What question did this study set out to answer?

This research aims to determine the ability of the CTI biomarker to predict mortality in individuals with cardiovascular-kidney-metabolic syndrome.

January 25, 2026Open Access

The C-reactive protein-triglyceride glucose index (CTI) predicts mortality in cardiovascular-kidney-metabolic syndrome: a dual-cohort study with machine learning validation.

Key Points

This research aims to determine the ability of the CTI biomarker to predict mortality in individuals with cardiovascular-kidney-metabolic syndrome.
Utilized the CTI biomarker from dual-cohort studies in NHANES and CHARLS.
Developed a random survival forest model for mortality prediction with AUC analysis.
Conducted sensitivity analyses for validation of results.
Identified CTI as a reliable predictor of all-cause and cardiovascular mortality.
Achieved an AUC greater than 0.86 in the NHANES cohort.
Validated findings consistently across both cohorts, strengthening its clinical relevance.

Abstract

CTI, a novel inflammatory metabolic biomarker, reliably predicts all-cause and cardiovascular mortality in CKM syndrome, with consistent validation across NHANES and CHARLS. The NHANES-derived RSF model (AUC > 0.86) combines high accuracy and clinical utility, and is supported by stable external validation in CHARLS and sensitivity analyses. SHAP-based mechanistic insights further enable personalized risk assessments.

The C-reactive protein-triglyceride glucose index (CTI) predicts mortality in cardiovascular-kidney-metabolic syndrome: a dual-cohort study with machine learning validation.

Key Points

Abstract

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