Abstract: factors associated with COVID-19
Background: factors associated with COVID-19
Establishing who is at risk from a novel rapidly arising cause of death, and why, requires a new approach to epidemiological research with very large datasets and timely data. Working on behalf of NHS England we, therefore, set out to deliver a secure and pseudonymized analytics platform inside the data center of a major primary care electronic health records vendor establishing coverage across detailed primary care records for a substantial proportion of all patients in England. The following results are preliminary. Data sources: Primary care electronic health records managed by the electronic health record vendor TPP, pseudonymous linked to patient-level data from the COVID-19 Patient Notification System (CPNS) for the death of hospital inpatients with confirmed COVID-19, using the new OpenSAFELY platform.
Population: 17,425,445 adults. Time period: 1st Feb 2020 to 25th April 2020. Primary outcome: Death in hospital among people with confirmed COVID-19.
Cohort study analyzed by Cox regression to generate hazard ratios: age and sex-adjusted, and multiply adjusted for covariates selected prospectively on the basis of clinical interest and prior findings. Results: There were 5683 deaths attributed to COVID-19. In summary after full adjustment, death from COVID-19 was strongly associated with: being male (hazard ratio 1.99, 95%CI 1.88-2.10); older age and deprivation (both with a strong gradient); uncontrolled diabetes (HR 2.36 95% CI 2.18-2.56); severe asthma (HR 1.25 CI 1.08-1.44); and various other prior medical conditions. Compared to people with ethnicity recorded as white, black people were at higher risk of death, with only partial attenuation in hazard ratios from the fully adjusted model (age-sex adjusted HR2.17
95% CI 1.84-2.57; fully adjusted HR 1.71 95% CI 1.44-2.02); with similar findings for Asian people (age-sex adjusted HR 1.95 95% CI 1.73-2.18; fully adjusted HR 1.62 95% CI 1.43- 1.82).
DOI: https://doi.org/10.1101/2020.05.06.20092999.this version posted May 7, 2020. The copyright holder for this preprint.
COVID-19, risk factors, ethnicity, deprivation, death, informatics.
On March 11th, 2020, the World Health Organization characterized COVID-19 as a pandemic after 118,000 cases and 4,291 deaths were reported in 114 countries.
1-As of 30 April, cases are over 3 million globally, with more than 200,000 deaths attributed to the virus.
2-In the UK, cases have reached 171,253, with 22,791 deaths in hospitals.
3- Age and genders are well-established risk factors, with over 90% of UK deaths to date being in people aged over 60 years, and 60% of deaths in men.
4-consistent with global patterns. Various pre-existing conditions have been reported to correlate with an increased risk of poor outcomes. In a re-analysis of a large aggregated case the series dataset from the Chinese center for disease control and prevention (44,672 patients, 1,023 deaths), cardiovascular disease, hypertension, diabetes, respiratory disease, and cancers were all associated with increased risk of death.
5-These factors often correlate with age, but correction for age was not possible in the available data. More recently, a large UK cross-sectional survey describing 16,749 patients already hospitalized with COVID-19 showed higher risk of death for patients with cardiac, pulmonary, and kidney disease, as well as malignancy, dementia, and obesity (hazard ratios 1.19-1.39 after age and sex correction).
6-Obesity has been reported as a risk factor for the treatment of the escalation in a French ITU cohort (n=124) and a New York hospital presentation cohort (n=3615).
7,8-The risks associated with smoking are disputed: increased risks were initially reported; recent studies suggest that smokers are underrepresented among those with more severe disease, and a potential protective mechanism for nicotine has been suggested.
9-Smoking prevalence among hospitalized patients was lower than expected in China (1,099 patients, 12.6% vs 28% in the general population),
10- and in a small French study (139 outpatients and 343 inpatients; Standardized Incidence Ratios 0.197 and 0.246, respectively).
11-People from black and minority ethnic (BME) groups are at increased risk of bad outcomes from COVID-19, but explanations for this association are unclear.
