed monitoring rates between several groups throughout the study.ConclusionDMARD monitoring rates temporarily deteriorated during the COVID-19 pandemic. Deterioration coincided with the onset of lockdown measures, with monitoring rates recovering rapidly as lockdown measures were eased. Differences observed in monitoring rates between medications, tests, regions and patient groups highlight opportunities to tackle potential inequalities in the provision or uptake of monitoring services. Further research should evaluate the causes of the differences identified between groups.
| S-EPMC7616619 | biostudies-literature
Project description:BackgroundMortality from COVID-19 shows a strong relationship with age and pre-existing medical conditions, as does mortality from other causes. We aimed to investigate how specific factors are differentially associated with COVID-19 mortality as compared to mortality from causes other than COVID-19.MethodsWorking on behalf of NHS England, we carried out a cohort study within the OpenSAFELY platform. Primary care data from England were linked to national death registrations. We included all adults (aged ≥18 years) in the database on 1st February 2020 and with >1 year of continuous prior registration; the cut-off date for deaths was 9th November 2020. Associations between individual-level characteristics and COVID-19 and non-COVID deaths, classified according to the presence of a COVID-19 code as the underlying cause of death on the death certificate, were estimated by fitting age- and sex-adjusted logistic models for these two outcomes.Findings17,456,515 individuals were included. 17,063 died from COVID-19 and 134,316 from other causes. Most factors associated with COVID-19 death were similarly associated with non-COVID death, but the magnitudes of association differed. Older age was more strongly associated with COVID-19 death than non-COVID death (e.g. ORs 40.7 [95% CI 37.7-43.8] and 29.6 [28.9-30.3] respectively for ≥80 vs 50-59 years), as was male sex, deprivation, obesity, and some comorbidities. Smoking, history of cancer and chronic liver disease had stronger associations with non-COVID than COVID-19 death. All non-white ethnic groups had higher odds than white of COVID-19 death (OR for Black: 2.20 [1.96-2.47], South Asian: 2.33 [2.16-2.52]), but lower odds than white of non-COVID death (Black: 0.88 [0.83-0.94], South Asian: 0.78 [0.75-0.81]).InterpretationSimilar associations of most individual-level factors with COVID-19 and non-COVID death suggest that COVID-19 largely multiplies existing risks faced by patients, with some notable exceptions. Identifying the unique factors contributing to the excess COVID-19 mortality risk among non-white groups is a priority to inform efforts to reduce deaths from COVID-19.FundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, Health Data Research UK.
| S-EPMC8106239 | biostudies-literature
Project description:BackgroundAfter claiming nearly five hundred thousand lives globally, the COVID-19 pandemic is showing no signs of slowing down. While the UK, USA, Brazil and parts of Asia are bracing themselves for the second wave-or the extension of the first wave-it is imperative to identify the primary social, economic, environmental, demographic, ethnic, cultural and health factors contributing towards COVID-19 infection and mortality numbers to facilitate mitigation and control measures.MethodsWe process several open-access datasets on US states to create an integrated dataset of potential factors leading to the pandemic spread. We then apply several supervised machine learning approaches to reach a consensus as well as rank the key factors. We carry out regression analysis to pinpoint the key pre-lockdown factors that affect post-lockdown infection and mortality, informing future lockdown-related policy making.FindingsPopulation density, testing numbers and airport traffic emerge as the most discriminatory factors, followed by higher age groups (above 40 and specifically 60+). Post-lockdown infected and death rates are highly influenced by their pre-lockdown counterparts, followed by population density and airport traffic. While healthcare index seems uncorrelated with mortality rate, principal component analysis on the key features show two groups: states (1) forming early epicenters and (2) experiencing strong second wave or peaking late in rate of infection and death. Finally, a small case study on New York City shows that days-to-peak for infection of neighboring boroughs correlate better with inter-zone mobility than the inter-zone distance.InterpretationStates forming the early hotspots are regions with high airport or road traffic resulting in human interaction. US states with high population density and testing tend to exhibit consistently high infected and death numbers. Mortality rate seems to be driven by individual physiology, preexisting condition, age etc., rather than gender, healthcare facility or ethnic predisposition. Finally, policymaking on the timing of lockdowns should primarily consider the pre-lockdown infected numbers along with population density and airport traffic.
