factors associated with deaths due to covid 19 versus other causes population based CORD-Papers-2022-06-02 (Version 1)

Title: Factors associated with deaths due to COVID-19 versus other causes: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform
Abstract: BACKGROUND: Mortality 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. METHODS: Working 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 1(st) February 2020 and with >1 year of continuous prior registration; the cut-off date for deaths was 9(th) 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. FINDINGS: 17456515 individuals were included. 17063 died from COVID-19 and 134316 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]). INTERPRETATION: Similar 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. FUNDING: Wellcome Royal Society National Institute for Health Research National Institute for Health Research Oxford Biomedical Research Centre UK Medical Research Council Health Data Research UK.
Published: 2021-05-08
Journal: Lancet Reg Health Eur
DOI: 10.1016/j.lanepe.2021.100109
DOI_URL: http://doi.org/10.1016/j.lanepe.2021.100109
Author Name: Bhaskaran Krishnan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/bhaskaran_krishnan
Author Name: Bacon Sebastian
Author link: https://covid19-data.nist.gov/pid/rest/local/author/bacon_sebastian
Author Name: Evans Stephen JW
Author link: https://covid19-data.nist.gov/pid/rest/local/author/evans_stephen_jw
Author Name: Bates Chris J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/bates_chris_j
Author Name: Rentsch Christopher T
Author link: https://covid19-data.nist.gov/pid/rest/local/author/rentsch_christopher_t
Author Name: MacKenna Brian
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mackenna_brian
Author Name: Tomlinson Laurie
Author link: https://covid19-data.nist.gov/pid/rest/local/author/tomlinson_laurie
Author Name: Walker Alex J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/walker_alex_j
Author Name: Schultze Anna
Author link: https://covid19-data.nist.gov/pid/rest/local/author/schultze_anna
Author Name: Morton Caroline E
Author link: https://covid19-data.nist.gov/pid/rest/local/author/morton_caroline_e
Author Name: Grint Daniel
Author link: https://covid19-data.nist.gov/pid/rest/local/author/grint_daniel
Author Name: Mehrkar Amir
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mehrkar_amir
Author Name: Eggo Rosalind M
Author link: https://covid19-data.nist.gov/pid/rest/local/author/eggo_rosalind_m
Author Name: Inglesby Peter
Author link: https://covid19-data.nist.gov/pid/rest/local/author/inglesby_peter
Author Name: Douglas Ian J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/douglas_ian_j
Author Name: McDonald Helen I
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mcdonald_helen_i
Author Name: Cockburn Jonathan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/cockburn_jonathan
Author Name: Williamson Elizabeth J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/williamson_elizabeth_j
Author Name: Evans David
Author link: https://covid19-data.nist.gov/pid/rest/local/author/evans_david
Author Name: Curtis Helen J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/curtis_helen_j
Author Name: Hulme William J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hulme_william_j
Author Name: Parry John
Author link: https://covid19-data.nist.gov/pid/rest/local/author/parry_john
Author Name: Hester Frank
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hester_frank
Author Name: Harper Sam
Author link: https://covid19-data.nist.gov/pid/rest/local/author/harper_sam
Author Name: Spiegelhalter David
Author link: https://covid19-data.nist.gov/pid/rest/local/author/spiegelhalter_david
Author Name: Smeeth Liam
Author link: https://covid19-data.nist.gov/pid/rest/local/author/smeeth_liam
Author Name: Goldacre Ben
Author link: https://covid19-data.nist.gov/pid/rest/local/author/goldacre_ben
sha: 0ceb52aa1a701df1e5dc19f2c6a8275ad909c85e
license: no-cc
license_url: [no creative commons license associated]
source_x: Elsevier; Medline; PMC
source_x_url: https://www.elsevier.com/https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/
pubmed_id: 33997835
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/33997835
pmcid: PMC8106239
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106239
url: https://www.sciencedirect.com/science/article/pii/S2666776221000867 https://api.elsevier.com/content/article/pii/S2666776221000867 https://doi.org/10.1016/j.lanepe.2021.100109 https://www.ncbi.nlm.nih.gov/pubmed/33997835/
has_full_text: TRUE
