Multimorbidity and combined interventions for patients with coronary heart disease in Chinese population: Latent class analysis of a multi-center study

Abstract

Background and aimsThis study aimed to explore the profile of multimorbidity phenotype clusters and their discrepancy in mortality and the efficiency of combined interventions on blood pressure, glucose and lipid in each cluster. MethodsFine and Gray competing risk regression models and Kaplan–Meier curves were used to assess the association between multimorbidity and mortality and rehospitalization. Fine and Gray competing risk regression models and subgroup analyses were used to estimate the relations between combined interventions and mortality. ResultsThree distinct multimorbidity clusters were observed: Class 1 named severe class, Class 2 termed moderate class, and Class 3 named mild class. Competing risk regression models revealed that patients in Class 1 have the greatest burden of mortality and rehospitalization compared to Class 3 after confounder adjustment, with HRs 1.43 (95% CI 1.30–1.56, P < 0.001) and 2.97 (95% CI 2.74–3.21, P < 0.001), respectively. The patients in Class 2 have moderate risk of mortality and rehospitalization compared to Class 3 after confounder adjustment, with HRs 1.41 (95% CI 1.30–1.52, P < 0.001) and 2.39 (95% CI 2.23–2.56, P < 0.001), respectively. Furthermore, we found that combined interventions on blood pressure, glucose and lipid simultaneously could further benefit on survival compared to each individual intervention or two in combine. ConclusionsThis study found that multimorbidity among patients with CHD was common and increased the risks of death and rehospitalization. Three multimorbidity clusters that were significantly associated with death and rehospitalization were identified. Simultaneous intervention on blood pressure, glucose and lipid level may further benefit CHD patient in survival.