Association between different insulin resistance surrogates and all-cause mortality in patients with coronary heart disease and hypertension: NHANES longitudinal cohort study

• Published in: Cardiovascular diabetology Vol. 23; no. 1; pp. 86 - 13
• Main Authors: Hou, Xin-Zheng, Lv, Yan-Fei, Li, Yu-Shan, Wu, Qian, Lv, Qian-Yu, Yang, Ying-Tian, Li, Lan-Lan, Ye, Xue-Jiao, Yang, Chen-Yan, Wang, Man-Shi, Cao, Lin-Lin, Wang, Shi-Han
• Format: Journal Article
• Language: English
• Published: England BioMed Central 28.02.2024; BMC
• Subjects: All-cause mortality; Body mass index; Cardiovascular disease; Coronary artery disease; Coronary heart disease; Diabetes mellitus; Health surveys; Heart diseases; Hypertension; Insulin resistance; Mortality; Prescription drugs; Statistical analysis; Survival; United States > US; Hypertension; Insulin resistance; All-cause mortality; Coronary heart disease
• DOI: 10.1186/s12933-024-02173-7
• ISSN: 1475-2840

Studies on the relationship between insulin resistance (IR) surrogates and long-term all-cause mortality in patients with coronary heart disease (CHD) and hypertension are lacking. This study aimed to explore the relationship between different IR surrogates and all-cause mortality and identify valuable predictors of survival status in this population. The data came from the National Health and Nutrition Examination Survey (NHANES 2001-2018) and National Death Index (NDI). Multivariate Cox regression and restricted cubic splines (RCS) were performed to evaluate the relationship between homeostatic model assessment of IR (HOMA-IR), triglyceride glucose index (TyG index), triglyceride glucose-body mass index (TyG-BMI index) and all-cause mortality. The recursive algorithm was conducted to calculate inflection points when segmenting effects were found. Then, segmented Kaplan-Meier analysis, LogRank tests, and multivariable Cox regression were carried out. Receiver operating characteristic (ROC) and calibration curves were drawn to evaluate the differentiation and accuracy of IR surrogates in predicting the all-cause mortality. Stratified analysis and interaction tests were conducted according to age, gender, diabetes, cancer, hypoglycemic and lipid-lowering drug use. 1126 participants were included in the study. During the median follow-up of 76 months, 455 participants died. RCS showed that HOMA-IR had a segmented effect on all-cause mortality. 3.59 was a statistically significant inflection point. When the HOMA-IR was less than 3.59, it was negatively associated with all-cause mortality [HR = 0.87,95%CI (0.78, 0.97)]. Conversely, when the HOMA-IR was greater than 3.59, it was positively associated with all-cause mortality [HR = 1.03,95%CI (1.00, 1.05)]. ROC and calibration curves indicated that HOMA-IR was a reliable predictor of survival status (area under curve = 0,812). No interactions between HOMA-IR and stratified variables were found. The relationship between HOMA-IR and all-cause mortality was U-shaped in patients with CHD and hypertension. HOMA-IR was a reliable predictor of all-cause mortality in this population.