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Association between the combined cholesterol, high-density lipoprotein, glucose index and frailty index and new-onset cardiovascular disease in individuals with cardiovascular-kidney-metabolic syndrome stages 0–3: evidence from CHARLS

医学 糖尿病 血管病学 疾病 内科学 索引(排版) 联想(心理学) 纵向研究 心脏病学 虚弱指数 糖尿病前期 血压 代谢综合征 梅德林 队列研究 前瞻性队列研究 体质指数 空腹血糖值 动脉粥样硬化性心血管疾病 流行病学
作者
Zhonghua Sun,Kexue Wang,Chiwei Guo,Jiajun Qiu,Wencai Wang,Yameng Xu,Yi Tang,Kaisaierjiang Kadier,Song Wen,Wei Zhang
出处
期刊:Cardiovascular Diabetology [BioMed Central]
被引量:2
标识
DOI:10.1186/s12933-026-03293-y
摘要

BACKGROUND: Early-stage cardiovascular-kidney-metabolic (CKM) syndrome, encompassing stages 0-3, represents a critical window for identifying individuals at risk before the development of clinical cardiovascular disease (CVD). Metabolic dysregulation and frailty-related physiological vulnerability may jointly contribute to cardiovascular susceptibility in middle-aged and older adults. However, conventional single-domain markers may not adequately capture this combined risk burden. This study aimed to evaluate the association and predictive utility of the combined cholesterol, high-density lipoprotein, glucose index and frailty index (CHG-FI) for new-onset CVD, heart disease, and stroke among individuals with early-stage CKM syndrome. METHODS: This cohort study used longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2020), including 4,603 participants with CKM stages 0-3. New-onset CVD, defined as the occurrence of heart disease or stroke during follow-up, was the primary outcome; new-onset heart disease and stroke were analyzed separately as secondary outcomes. CHG-FI was calculated as the product of the cholesterol, high-density lipoprotein, glucose (CHG) index and frailty index (FI). Multivariable Cox proportional hazards models were used to assess the associations of CHG-FI with new-onset cardiovascular outcomes. Restricted cubic splines were applied to examine nonlinear dose-response relationships. Joint-exposure analyses were used to characterize CVD risk across combined CHG and FI categories, and multiplicative and additive interaction analyses were performed to assess whether CHG and FI interacted in relation to new-onset CVD. Predictive performance was compared with CHG, FI, triglyceride-glucose index (TyG), atherogenic index of plasma (AIP), and metabolic score for insulin resistance (METS-IR) using receiver operating characteristic curves, DeLong tests, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Formal incremental modeling was further performed by separately adding CHG-FI and comparator indices to the fully adjusted base model. RESULTS: During a median follow-up of 9 years, 1,189 participants (25.8%) developed new-onset CVD. In fully adjusted models, each one-unit increase in CHG-FI was associated with higher risks of new-onset heart disease (HR = 1.59; 95% CI 1.42-1.77), stroke (HR = 1.56; 95% CI 1.32-1.83), and composite CVD (HR = 1.56; 95% CI 1.41-1.72). Participants in the highest CHG-FI quartile had more than two-fold higher risks of all cardiovascular outcomes compared with those in the lowest quartile. Restricted cubic spline analyses showed nonlinear associations, with cardiovascular risk increasing more steeply across lower to moderate CHG-FI levels. In joint-exposure analyses, participants with both high CHG and high FI had the highest risk of new-onset CVD (HR = 2.05; 95% CI 1.71-2.47); however, no statistically significant multiplicative or additive interaction was observed. CHG-FI showed the highest AUCs for new-onset CVD (0.624) and heart disease (0.622) among the evaluated indices and statistically outperformed CHG, FI, TyG, AIP, and METS-IR for both outcomes; however, the absolute discriminative performance was modest. For new-onset CVD, CHG-FI showed statistically significant reclassification improvements compared with CHG, TyG, AIP, and METS-IR, with NRI values of 13.85%, 9.16%, 11.02%, and 20.90%, respectively, and yielded small but statistically significant IDI improvements ranging from 0.20 to 0.48% compared with all reference indices. In formal incremental models, adding CHG-FI to the fully adjusted base model provided statistically significant but limited improvement, with only small absolute gains over FI alone. CONCLUSIONS: Higher CHG-FI was independently associated with increased risks of new-onset CVD, heart disease, and stroke among middle-aged and older adults with early-stage CKM syndrome. Participants with both high CHG and high FI had the greatest risk of new-onset CVD, although this pattern did not reflect a statistically significant multiplicative or additive interaction. CHG-FI showed statistically significant but modest discriminative performance, and the incremental improvements beyond comparator indices and clinical covariates were limited in magnitude. These findings suggest that CHG-FI may serve as a complementary marker reflecting integrated glucose-lipid metabolic dysregulation and frailty-related vulnerability, but it should not be considered a standalone clinical prediction tool and requires further validation before clinical application.
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