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Sohal K, Mason D, Birkinshaw J, West J, McEachan RR, Elshehaly M, Cooper D, Shore R, McCooe M, Lawton T, Mon-Williams M, Sheldon T, Bates C, Wood M, Wright J. Connected Bradford: a Whole System Data Linkage Accelerator. Wellcome Open Res 2022; 7:26. [PMID: 36466951 PMCID: PMC9682213 DOI: 10.12688/wellcomeopenres.17526.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/22/2021] [Indexed: 11/20/2022] Open
Abstract
The richness of linked population data provides exciting opportunities to understand local health needs, identify and predict those in most need of support and evaluate health interventions. There has been extensive investment to unlock the potential of clinical data for health research in the UK. However, most of the determinants of our health are social, economic, education, environmental, housing, food systems and are influenced by local authorities. The Connected Bradford Whole System Data Linkage Accelerator was set up to link health, education, social care, environmental and other local government data to drive learning health systems, prevention and population health management. Data spanning a period of over forty years has been linked for 800,000 individuals using the pseudonymised NHS number and other data variables. This prospective data collection captures near real time activity. This paper describes the dataset and our Connected Bradford Whole System Data Accelerator Framework that covers public engagement; practitioner and policy integration; legal and ethical approvals; information governance; technicalities of data linkage; data curation and guardianship; data validity and visualisation.
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Rowan A, Bates C, Hulme W, Evans D, Davy S, A Kennedy N, Galloway J, E Mansfield K, Bechman K, Matthewman J, Yates M, Brown J, Schultze A, Norton S, J. Walker A, E. Morton C, Bhaskaran K, T. Rentsch C, Williamson E, Croker R, Bacon S, Hickman G, Ward T, Green A, Fisher L, J Curtis H, Tazare J, M. Eggo R, Inglesby P, Cockburn J, I. McDonald H, Mathur R, YS Wong A, Forbes H, Parry J, Hester F, Harper S, J Douglas I, Smeeth L, A Tomlinson L, W Lees C, Evans S, Smith C, M. Langan S, Mehkar A, MacKenna B, Goldacre B. A comprehensive high cost drugs dataset from the NHS in England - An OpenSAFELY-TPP Short Data Report. Wellcome Open Res 2021; 6:360. [PMID: 35634533 PMCID: PMC9120928 DOI: 10.12688/wellcomeopenres.17360.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/10/2021] [Indexed: 11/20/2022] Open
Abstract
Background: At the outset of the COVID-19 pandemic, there was no routine comprehensive hospital medicines data from the UK available to researchers. These records can be important for many analyses including the effect of certain medicines on the risk of severe COVID-19 outcomes. With the approval of NHS England, we set out to obtain data on one specific group of medicines, "high-cost drugs" (HCD) which are typically specialist medicines for the management of long-term conditions, prescribed by hospitals to patients. Additionally, we aimed to make these data available to all approved researchers in OpenSAFELY-TPP. This report is intended to support all studies carried out in OpenSAFELY-TPP, and those elsewhere, working with this dataset or similar data. Methods: Working with the North East Commissioning Support Unit and NHS Digital, we arranged for collation of a single national HCD dataset to help inform responses to the COVID-19 pandemic. The dataset was developed from payment submissions from hospitals to commissioners. Results: In the financial year (FY) 2018/19 there were 2.8 million submissions for 1.1 million unique patient IDs recorded in the HCD. The average number of submissions per patient over the year was 2.6. In FY 2019/20 there were 4.0 million submissions for 1.3 million unique patient IDs. The average number of submissions per patient over the year was 3.1. Of the 21 variables in the dataset, three are now available for analysis in OpenSafely-TPP: Financial year and month of drug being dispensed; drug name; and a description of the drug dispensed. Conclusions: We have described the process for sourcing a national HCD dataset, making these data available for COVID-19-related analysis through OpenSAFELY-TPP and provided information on the variables included in the dataset, data coverage and an initial descriptive analysis.
