Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2026
Associations of cardiometabolic index with stroke outcomes in European and American cohorts.
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Wang Guiqing, Wang Shengping, Li Hang, Luo Zhi
Аннотация
BACKGROUND: While the cardiometabolic index (CMI) has emerged as a potential stroke predictor, its utility across diverse populations and specific clinical contexts remains underexplored. This study aims to bridge these methodological and clinical knowledge gaps using large-scale, multi-ethnic cohorts.
METHODS: Leveraging data from the UK Biobank (n=413,686) and NHANES (n=40,607), we employed multivariate Cox proportional hazards regression to evaluate the associations between CMI and incident ischemic/hemorrhagic stroke, as well as cerebrovascular mortality. Restricted cubic splines (RCS) were utilized to characterize potential non-linear dose-response relationships.
RESULTS: RCS analysis demonstrated a non-linear association between CMI and both ischemic and hemorrhagic stroke. In fully adjusted models, each unit increase in CMI was associated with elevated stroke and mortality risk: 24% higher risk of ischemic stroke (HR = 1.24, 95% CI: 1.21-1.28) and a 11% increased risk of cerebrovascular mortality (HR = 1.11, 95% CI: 1.01-1.21). Notably, interaction analyses confirmed joint modifying effects, indicating that genetic susceptibility and metabolic dysfunction collectively amplify stroke risk. Subgroup analyses revealed that the association between CMI and stroke was stronger in younger individuals and females.
CONCLUSIONS: Our study suggests that CMI may serve as a potential biomarker associated with stroke incidence and mortality. These observations indicate that CMI could have utility in clinical settings for the identification of high-risk populations, although further validation is needed. To better understand the clinical applicability of these findings, future research should focus on the development of integrated clinical prediction tools and comprehensive health economic evaluations to assess the feasibility of CMI-based screening strategies.
METHODS: Leveraging data from the UK Biobank (n=413,686) and NHANES (n=40,607), we employed multivariate Cox proportional hazards regression to evaluate the associations between CMI and incident ischemic/hemorrhagic stroke, as well as cerebrovascular mortality. Restricted cubic splines (RCS) were utilized to characterize potential non-linear dose-response relationships.
RESULTS: RCS analysis demonstrated a non-linear association between CMI and both ischemic and hemorrhagic stroke. In fully adjusted models, each unit increase in CMI was associated with elevated stroke and mortality risk: 24% higher risk of ischemic stroke (HR = 1.24, 95% CI: 1.21-1.28) and a 11% increased risk of cerebrovascular mortality (HR = 1.11, 95% CI: 1.01-1.21). Notably, interaction analyses confirmed joint modifying effects, indicating that genetic susceptibility and metabolic dysfunction collectively amplify stroke risk. Subgroup analyses revealed that the association between CMI and stroke was stronger in younger individuals and females.
CONCLUSIONS: Our study suggests that CMI may serve as a potential biomarker associated with stroke incidence and mortality. These observations indicate that CMI could have utility in clinical settings for the identification of high-risk populations, although further validation is needed. To better understand the clinical applicability of these findings, future research should focus on the development of integrated clinical prediction tools and comprehensive health economic evaluations to assess the feasibility of CMI-based screening strategies.