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Patterns of Multimorbidity and Risk of Severe SARS-CoV-2 Infection: an Observational Study in the U.K

Overview
Journal BMC Infect Dis
Publisher Biomed Central
Date 2021 Sep 5
PMID 34481456
Citations 40
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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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References
1.
Armstrong J, Rudkin J, Allen N, Crook D, Wilson D, Wyllie D . Dynamic linkage of COVID-19 test results between Public Health England's Second Generation Surveillance System and UK Biobank. Microb Genom. 2020; 6(7). PMC: 7478634. DOI: 10.1099/mgen.0.000397. View

2.
Woolford S, DAngelo S, Curtis E, Parsons C, Ward K, Dennison E . COVID-19 and associations with frailty and multimorbidity: a prospective analysis of UK Biobank participants. Aging Clin Exp Res. 2020; 32(9):1897-1905. PMC: 7377312. DOI: 10.1007/s40520-020-01653-6. View

3.
Iaccarino G, Grassi G, Borghi C, Ferri C, Salvetti M, Volpe M . Age and Multimorbidity Predict Death Among COVID-19 Patients: Results of the SARS-RAS Study of the Italian Society of Hypertension. Hypertension. 2020; 76(2):366-372. DOI: 10.1161/HYPERTENSIONAHA.120.15324. View

4.
Petrilli C, Jones S, Yang J, Rajagopalan H, ODonnell L, Chernyak Y . Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020; 369:m1966. PMC: 7243801. DOI: 10.1136/bmj.m1966. View

5.
Swanson J . The UK Biobank and selection bias. Lancet. 2012; 380(9837):110. DOI: 10.1016/S0140-6736(12)61179-9. View