Keywords Extracted from Text Content: non-COVID-19 cancer liver COVID-19 OpenSAFELY NHS 134,316 patients appendix cerebral palsy Fine UKRI ONS cancer cancer patients September-9 Covid-19 serum creatinine alcohol People spleen VPN appendix Figure A1a -v coronavirus 2 cancers https://opensafely.org/. cell Non-COVID cerebellar people COVID-19 death [8 organ COVID-19 NHS Cancers glomerular COVID-19 [2 Patients UK Health Service F00-03 COPI dementia/ Alzheimer's Open-SAFELY.org oral steroids GSK KB doi:10.1016/j.lanepe.2021.100109 Mohn-Westlake Non-white neurone UK Biobank ISO survivors individuals body volunteer FOOTNOTES 134,316 107731/Z/15/Z Patient liver patient SARS-CoV-2 Figures 3-4 https://github HbA1c NIHR, cardiovascular sickle cell Fig. 2 US CIs U07.1/U07.2 patients Humber appendix Table A1 Dementia appendix Table A2 NHS IG COVID-19 À virus 4-knot appendix Table A1 . https://codelists.opensafely.org G30 dementia/ Alzheimer's disease heart immunodeficiency [22] kidney OpenSAFELY BG's grants COVID-19 [23] UK U07.1
Extracted Text Content in Record: First 5000 Characters:Background: Mortality 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. Methods: Working 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 1 st February 2020 and with >1 year of continuous prior registration; the cutoff date for deaths was 9 th 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. Findings: 17,456,515 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]). Interpretation: Similar 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. A range of demographic and clinical risk factors for COVID-19 death were established in the first few months of the pandemic but little evidence is available on whether such factors have similar associations with COVID-19 death and non-COVID-19 death. We used data from a large database linking richly detailed primary care records and death registrations for 40% of the population of England. We conducted analyses comparing factors associated with COVID-19 and non-COVID deaths to generate unique insights into the extent to which risk factors for COVID-19 death mirror broader risk factors for death. We carried out a range of sensitivity analyses to ensure that our findings were robust. COVID-19 appears to largely act as if multiplying existing risks faced by patients. Public health decisions requiring prioritisation of vulnerable subgroups can therefore be informed by our knowledge of pre-pandemic mortality risks based on established risk factors. However there were some key exceptions; notably, higher risks of COVID-19 death for non-white ethnic groups were in contrast to lower risks of non-COVID deaths in these groups. Improved understanding of the unique drivers of COVID-19 mortality in non-white groups should be a research priority. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected tens of millions of people worldwide, causing substantial mortality [1] . Numerous factors have emerged as being associated with a higher risk of severe outcomes and death from COVID-19 [2] . Mortality appears to rise exponentially with increasing age. Male sex, obesity, socioeconomic deprivation, and a number of comorbidities are also associated with higher risk. [3, 4] Substantial variation in mortality by ethnicity has also been observed in several studies, with evidence from both the UK and US suggesting worse COVID-related outcomes among minority ethnic groups, compared with the majority White populations. [5] [6] [7] However, little evidence is available on how the factors associated with COVID-19 mortality compare with the factors associated with mortality from other causes, and hence the extent to which a person's risk of dying from COVID-19 is likely to be governed by their broader mortality risk. We know that increasing age is the major risk factor for all-cause mortality. It is possible that COVID-19 simply multiplies everyone's risk of death by a constant factor, or it could be that some factors have a different effect on COVID-19 deaths specifically. A better understanding of this would help inform strategies to identify and protect those most at risk of poor outcomes during the pandemic. A previous analysis of death registration data in England and Wales showed exponential relationships between adult age and both rates of COVID-19 death (between March and June 2020), a
Keywords Extracted from PMC Text: spleen COVID-19 Fine body FH WJH SARS-CoV-2 HbA1c oral steroids appendix Table A2 People CTR UKRI serum creatinine https://github.com/opensafely/covid-vs-noncovid-deaths-research CB liver F00-03 Dementia COVID-19 – virus NIHR, 134,316 BM organ 107731/Z/15/Z cerebral palsy COVID-19 death [8 patients cell CEM AM OpenSAFELY.org U07.1 ISO LT, https://opensafely.org/. BG's grants [22] alcohol COVID-19 [23] cancers cancer patients Non-COVID cardiovascular UK [7] Humber people Cancers VPN Covid-19 Patients neurone [15,16] patient immunodeficiency GSK IJD heart G30 individuals Non-white cerebellar AJW NHS IG dementia/ Alzheimer's Mohn-Westlake US KB appendix Table A1 volunteer 4-knot COPI appendix Figure A1a-v PI patient " Patient cancer U07.1/U07.2 ONS glomerular sickle cell OpenSAFELY kidney https://codelists.opensafely.org appendix 5th codelists - KB CTR BM CB JC CEM AJW UK Health Service COVID-19 [2 survivors centre ≥80 UK Biobank NHS