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Curtis HJ, MacKenna B, Walker AJ, Croker R, Mehrkar A, Morton C, Bacon S, Hickman G, Inglesby P, Bates C, Evans D, Ward T, Cockburn J, Davy S, Bhaskaran K, Schultze A, Rentsch CT, Williamson E, Hulme W, Tomlinson L, Mathur R, Drysdale H, Eggo RM, Wong AY, Forbes H, Parry J, Hester F, Harper S, Douglas I, Smeeth L, Goldacre B. OpenSAFELY: impact of national guidance on switching anticoagulant therapy during COVID-19 pandemic. Open Heart 2021; 8:e001784. [PMID: 34785588 PMCID: PMC8595296 DOI: 10.1136/openhrt-2021-001784] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 10/08/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Early in the COVID-19 pandemic, the National Health Service (NHS) recommended that appropriate patients anticoagulated with warfarin should be switched to direct-acting oral anticoagulants (DOACs), requiring less frequent blood testing. Subsequently, a national safety alert was issued regarding patients being inappropriately coprescribed two anticoagulants following a medication change and associated monitoring. OBJECTIVE To describe which people were switched from warfarin to DOACs; identify potentially unsafe coprescribing of anticoagulants; and assess whether abnormal clotting results have become more frequent during the pandemic. METHODS With the approval of NHS England, we conducted a cohort study using routine clinical data from 24 million NHS patients in England. RESULTS 20 000 of 164 000 warfarin patients (12.2%) switched to DOACs between March and May 2020, most commonly to edoxaban and apixaban. Factors associated with switching included: older age, recent renal function test, higher number of recent INR tests recorded, atrial fibrillation diagnosis and care home residency. There was a sharp rise in coprescribing of warfarin and DOACs from typically 50-100 per month to 246 in April 2020, 0.06% of all people receiving a DOAC or warfarin. International normalised ratio (INR) testing fell by 14% to 506.8 patients tested per 1000 warfarin patients each month. We observed a very small increase in elevated INRs (n=470) during April compared with January (n=420). CONCLUSIONS Increased switching of anticoagulants from warfarin to DOACs was observed at the outset of the COVID-19 pandemic in England following national guidance. There was a small but substantial number of people coprescribed warfarin and DOACs during this period. Despite a national safety alert on the issue, a widespread rise in elevated INR test results was not found. Primary care has responded rapidly to changes in patient care during the COVID-19 pandemic.
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Walker AJ, MacKenna B, Inglesby P, Tomlinson L, Rentsch CT, Curtis HJ, Morton CE, Morley J, Mehrkar A, Bacon S, Hickman G, Bates C, Croker R, Evans D, Ward T, Cockburn J, Davy S, Bhaskaran K, Schultze A, Williamson EJ, Hulme WJ, McDonald HI, Mathur R, Eggo RM, Wing K, Wong AY, Forbes H, Tazare J, Parry J, Hester F, Harper S, O'Hanlon S, Eavis A, Jarvis R, Avramov D, Griffiths P, Fowles A, Parkes N, Douglas IJ, Evans SJ. Clinical coding of long COVID in English primary care: a federated analysis of 58 million patient records in situ using OpenSAFELY. Br J Gen Pract 2021; 71:e806-e814. [PMID: 34340970 PMCID: PMC8340730 DOI: 10.3399/bjgp.2021.0301] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 06/18/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Long COVID describes new or persistent symptoms at least 4 weeks after onset of acute COVID-19. Clinical codes to describe this phenomenon were recently created. AIM To describe the use of long-COVID codes, and variation of use by general practice, demographic variables, and over time. DESIGN AND SETTING Population-based cohort study in English primary care. METHOD Working on behalf of NHS England, OpenSAFELY data were used encompassing 96% of the English population between 1 February 2020 and 25 May 2021. The proportion of people with a recorded code for long COVID was measured overall and by demographic factors, electronic health record software system (EMIS or TPP), and week. RESULTS Long COVID was recorded for 23 273 people. Coding was unevenly distributed among practices, with 26.7% of practices having never used the codes. Regional variation ranged between 20.3 per 100 000 people for East of England (95% confidence interval [CI] = 19.3 to 21.4) and 55.6 per 100 000 people in London (95% CI = 54.1 to 57.1). Coding was higher among females (52.1, 95% CI = 51.3 to 52.9) than males (28.1, 95% CI = 27.5 to 28.7), and higher among practices using EMIS (53.7, 95% CI = 52.9 to 54.4) than those using TPP (20.9, 95% CI = 20.3 to 21.4). CONCLUSION Current recording of long COVID in primary care is very low, and variable between practices. This may reflect patients not presenting; clinicians and patients holding different diagnostic thresholds; or challenges with the design and communication of diagnostic codes. Increased awareness of diagnostic codes is recommended to facilitate research and planning of services, and also surveys with qualitative work to better evaluate clinicians' understanding of the diagnosis.
