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Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the U.K.
Chudasama, Yogini V; Zaccardi, Francesco; Gillies, Clare L; Razieh, Cameron; Yates, Thomas; Kloecker, David E; Rowlands, Alex V; Davies, Melanie J; Islam, Nazrul; Seidu, Samuel; Forouhi, Nita G; Khunti, Kamlesh.
  • Chudasama YV; Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK. yc244@leicester.ac.uk.
  • Zaccardi F; Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK.
  • Gillies CL; Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK.
  • Razieh C; NIHR Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, UK.
  • Yates T; NIHR Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, UK.
  • Kloecker DE; Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK.
  • Rowlands AV; NIHR Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, UK.
  • Davies MJ; NIHR Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, UK.
  • Islam N; Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
  • Seidu S; Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK.
  • Forouhi NG; Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK.
  • Khunti K; Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK.
BMC Infect Dis ; 21(1): 908, 2021 Sep 04.
Article in English | MEDLINE | ID: covidwho-1455937
Preprint
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ABSTRACT

BACKGROUND:

Pre-existing comorbidities have been linked to SARS-CoV-2 infection but evidence is sparse on the importance and pattern of multimorbidity (2 or more conditions) and severity of infection indicated by hospitalisation or mortality. We aimed to use a multimorbidity index developed specifically for COVID-19 to investigate the association between multimorbidity and risk of severe SARS-CoV-2 infection.

METHODS:

We used data from the UK Biobank linked to laboratory confirmed test results for SARS-CoV-2 infection and mortality data from Public Health England between March 16 and July 26, 2020. By reviewing the current literature on COVID-19 we derived a multimorbidity index including (1) angina; (2) asthma; (3) atrial fibrillation; (4) cancer; (5) chronic kidney disease; (6) chronic obstructive pulmonary disease; (7) diabetes mellitus; (8) heart failure; (9) hypertension; (10) myocardial infarction; (11) peripheral vascular disease; (12) stroke. Adjusted logistic regression models were used to assess the association between multimorbidity and risk of severe SARS-CoV-2 infection (hospitalisation/death). Potential effect modifiers of the association were assessed age, sex, ethnicity, deprivation, smoking status, body mass index, air pollution, 25-hydroxyvitamin D, cardiorespiratory fitness, high sensitivity C-reactive protein.

RESULTS:

Among 360,283 participants, the median age was 68 [range 48-85] years, most were White (94.5%), and 1706 had severe SARS-CoV-2 infection. The prevalence of multimorbidity was more than double in those with severe SARS-CoV-2 infection (25%) compared to those without (11%), and clusters of several multimorbidities were more common in those with severe SARS-CoV-2 infection. The most common clusters with severe SARS-CoV-2 infection were stroke with hypertension (79% of those with stroke had hypertension); diabetes and hypertension (72%); and chronic kidney disease and hypertension (68%). Multimorbidity was independently associated with a greater risk of severe SARS-CoV-2 infection (adjusted odds ratio 1.91 [95% confidence interval 1.70, 2.15] compared to no multimorbidity). The risk remained consistent across potential effect modifiers, except for greater risk among older age. The highest risk of severe infection was strongly evidenced in those with CKD and diabetes (4.93 [95% CI 3.36, 7.22]).

CONCLUSION:

The multimorbidity index may help identify individuals at higher risk for severe COVID-19 outcomes and provide guidance for tailoring effective treatment.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Limits: Aged / Humans / Middle aged Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: S12879-021-06600-y

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Limits: Aged / Humans / Middle aged Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: S12879-021-06600-y