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

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@article{9e6816fe2eea45c4a07983796c7ecca4,
title = "Comorbidity phenotypes and risk of mortality in patients with ischaemic heart disease in the UK",
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. ",
author = "Francesca Crowe and Dawit Zemedikun and Kelvin Okoth and Nicola Adderley and Gavin Rudge and Mark Sheldon and Krishnarajah Nirantharakumar and Tom Marshall",
year = "2020",
month = jun,
doi = "10.1136/heartjnl-2019-316091",
language = "English",
volume = "106",
pages = "810--816",
journal = "Heart",
issn = "1355-6037",
publisher = "BMJ Publishing Group",
number = "11",

}

RIS

TY - JOUR

T1 - Comorbidity phenotypes and risk of mortality in patients with ischaemic heart disease in the UK

AU - Crowe, Francesca

AU - Zemedikun, Dawit

AU - Okoth, Kelvin

AU - Adderley, Nicola

AU - Rudge, Gavin

AU - Sheldon, Mark

AU - Nirantharakumar, Krishnarajah

AU - Marshall, Tom

PY - 2020/6

Y1 - 2020/6

N2 - 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.

AB - 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.

U2 - 10.1136/heartjnl-2019-316091

DO - 10.1136/heartjnl-2019-316091

M3 - Article

VL - 106

SP - 810

EP - 816

JO - Heart

JF - Heart

SN - 1355-6037

IS - 11

ER -