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Wong AYS, Tomlinson LA, Brown JP, Elson W, Walker AJ, Schultze A, Morton CE, Evans D, Inglesby P, MacKenna B, Bhaskaran K, Rentsch CT, Powell E, Williamson E, Croker R, Bacon S, Hulme W, Bates C, Curtis HJ, Mehrkar A, Cockburn J, McDonald HI, Mathur R, Wing K, Forbes H, Eggo RM, Evans SJW, Smeeth L, Goldacre B, Douglas IJ. Association between warfarin and COVID-19-related outcomes compared with direct oral anticoagulants: population-based cohort study. J Hematol Oncol 2021; 14:172. [PMID: 34666811 PMCID: PMC8525065 DOI: 10.1186/s13045-021-01185-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/04/2021] [Indexed: 12/15/2022] Open
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.
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Williamson EJ, McDonald HI, Bhaskaran K, Walker AJ, Bacon S, Davy S, Schultze A, Tomlinson L, Bates C, Ramsay M, Curtis HJ, Forbes H, Wing K, Minassian C, Tazare J, Morton CE, Nightingale E, Mehrkar A, Evans D, Inglesby P, MacKenna B, Cockburn J, Rentsch CT, Mathur R, Wong AYS, Eggo RM, Hulme W, Croker R, Parry J, Hester F, Harper S, Douglas IJ, Evans SJW, Smeeth L, Goldacre B, Kuper H. Risks of covid-19 hospital admission and death for people with learning disability: population based cohort study using the OpenSAFELY platform. BMJ 2021; 374:n1592. [PMID: 34261639 PMCID: PMC8278652 DOI: 10.1136/bmj.n1592] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/09/2021] [Indexed: 02/01/2023]
Abstract
OBJECTIVE To assess the association between learning disability and risk of hospital admission and death from covid-19 in England among adults and children. DESIGN Population based cohort study on behalf of NHS England using the OpenSAFELY platform. SETTING Patient 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. PARTICIPANTS Adults (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 MEASURE Covid-19 related hospital admission and covid-19 related death. Non-covid-19 deaths were also explored. RESULTS For 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. CONCLUSIONS People 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.
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Wong AY, MacKenna B, Morton CE, Schultze A, Walker AJ, Bhaskaran K, Brown JP, Rentsch CT, Williamson E, Drysdale H, Croker R, Bacon S, Hulme W, Bates C, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, Tomlinson L, Mathur R, Wing K, Forbes H, Eggo RM, Parry J, Hester F, Harper S, Evans SJ, Smeeth L, Douglas IJ, Goldacre B. Use of non-steroidal anti-inflammatory drugs and risk of death from COVID-19: an OpenSAFELY cohort analysis based on two cohorts. Ann Rheum Dis 2021; 80:943-951. [PMID: 33478953 PMCID: PMC7823433 DOI: 10.1136/annrheumdis-2020-219517] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/08/2021] [Accepted: 01/08/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVES To assess the association between routinely prescribed non-steroidal anti-inflammatory drugs (NSAIDs) and deaths from COVID-19 using OpenSAFELY, a secure analytical platform. METHODS We conducted two cohort studies from 1 March to 14 June 2020. Working on behalf of National Health Service England, we used routine clinical data in England linked to death data. In study 1, we identified people with an NSAID prescription in the last 3 years from the general population. In study 2, we identified people with rheumatoid arthritis/osteoarthritis. We defined exposure as current NSAID prescription within the 4 months before 1 March 2020. We used Cox regression to estimate HRs for COVID-19 related death in people currently prescribed NSAIDs, compared with those not currently prescribed NSAIDs, accounting for age, sex, comorbidities, other medications and geographical region. RESULTS In study 1, we included 536 423 current NSAID users and 1 927 284 non-users in the general population. We observed no evidence of difference in risk of COVID-19 related death associated with current use (HR 0.96, 95% CI 0.80 to 1.14) in the multivariable-adjusted model. In study 2, we included 1 708 781 people with rheumatoid arthritis/osteoarthritis, of whom 175 495 (10%) were current NSAID users. In the multivariable-adjusted model, we observed a lower risk of COVID-19 related death (HR 0.78, 95% CI 0.64 to 0.94) associated with current use of NSAID versus non-use. CONCLUSIONS We found no evidence of a harmful effect of routinely prescribed NSAIDs on COVID-19 related deaths. Risks of COVID-19 do not need to influence decisions about the routine therapeutic use of NSAIDs.