12,13- We, therefore, set out to determine factors associated with the risk of death from COVID-19 in England using a very large sample of the adult population, with deaths data linked to longitudinal primary care electronic health records. This is the first iteration, based on the currently available data; further updates and additional outcomes will be released as more data become available through the OpenSAFELY.org platform.
We have quantified a range of clinical risk factors for death from COVID-19, some of which were not previously well characterized, in the largest cohort study conducted by any country to date. People from Asian and black groups are at markedly increased risk of in-hospital death from COVID-19, and contrary to some prior speculation this is only partially attributable to pre-existing clinical risk factors or deprivation; further research into the drivers of this association is therefore urgently required. Deprivation is also a major risk factor with, again, little of the excess risk explained by co-morbidity or other risk factors. The findings for clinical risk factors are concordant with policies in the UK for protecting those at the highest risk. Our Open SAFELY platform is rapidly adding further NHS patients’ records; we will update and extend these results regularly. It is made available under a CC-BY 4.0 International license. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. medRxiv preprint
BG conceived the platform and the approach; BG and LS led the project overall and are guarantors; SB led the software; EW KB led the statistical analysis; CM AW led on code lists and implementation; AM led on IG; Contributions are as follows: Data curation CB JP JC SH SB DE PI CM; Analysis EW KB AW CM; Funding acquisition BG LS; information governance AM BG CB JP; Methodology EW KB AW BG LS CB JP JC SH SB DE PI CM RP; Disease category conceptualization and code lists CM AW PI SB DE CB JC JP SH HD HC KB SB AM BM LT ID HM RM HF JQ;
Ethics approval HC EW LS BG; Project administration CM HC CB SB AM LS BG; Resources BG LS FH; Software SB DE PI AW CM CB FH JC SH; Supervision BG LS SB; Writing (original draft) HC EW KB BM CM AM BG LS; Writing (review & editing) CB CM HC EW KB SB AM BM LT ID HM RM AW SE. All authors were involved in the design and conceptual development and reviewed and approved the final manuscript.
The Kavian Scientific Research Association (KSRA) is a non-profit research organisation to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.
KSRA research association, as a non-profit research firm, is committed to providing research services in the field of knowledge. The main beneficiaries of this association are public or private knowledge-based companies, students, researchers, researchers, professors, universities, and industrial and semi-industrial centers around the world.
Our main services Based on Education for all Spectrum people in the world. We want to make an integration between researches and educations. We believe education is the main right of Human beings. So our services should be concentrated on inclusive education.
The KSRA team partners with local under-served communities around the world to improve the access to and quality of knowledge based on education, amplify and augment learning programs where they exist, and create new opportunities for e-learning where traditional education systems are lacking or non-existent.
FULL Paper PDF file:factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients.
OpenSAFELY: factors associated with COVID-19-related hospital death in the linked Electronic health records of 17 million adult NHS patients.
The OpenSAFELY Collaborative; Elizabeth Williamson2
*, Alex J Walker*, Krishnan Bhaskaran*, Seb Bacon*, Chris Bates*, Caroline E Morton, Helen J Curtis, Amir Mehrkar, David Evans, Peter Inglesby, Jonathan Cockburn, Helen I McDonald, Brian MacKenna, Laurie Tomlinson, Ian J Douglas, Christopher T Rentsch, Rohini Mathur Angel Wong, RichardGrieve, David Harrison, Harriet Forbes
, Anna Schultze, Richard Croker, John Parry, FrankHester, Sam Harper, Raf Perera, Stephen Evans, Liam Smeeth, Ben Goldacre,
The DataLab, Nuffield Dept of Primary Care Health Sciences, University of Oxford, OX2 6GG
2 London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT
3 TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX
4 ICNARC, 24 High Holborn, Holborn, London WC1V 6AZ
5 NIHR Health Protection Research Unit (HPRU) in Immunisation
* Equal contributions † Joint principal investigators ‡ Corresponding: email@example.com
medRxiv preprint DOI: https://doi.org/10.1101/2020.05.06.20092999.this version posted May 7, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.