| S-EPMC7584177 | biostudies-literature
Project description:BackgroundDifferences in the distribution of individual-level clinical risk factors across regions do not fully explain the observed global disparities in COVID-19 outcomes. We aimed to investigate the associations between environmental and societal factors and country-level variations in mortality attributed to COVID-19 among people with rheumatic disease globally.MethodsIn this observational study, we derived individual-level data on adults (aged 18-99 years) with rheumatic disease and a confirmed status of their highest COVID-19 severity level from the COVID-19 Global Rheumatology Alliance (GRA) registry, collected between March 12, 2020, and Aug 27, 2021. Environmental and societal factors were obtained from publicly available sources. The primary endpoint was mortality attributed to COVID-19. We used a multivariable logistic regression to evaluate independent associations between environmental and societal factors and death, after controlling for individual-level risk factors. We used a series of nested mixed-effects models to establish whether environmental and societal factors sufficiently explained country-level variations in death.Findings14 044 patients from 23 countries were included in the analyses. 10 178 (72·5%) individuals were female and 3866 (27·5%) were male, with a mean age of 54·4 years (SD 15·6). Air pollution (odds ratio 1·10 per 10 μg/m3 [95% CI 1·01-1·17]; p=0·0105), proportion of the population aged 65 years or older (1·19 per 1% increase [1·10-1·30]; p<0·0001), and population mobility (1·03 per 1% increase in number of visits to grocery and pharmacy stores [1·02-1·05]; p<0·0001 and 1·02 per 1% increase in number of visits to workplaces [1·00-1·03]; p=0·032) were independently associated with higher odds of mortality. Number of hospital beds (0·94 per 1-unit increase per 1000 people [0·88-1·00]; p=0·046), human development index (0·65 per 0·1-unit increase [0·44-0·96]; p=0·032), government response stringency (0·83 per 10-unit increase in containment index [0·74-0·93]; p=0·0018), as well as follow-up time (0·78 per month [0·69-0·88]; p<0·0001) were independently associated with lower odds of mortality. These factors sufficiently explained country-level variations in death attributable to COVID-19 (intraclass correlation coefficient 1·2% [0·1-9·5]; p=0·14).InterpretationOur findings highlight the importance of environmental and societal factors as potential explanations of the observed regional disparities in COVID-19 outcomes among people with rheumatic disease and lay foundation for a new research agenda to address these disparities.FundingAmerican College of Rheumatology and European Alliance of Associations for Rheumatology.
| S-EPMC9313519 | biostudies-literature
Project description:BackgroundCharacterizations of coronavirus disease 2019 (COVID-19) vaccine breakthrough infections are limited. We aim to characterize breakthrough infections and identify risk factors associated with outcomes.MethodsThis was a retrospective case series of consecutive fully vaccinated patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a multicenter academic center in Southeast Michigan, between December 30, 2020, and September 15, 2021.ResultsA total of 982 patients were identified; the mean age was 57.9 years, 565 (59%) were female, 774 (79%) were White, and 255 (26%) were health care workers (HCWs). The median number of comorbidities was 2; 225 (23%) were immunocompromised. BNT162b2 was administered to 737 (75%) individuals. The mean time to SARS-CoV-2 detection was 135 days. The majority were asymptomatic or exhibited mild to moderate disease, 154 (16%) required hospitalization, 127 (13%) had severe-critical illness, and 19 (2%) died. Age (odds ratio [OR], 1.14; 95% CI, 1.04-1.07; P < .001), cardiovascular disease (OR, 3.02; 95% CI, 1.55-5.89; P = .001), and immunocompromised status (OR, 2.57; 95% CI, 1.70-3.90; P < .001) were independent risk factors for hospitalization. Additionally, age (OR, 1.06; 95% CI, 1.02-1.11; P = .006) was significantly associated with mortality. HCWs (OR, 0.15; 95% CI, 0.05-0.50; P = .002) were less likely to be hospitalized, and prior receipt of BNT162b2 was associated with lower odds of hospitalization (OR, 0.436; 95% CI, 0.303-0.626; P < .001) and/or death (OR, 0.360; 95% CI, 0.145-0.898; P = .029).ConclusionsCOVID-19 vaccines remain effective at attenuating disease severity. However, patients with breakthrough infections necessitating hospitalization may benefit from early treatment modalities and COVID-19-mitigating strategies, especially in areas with substantial or high transmission rates.
| S-EPMC8903475 | biostudies-literature
Project description:BackgroundBiological evidence suggests ursodeoxycholic acid (UDCA)-a common treatment of cholestatic liver disease-may prevent severe COVID-19 outcomes. We aimed to compare the hazard of COVID-19 hospitalisation or death between UDCA users versus non-users in a population with primary biliary cholangitis (PBC) or primary sclerosing cholangitis (PSC).MethodsWith the approval of NHS England, we conducted a population-based cohort study using primary care records between 1 March 2020 and 31 December 2022, linked to death registration data and hospital records through the OpenSAFELY-TPP platform. Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for the association between time-varying UDCA exposure and COVID-19 related hospitalisation or death, stratified by geographical region and considering models unadjusted and fully adjusted for pre-specified confounders.ResultsWe identify 11,305 eligible individuals, 640 were hospitalised or died with COVID-19 during follow-up, 400 (63%) events among UDCA users. After confounder adjustment, UDCA is associated with a 21% relative reduction in the hazard of COVID-19 hospitalisation or death (HR 0.79, 95% CI 0.67-0.93), consistent with an absolute risk reduction of 1.35% (95% CI 1.07%-1.69%).ConclusionsWe found evidence that UDCA is associated with a lower hazard of COVID-19 related hospitalisation and death, support calls for clinical trials investigating UDCA as a preventative measure for severe COVID-19 outcomes.
| S-EPMC11576861 | biostudies-literature