Comorbidity phenotypes and risk of mortality in patients with ischaemic heart disease in the UK

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Colleges, School and Institutes

Abstract

Objectives: The objective of this study is to use latent class analysis of up to 20 comorbidities in patients with a diagnosis of ischaemic heart disease (IHD) to identify clusters of comorbidities and to examine the associations between these clusters and mortality.
Methods: Longitudinal analysis of electronic health records in the health improvement network (THIN), a UK primary care database including 92,186 men and women aged ≥ 18 years with IHD and a median of 2 (IQR 1-3) comorbidities.
Results: Latent class analysis revealed five clusters with half categorised as a low-burden comorbidity group. After a median follow-up of 3.2 (IQR 1.4-5.8) years, 17,645 patients died. Compared with the low-burden comorbidity group, two groups of patients with a high-burden of comorbidities had the highest adjusted hazard ratio (HR) for mortality – those with vascular and musculoskeletal conditions, HR 2.38 (95% CI 2.28-2.49) and those with respiratory and musculoskeletal conditions, HR 2.62 (95% CI 2.45-2.79). Hazards of mortality in two other groups of patients characterised by cardio-metabolic and mental health comorbidities were also higher than the low-burden comorbidity group; HR 1.46 (95% CI 1.39-1.52) and 1.55 (1.46- 1.64), respectively.
Conclusions: This analysis has identified five distinct comorbidity clusters in IHD patients that were differentially associated with risk of mortality. These analyses should be replicated in other large datasets and this may help shape the development of future interventions or health services that take into account the impact of these comorbidity clusters.

Details

Original languageEnglish
JournalHeart
Publication statusAccepted/In press - 28 Jan 2020