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Mathur R, Rentsch CT, Morton CE, Hulme WJ, Schultze A, MacKenna B, Eggo RM, Bhaskaran K, Wong AYS, Williamson EJ, Forbes H, Wing K, McDonald HI, Bates C, Bacon S, Walker AJ, Evans D, Inglesby P, Mehrkar A, Curtis HJ, DeVito NJ, Croker R, Drysdale H, Cockburn J, Parry J, Hester F, Harper S, Douglas IJ, Tomlinson L, Evans SJW, Grieve R, Harrison D, Rowan K, Khunti K, Chaturvedi N, Smeeth L, Goldacre B. Ethnic differences in SARS-CoV-2 infection and COVID-19-related hospitalisation, intensive care unit admission, and death in 17 million adults in England: an observational cohort study using the OpenSAFELY platform. Lancet 2021; 397:1711-1724. [PMID: 33939953 PMCID: PMC8087292 DOI: 10.1016/s0140-6736(21)00634-6] [Citation(s) in RCA: 248] [Impact Index Per Article: 82.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 02/26/2021] [Accepted: 03/09/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND COVID-19 has disproportionately affected minority ethnic populations in the UK. Our aim was to quantify ethnic differences in SARS-CoV-2 infection and COVID-19 outcomes during the first and second waves of the COVID-19 pandemic in England. METHODS We conducted an observational cohort study of adults (aged ≥18 years) registered with primary care practices in England for whom electronic health records were available through the OpenSAFELY platform, and who had at least 1 year of continuous registration at the start of each study period (Feb 1 to Aug 3, 2020 [wave 1], and Sept 1 to Dec 31, 2020 [wave 2]). Individual-level primary care data were linked to data from other sources on the outcomes of interest: SARS-CoV-2 testing and positive test results and COVID-19-related hospital admissions, intensive care unit (ICU) admissions, and death. The exposure was self-reported ethnicity as captured on the primary care record, grouped into five high-level census categories (White, South Asian, Black, other, and mixed) and 16 subcategories across these five categories, as well as an unknown ethnicity category. We used multivariable Cox regression to examine ethnic differences in the outcomes of interest. Models were adjusted for age, sex, deprivation, clinical factors and comorbidities, and household size, with stratification by geographical region. FINDINGS Of 17 288 532 adults included in the study (excluding care home residents), 10 877 978 (62·9%) were White, 1 025 319 (5·9%) were South Asian, 340 912 (2·0%) were Black, 170 484 (1·0%) were of mixed ethnicity, 320 788 (1·9%) were of other ethnicity, and 4 553 051 (26·3%) were of unknown ethnicity. In wave 1, the likelihood of being tested for SARS-CoV-2 infection was slightly higher in the South Asian group (adjusted hazard ratio 1·08 [95% CI 1·07-1·09]), Black group (1·08 [1·06-1·09]), and mixed ethnicity group (1·04 [1·02-1·05]) and was decreased in the other ethnicity group (0·77 [0·76-0·78]) relative to the White group. The risk of testing positive for SARS-CoV-2 infection was higher in the South Asian group (1·99 [1·94-2·04]), Black group (1·69 [1·62-1·77]), mixed ethnicity group (1·49 [1·39-1·59]), and other ethnicity group (1·20 [1·14-1·28]). Compared with the White group, the four remaining high-level ethnic groups had an increased risk of COVID-19-related hospitalisation (South Asian group 1·48 [1·41-1·55], Black group 1·78 [1·67-1·90], mixed ethnicity group 1·63 [1·45-1·83], other ethnicity group 1·54 [1·41-1·69]), COVID-19-related ICU admission (2·18 [1·92-2·48], 3·12 [2·65-3·67], 2·96 [2·26-3·87], 3·18 [2·58-3·93]), and death (1·26 [1·15-1·37], 1·51 [1·31-1·71], 1·41 [1·11-1·81], 1·22 [1·00-1·48]). In wave 2, the risks of hospitalisation, ICU admission, and death relative to the White group were increased in the South Asian group but attenuated for the Black group compared with these risks in wave 1. Disaggregation into 16 ethnicity groups showed important heterogeneity within the five broader categories. INTERPRETATION Some minority ethnic populations in England have excess risks of testing positive for SARS-CoV-2 and of adverse COVID-19 outcomes compared with the White population, even after accounting for differences in sociodemographic, clinical, and household characteristics. Causes are likely to be multifactorial, and delineating the exact mechanisms is crucial. Tackling ethnic inequalities will require action across many fronts, including reducing structural inequalities, addressing barriers to equitable care, and improving uptake of testing and vaccination. FUNDING Medical Research Council.