Extracted PMC Text Content in Record: First 5000 Characters:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected tens of millions of people worldwide, causing substantial mortality [1]. Numerous factors have emerged as being associated with a higher risk of severe outcomes and death from COVID-19 [2]. Mortality appears to rise exponentially with increasing age. Male sex, obesity, socioeconomic deprivation, and a number of comorbidities are also associated with higher risk. [3,4] Substantial variation in mortality by ethnicity has also been observed in several studies, with evidence from both the UK and US suggesting worse COVID-related outcomes among minority ethnic groups, compared with the majority White populations. [5], [6], [7] However, little evidence is available on how the factors associated with COVID-19 mortality compare with the factors associated with mortality from other causes, and hence the extent to which a person's risk of dying from COVID-19 is likely to be governed by their broader mortality risk. We know that increasing age is the major risk factor for all-cause mortality. It is possible that COVID-19 simply multiplies everyone's risk of death by a constant factor, or it could be that some factors have a different effect on COVID-19 deaths specifically. A better understanding of this would help inform strategies to identify and protect those most at risk of poor outcomes during the pandemic. A previous analysis of death registration data in England and Wales showed exponential relationships between adult age and both rates of COVID-19 death (between March and June 2020), and pre-pandemic rates of all-cause mortality derived from life tables, with a slightly steeper age-mortality association for COVID-19 death [8]. A study using UK Biobank data found that both modifiable and non-modifiable risk factors for COVID-19 infection were somewhat stronger than for other infections, but did not assess severity of disease or mortality [9]. A further study using UK Biobank data from before the current pandemic examined how demographic characteristics and non-communicable disease comorbidities were associated with deaths from infections versus other causes; the authors observed broadly similar patterns of risk for the two outcomes, though the magnitude of associations differed [10]. However, it is unclear to what extent findings from pre-pandemic infection-related deaths can be used to draw conclusions about COVID-19. To our knowledge, no study to date has directly compared factors associated with COVID-19 versus non-COVID deaths in the same cohort. We aimed to address this by conducting parallel analyses of COVID-19 and non-COVID death outcomes using population-based data from England within the OpenSAFELY platform. A retrospective cohort study was carried out within OpenSAFELY, a new data analytics platform in England created to address urgent COVID-19 related questions, which has been described previously [4]. We used routinely-collected electronic data from primary care practices using TPP SystmOne software, covering 2816 practices and approximately 40% of the population in England, linked to Office of National Statistics (ONS) death registrations. We included all adults (aged 18 years or over) alive and under follow-up on 1st February 2020, and with at least one year of continuous GP registration prior to this date, to ensure that baseline data could be adequately captured. We excluded people with missing age, sex, or index of multiple deprivation, since these are likely to indicate poor data quality. For a secondary analysis of deaths prior to the pandemic, a second cohort was extracted comprising all adults alive and under follow-up on 1st February 2019 and with at least one year of GP registration prior to that date (hereafter referred to as the "2019 cohort"). Finally, we compared directly those that died due to COVID-19 and those that died from other causes to assess associations between individual level factors and cause of death (analogous to a case-control analysis). The outcomes were COVID-19 death, and deaths from causes other than COVID-19 (hereafter "non-COVID death"). Cause of death was assigned using the underlying cause of death field (main/primary cause of death, coded in ICD-10) in the death registration. COVID-19 death was defined as any death with the underlying cause coded as U07.1 ("COVID-19, virus identified") or U07.2 ("COVID-19, virus not identified") [11]. Non-COVID deaths comprised all other deaths; these were also further sub-divided into categories covering the most common causes of death, namely cancer (ICD-10 chapter C), cardiovascular disease (chapter I), respiratory (chapter J), dementia/Alzheimer's disease (F00-03 or G30), and other (all other ICD-10 codes). Two sensitivity analyses were done to check that our findings were robust to the way COVID-19 deaths were defined: (i) only using the U07.1 ("virus identified") code which would likely have higher specificity; (ii) counting a U07.1/U07.2 code anyw
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