Predictive value of the triglyceride-glucose index for short- and long-term all-cause mortality in patients with critical coronary artery disease: a cohort study from the MIMIC-IV database

Triglyceride-glucose (TyG) index is linked to a poor prognosis for cardiovascular condition and is a valid indicator of insulin resistance. This study evaluated the potential predicting usefulness of the TyG index for all-cause mortality, both short- and long-term, for those concerning critical coronary artery disease (CAD). In this study, information from 5452 critically-ill individuals with CAD in intensive care units were gathered from the Medical Information Marketplace in Intensive Care (MIMIC-IV) database. Depending on the TyG index degree, the patients were categorized into three categories. Clinical outcomes included short-term (30-day) and long-term (365-day) all-cause mortality. The corresponding relationships involving the TyG index and clinical outcomes were examined by deploying restricted cubic spline (RCS) regression analysis and Cox proportional risk regression. An increased TyG index was associated with increased 30-day (Tertile 1: 6.1%, Tertile 2: 7.3%, Tertile 3: 9.2%, P = 0.001) and 365-day (Tertile 1: 15.2%, Tertile 2: 17.0%, Tertile 3: 19.6%, P = 0.002) death rates across all causes. Cox regression with multiple variables indicates that higher TyG indices were linked to higher all-caused mortality hazard ratios throughout the short and long terms, with a larger predictive value for the former. RCS regression analyses suggested that the risk of death was notably and linearly that is associated with TyG index. The TyG index is a reliable predictor of all-cause mortality at different stages in critically ill CAD patients, with a higher predictive ability for short-term mortality. Early intervention in patients with elevated TyG index may improve their survival outcomes. Future research should delve into understanding its pathophysiological mechanisms and develop intervention strategies based on the TyG index, providing new insights and strategies to enhance the outlook for critically ill CAD patients.