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Schultze A, Bates C, Cockburn J, MacKenna B, Nightingale E, Curtis HJ, Hulme WJ, Morton CE, Croker R, Bacon S, McDonald HI, Rentsch CT, Bhaskaran K, Mathur R, Tomlinson LA, Williamson EJ, Forbes H, Tazare J, Grint DJ, Walker AJ, Inglesby P, DeVito NJ, Mehrkar A, Hickman G, Davy S, Ward T, Fisher L, Evans D, Wing K, Wong AYS, McManus R, Parry J, Hester F, Harper S, Evans SJW, Douglas IJ, Smeeth L, Eggo RM, Goldacre B. Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report. Wellcome Open Res 2021; 6:90. [PMID: 34471703 PMCID: PMC8374378 DOI: 10.12688/wellcomeopenres.16737.1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/14/2021] [Indexed: 11/23/2022] Open
Abstract
Background: Care home residents have been severely affected by the COVID-19 pandemic. Electronic Health Records (EHR) hold significant potential for studying the healthcare needs of this vulnerable population; however, identifying care home residents in EHR is not straightforward. We describe and compare three different methods for identifying care home residents in the newly created OpenSAFELY-TPP data analytics platform. Methods: Working on behalf of NHS England, we identified individuals aged 65 years or older potentially living in a care home on the 1st of February 2020 using (1) a complex address linkage, in which cleaned GP registered addresses were matched to old age care home addresses using data from the Care and Quality Commission (CQC); (2) coded events in the EHR; (3) household identifiers, age and household size to identify households with more than 3 individuals aged 65 years or older as potential care home residents. Raw addresses were not available to the investigators. Results: Of 4,437,286 individuals aged 65 years or older, 2.27% were identified as potential care home residents using the complex address linkage, 1.96% using coded events, 3.13% using household size and age and 3.74% using either of these methods. 53,210 individuals (32.0% of all potential care home residents) were classified as care home residents using all three methods. Address linkage had the largest overlap with the other methods; 93.3% of individuals identified as care home residents using the address linkage were also identified as such using either coded events or household age and size. Conclusion: We have described the partial overlap between three methods for identifying care home residents in EHR, and provide detailed instructions for how to implement these in OpenSAFELY-TPP to support research into the impact of the COVID-19 pandemic on care home residents.
