Association of the estimated glucose disposal rate combined with a body shape index with all-cause and cardiovascular-specific mortality among individuals with cardiovascular-kidney-metabolic syndrome
a day ago
- #mortality risk
- #CKM syndrome
- #machine learning
- Study examines the combined effect of estimated glucose disposal rate (eGDR) and a body shape index (ABSI) on mortality in individuals with cardiovascular-kidney-metabolic (CKM) syndrome.
- Data from NHANES (1999-2018) included 18,186 individuals with CKM syndrome stages 0-4.
- Low eGDR and high ABSI independently predicted higher mortality risk.
- Combined low eGDR and high ABSI showed the highest mortality risk: all-cause HR = 2.79, cardiovascular-specific HR = 4.53.
- XGBoost machine learning model performed best in predicting mortality (AUC 0.877 for all-cause, 0.850 for cardiovascular-specific mortality).
- Findings suggest eGDR and ABSI improve risk stratification in CKM syndrome patients.