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

被引:48
作者
Chudasama, Yogini V. [1 ]
Zaccardi, Francesco [1 ]
Gillies, Clare L. [1 ]
Razieh, Cameron [2 ]
Yates, Thomas [2 ]
Kloecker, David E. [1 ]
Rowlands, Alex V. [2 ]
Davies, Melanie J. [2 ]
Islam, Nazrul [3 ,4 ]
Seidu, Samuel [1 ]
Forouhi, Nita G. [4 ]
Khunti, Kamlesh [1 ]
机构
[1] Univ Leicester, Leicester Gen Hosp, Leicester Real World Evidence Unit, Diabet Res Ctr, Leicester, Leics, England
[2] NIHR Leicester Biomed Res Ctr, Leicester Diabet Ctr, Leicester, Leics, England
[3] Univ Oxford, Nuffield Dept Popula tion Hlth, Clin Trial Serv Unit & Epidemiol Studies Unit CTS, Oxford, England
[4] Univ Cambridge, Med Res Council Epidemiol Unit, Sch Clin Med, Cambridge, England
基金
英国医学研究理事会;
关键词
Multimorbidity; Pattern; SARS-CoV-2; infection; COVID-19; Hospitalisation; Mortality; Risk factors; BIOBANK; CARE;
D O I
10.1186/s12879-021-06600-y
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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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