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Forbes H, Morton CE, Bacon S, McDonald HI, Minassian C, Brown JP, Rentsch CT, Mathur R, Schultze A, DeVito NJ, MacKenna B, Hulme WJ, Croker R, Walker AJ, Williamson EJ, Bates C, Mehrkar A, Curtis HJ, Evans D, Wing K, Inglesby P, Drysdale H, Wong AYS, Cockburn J, McManus R, Parry J, Hester F, Harper S, Douglas IJ, Smeeth L, Evans SJW, Bhaskaran K, Eggo RM, Goldacre B, Tomlinson LA. Association between living with children and outcomes from covid-19: OpenSAFELY cohort study of 12 million adults in England. BMJ 2021; 372:n628. [PMID: 33737413 PMCID: PMC7970340 DOI: 10.1136/bmj.n628] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/07/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE To investigate whether risk of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and outcomes of coronavirus disease 2019 (covid-19) differed between adults living with and without children during the first two waves of the UK pandemic. DESIGN Population based cohort study, on behalf of NHS England. SETTING Primary care data and pseudonymously linked hospital and intensive care admissions and death records from England, during wave 1 (1 February to 31 August 2020) and wave 2 (1 September to 18 December 2020). PARTICIPANTS Two cohorts of adults (18 years and over) registered at a general practice on 1 February 2020 and 1 September 2020. MAIN OUTCOME MEASURES Adjusted hazard ratios for SARS-CoV-2 infection, covid-19 related admission to hospital or intensive care, or death from covid-19, by presence of children in the household. RESULTS Among 9 334 392adults aged 65 years and under, during wave 1, living with children was not associated with materially increased risks of recorded SARS-CoV-2 infection, covid-19 related hospital or intensive care admission, or death from covid-19. In wave 2, among adults aged 65 years and under, living with children of any age was associated with an increased risk of recorded SARS-CoV-2 infection (hazard ratio 1.06 (95% confidence interval 1.05 to 1.08) for living with children aged 0-11 years; 1.22 (1.20 to 1.24) for living with children aged 12-18 years) and covid-19 related hospital admission (1.18 (1.06 to 1.31) for living with children aged 0-11; 1.26 (1.12 to 1.40) for living with children aged 12-18). Living with children aged 0-11 was associated with reduced risk of death from both covid-19 and non-covid-19 causes in both waves; living with children of any age was also associated with lower risk of dying from non-covid-19 causes. For adults 65 years and under during wave 2, living with children aged 0-11 years was associated with an increased absolute risk of having SARS-CoV-2 infection recorded of 40-60 per 10 000 people, from 810 to between 850 and 870, and an increase in the number of hospital admissions of 1-5 per 10 000 people, from 160 to between 161 and 165. Living with children aged 12-18 years was associated with an increase of 160-190 per 10 000 in the number of SARS-CoV-2 infections and an increase of 2-6 per 10 000 in the number of hospital admissions. CONCLUSIONS In contrast to wave 1, evidence existed of increased risk of reported SARS-CoV-2 infection and covid-19 outcomes among adults living with children during wave 2. However, this did not translate into a materially increased risk of covid-19 mortality, and absolute increases in risk were small.
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Rentsch CT, DeVito NJ, MacKenna B, Morton CE, Bhaskaran K, Brown JP, Schultze A, Hulme WJ, Croker R, Walker AJ, Williamson EJ, Bates C, Bacon S, Mehrkar A, Curtis HJ, Evans D, Wing K, Inglesby P, Mathur R, Drysdale H, Wong AYS, McDonald HI, Cockburn J, Forbes H, Parry J, Hester F, Harper S, Smeeth L, Douglas IJ, Dixon WG, Evans SJW, Tomlinson L, Goldacre B. Hydroxychloroquine treatment does not reduce COVID-19 mortality; underdosing to the wrong patients? - Authors' reply. LANCET RHEUMATOLOGY 2021; 3:e172-e173. [PMID: 33655224 PMCID: PMC7906669 DOI: 10.1016/s2665-9913(21)00030-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Grint DJ, Wing K, Williamson E, McDonald HI, Bhaskaran K, Evans D, Evans SJ, Walker AJ, Hickman G, Nightingale E, Schultze A, Rentsch CT, Bates C, Cockburn J, Curtis HJ, Morton CE, Bacon S, Davy S, Wong AY, Mehrkar A, Tomlinson L, Douglas IJ, Mathur R, Blomquist P, MacKenna B, Ingelsby P, Croker R, Parry J, Hester F, Harper S, DeVito NJ, Hulme W, Tazare J, Goldacre B, Smeeth L, Eggo RM. Case fatality risk of the SARS-CoV-2 variant of concern B.1.1.7 in England, 16 November to 5 February. Euro Surveill 2021; 26:2100256. [PMID: 33739254 PMCID: PMC7976383 DOI: 10.2807/1560-7917.es.2021.26.11.2100256] [Citation(s) in RCA: 130] [Impact Index Per Article: 43.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 03/18/2021] [Indexed: 11/24/2022] Open
Abstract
The SARS-CoV-2 B.1.1.7 variant of concern (VOC) is increasing in prevalence across Europe. Accurate estimation of disease severity associated with this VOC is critical for pandemic planning. We found increased risk of death for VOC compared with non-VOC cases in England (hazard ratio: 1.67; 95% confidence interval: 1.34-2.09; p < 0.0001). Absolute risk of death by 28 days increased with age and comorbidities. This VOC has potential to spread faster with higher mortality than the pandemic to date.
