Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the U.K.

BMC Infectious Diseases

Nazrul Islam¹  Samuel Seidu²  Kamlesh Khunti²  Yogini V. Chudasama²  David E. Kloecker²  Francesco Zaccardi²  Clare L. Gillies²  Nita G. Forouhi³  Cameron Razieh⁴  Alex V. Rowlands⁴  Melanie J. Davies⁴  Thomas Yates⁴ 

[1] Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK;Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK;Leicester Real World Evidence Unit, Diabetes Research Centre, Leicester General Hospital, University of Leicester, Leicester, UK;Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK;NIHR Leicester Biomedical Research Centre, Leicester Diabetes Centre, Leicester, UK;

关键词: Multimorbidity;    Pattern;    SARS-CoV-2 infection;    COVID-19;    Hospitalisation;    Mortality;    Risk factors;   

DOI  :  10.1186/s12879-021-06600-y

来源: Springer

【 摘 要 】

BackgroundPre-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.MethodsWe 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.ResultsAmong 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]).ConclusionThe multimorbidity index may help identify individuals at higher risk for severe COVID-19 outcomes and provide guidance for tailoring effective treatment.

【 授权许可】

CC BY