ORIGINAL RESEARCH article
Front. Nutr.
Sec. Nutrition, Psychology and Brain Health
Dynamic TyG trajectories and cumulative TyG burden are associated with in-hospital mortality in acute brain injury: a multicenter interpretable machine-learning analysis
Provisionally accepted
- 1Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China
- 2Nanjing University Medical School Affiliated Nanjing Drum Tower Hospital, Nanjing, China
- 3Neurosurgical Institute, Nanjing University, Nanjing, China
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Background Dynamic metabolic changes may influence outcomes after acute brain injury (ABI), but most ICU studies use only a single triglyceride–glucose (TyG) value. We examined whether ICU TyG trajectories and a cumulative TyG burden provide time-sensitive prognostic information and can be embedded in an interpretable mortality model. Methods Adults with ABI from three ICU databases (NSICU, MIMIC-IV, eICU) were retrospectively analyzed. TyG trajectories were derived from serial ICU measurements, cumulative exposure was summarized as prespecified threshold-based mean area under the curve (TBM), and in-hospital mortality was evaluated with 7-day time-stratified Cox models. A machine-learning model including TyG trajectory, TBM, and routinely available clinical variables was trained in NSICU and validated in the pooled external cohort. Results Among 4,760 admissions, three trajectories were identified—low–slightly increasing (LSI), moderate– increasing (MI), and persistently high (PH). Mortality did not differ across trajectories during days 0–7, but after day 7 both MI (HR 1.48, 95% CI 1.18–1.86; P < 0.001) and PH (HR 1.51, 95% CI 1.17–1.93; P = 0.001) showed higher in-hospital mortality than LSI. TBM showed a parallel positive association; TBM8p7 remained significant in fully adjusted models (HR 1.42, 95% CI 1.18–1.70; P < 0.001). ExtraTrees was selected for its consistent internal and external validation performance, and model interpretability analyses placed TyG trajectory and TBM8p7 among the next most important predictors alongside SOFA score and
Keywords: Acute brain injury, Interpretable machine learning, Metabolic trajectory, threshold-based mean area under the curve, time-stratified Cox, triglyceride-glucose index
Received: 05 Dec 2025; Accepted: 09 Feb 2026.
Copyright: © 2026 Wang, Peng, Xu, Duan, Hang and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Penglai Zhao
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