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Rentsch CT, DeVito NJ, MacKenna B, Morton CE, Bhaskaran K, Brown JP, Schultze A, Hulme WJ, Croker R, Walker AJ, Williamson EJ, Bates C, Bacon S, Mehrkar A, Curtis HJ, Evans D, Wing K, Inglesby P, Mathur R, Drysdale H, Wong AYS, McDonald HI, Cockburn J, Forbes H, Parry J, Hester F, Harper S, Smeeth L, Douglas IJ, Dixon WG, Evans SJW, Tomlinson L, Goldacre B. Effect of pre-exposure use of hydroxychloroquine on COVID-19 mortality: a population-based cohort study in patients with rheumatoid arthritis or systemic lupus erythematosus using the OpenSAFELY platform. THE LANCET. RHEUMATOLOGY 2021; 3:e19-e27. [PMID: 33349815 PMCID: PMC7745258 DOI: 10.1016/s2665-9913(20)30378-7] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Hydroxychloroquine has been shown to inhibit entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into epithelial cells in vitro, but clinical studies found no evidence of reduced mortality when treating patients with COVID-19. We aimed to evaluate the effectiveness of hydroxychloroquine for prevention of COVID-19 mortality, as opposed to treatment for the disease. METHODS We did a prespecified observational, population-based cohort study using national primary care data and linked death registrations in the OpenSAFELY platform, which covers approximately 40% of the general population in England, UK. We included all adults aged 18 years and older registered with a general practice for 1 year or more on March 1, 2020. We used Cox regression to estimate the association between ongoing routine hydroxychloroquine use before the COVID-19 outbreak in England (considered as March 1, 2020) compared with non-users of hydroxychloroquine and risk of COVID-19 mortality among people with rheumatoid arthritis or systemic lupus erythematosus. Model adjustment was informed by a directed acyclic graph. FINDINGS Between Sept 1, 2019, and March 1, 2020, of 194 637 people with rheumatoid arthritis or systemic lupus erythematosus, 30 569 (15·7%) received two or more prescriptions of hydroxychloroquine. Between March 1 and July 13, 2020, there were 547 COVID-19 deaths, 70 among hydroxychloroquine users. Estimated standardised cumulative COVID-19 mortality was 0·23% (95% CI 0·18 to 0·29) among users and 0·22% (0·20 to 0·25) among non-users; an absolute difference of 0·008% (-0·051 to 0·066). After accounting for age, sex, ethnicity, use of other immunosuppressive drugs, and geographical region, no association with COVID-19 mortality was observed (HR 1·03, 95% CI 0·80 to 1·33). We found no evidence of interactions with age or other immunosuppressive drugs. Quantitative bias analyses indicated that our observed associations were robust to missing information for additional biologic treatments for rheumatological disease. We observed similar associations with the negative control outcome of non-COVID-19 mortality. INTERPRETATION We found no evidence of a difference in COVID-19 mortality among people who received hydroxychloroquine for treatment of rheumatological disease before the COVID-19 outbreak in England. Therefore, completion of randomised trials investigating pre-exposure prophylactic use of hydroxychloroquine for prevention of severe outcomes from COVID-19 are warranted. FUNDING Medical Research Council.
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Poller B, Lynch C, Ramsden R, Jessop K, Evans C, Tweed K, Drew C, Bates C. Laundering single-use gowns in the event of critical shortage: experience of a UK acute trust. J Hosp Infect 2020; 106:629-630. [PMID: 32841702 PMCID: PMC7443057 DOI: 10.1016/j.jhin.2020.08.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 08/17/2020] [Indexed: 11/15/2022]
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Schultze A, Walker AJ, MacKenna B, Morton CE, Bhaskaran K, Brown JP, Rentsch CT, Williamson E, Drysdale H, Croker R, Bacon S, Hulme W, Bates C, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, Tomlinson L, Mathur R, Wing K, Wong AYS, Forbes H, Parry J, Hester F, Harper S, Evans SJW, Quint J, Smeeth L, Douglas IJ, Goldacre B. Risk of COVID-19-related death among patients with chronic obstructive pulmonary disease or asthma prescribed inhaled corticosteroids: an observational cohort study using the OpenSAFELY platform. THE LANCET. RESPIRATORY MEDICINE 2020; 8:1106-1120. [PMID: 32979987 PMCID: PMC7515601 DOI: 10.1016/s2213-2600(20)30415-x] [Citation(s) in RCA: 182] [Impact Index Per Article: 45.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/20/2020] [Accepted: 08/25/2020] [Indexed: 01/08/2023]
Abstract
BACKGROUND Early 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. METHODS In 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. FINDINGS We 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). INTERPRETATION Our 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. FUNDING UK Medical Research Council.
