Dynamic trajectories of the triglyceride-glucose index link to all-cause hospital mortality in patients with hypertension and kidney failure: a multicenter study

Background: Chronic kidney disease and hypertension form a vicious cardiorenal cycle, exacerbating metabolic dysfunction and mortality. The triglyceride-glucose (TyG) index, a surrogate for insulin resistance, has shown prognostic value in cardiovascular and renal diseases. Previous research analyzed single-timepoint TyG, ignoring longitudinal trajectories during hospitalization. We aimed to investigate TyG trajectories and their association with hospital mortality in patients with hypertension and kidney failure (KF). Methods: Patients diagnosed with hypertension and KF were retrospectively retrieved from MIMIC-IV and a private dataset. Patients were clustered into four TyG trajectory groups using K-means clustering. A novel time-weighted average TyG (WATyG) metric was developed to quantify cumulative metabolic exposure. Logistic regression, restricted cubic spline (RCS) models, and subgroup analyses examined associations between TyG dynamics and mortality. Results: A total of 2,038 patients from MIMIC-IV and 1,266 from a private dataset were analyzed, with mortality rates of 28.41% and 7.03%, respectively. Four TyG trajectories were identified: rapidly increasing (Cluster 1), rapidly decreasing (Cluster 2), persistent high (Cluster 3), and stable low (Cluster 4). Clusters 1 and 3 had significantly higher mortality rates than Clusters 2 and 4 (all P