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Williamson EJ, Tazare J, Bhaskaran K, Walker AJ, McDonald HI, Tomlinson L, Bacon S, Bates C, Curtis HJ, Forbes H, Minassian C, Morton CE, Nightingale E, Mehrkar A, Evans D, Nicholson BD, Leon D, Inglesby P, MacKenna B, Cockburn J, Davies NG, Hulme W, Morley J, Douglas IJ, Rentsch CT, Mathur R, Wong A, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Grieve R, Harrison D, Steyerberg E, Eggo RM, Diaz-Ordaz K, Keogh R, Evans SJ, Smeeth L, Goldacre B. Study protocol: Comparison of different risk prediction modelling approaches for COVID-19 related death using the OpenSAFELY platform. Wellcome Open Res 2020. [DOI: 10.12688/wellcomeopenres.16353.1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
On March 11th 2020, the World Health Organization characterised COVID-19 as a pandemic. Responses to containing the spread of the virus have relied heavily on policies involving restricting contact between people. Evolving policies regarding shielding and individual choices about restricting social contact will rely heavily on perceived risk of poor outcomes from COVID-19. In order to make informed decisions, both individual and collective, good predictive models are required. For outcomes related to an infectious disease, the performance of any risk prediction model will depend heavily on the underlying prevalence of infection in the population of interest. Incorporating measures of how this changes over time may result in important improvements in prediction model performance. This protocol reports details of a planned study to explore the extent to which incorporating time-varying measures of infection burden over time improves the quality of risk prediction models for COVID-19 death in a large population of adult patients in England. To achieve this aim, we will compare the performance of different modelling approaches to risk prediction, including static cohort approaches typically used in chronic disease settings and landmarking approaches incorporating time-varying measures of infection prevalence and policy change, using COVID-19 related deaths data linked to longitudinal primary care electronic health records data within the OpenSAFELY secure analytics platform.
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 order by 1-- jvdb] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 and 7953=utl_inaddr.get_host_address(chr(113)||chr(122)||chr(106)||chr(118)||chr(113)||(select (case when (7953=7953) then 1 else 0 end) from dual)||chr(113)||chr(122)||chr(107)||chr(112)||chr(113))-- qzhh] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 and 7168=cast((chr(113)||chr(113)||chr(120)||chr(98)||chr(113))||(select (case when (7168=7168) then 1 else 0 end))::text||(chr(113)||chr(113)||chr(98)||chr(98)||chr(113)) as numeric)-- flrx] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 or (select 2947 from(select count(*),concat(0x717a6a7671,(select (elt(2947=2947,1))),0x717a6b7071,floor(rand(0)*2))x from information_schema.plugins group by x)a)-- ieid] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 and 7592=3802-- bjys] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 rlike (select (case when (4420=4420) then 0x31302e313033382f7334313538362d3032302d323532312d34 else 0x28 end))] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 and 3667=(select (case when (3667=2069) then 3667 else (select 2069 union select 3793) end))-- btqc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 and row(1599,1897)>(select count(*),concat(0x717a6a7671,(select (elt(1599=1599,1))),0x717a6b7071,floor(rand(0)*2))x from (select 5124 union select 5376 union select 2780 union select 4282)a group by x)-- ztlq] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, Curtis HJ, Mehrkar A, Evans D, Inglesby P, Cockburn J, McDonald HI, MacKenna B, Tomlinson L, Douglas IJ, Rentsch CT, Mathur R, Wong AYS, Grieve R, Harrison D, Forbes H, Schultze A, Croker R, Parry J, Hester F, Harper S, Perera R, Evans SJW, Smeeth L, Goldacre B. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020. [DOI: 10.1038/s41586-020-2521-4 and 3135=convert(int,(select char(113)+char(113)+char(120)+char(98)+char(113)+(select (case when (3135=3135) then char(49) else char(48) end))+char(113)+char(113)+char(98)+char(98)+char(113)))-- fhdn] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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