Evidence mapPaperPMID 41723444Full record

ArticleLipids in health and disease2026

Joint effects of triglyceride-glucose-BMI and stress hyperglycemia ratio on all-cause mortality in trauma surgical intensive care patients: a multicenter cohort study.

Chen Jiang, Zhanfei Li, Qiqi Wu, Jian Chen, Ying Yao, Kan Wang

Abstract readMulticenter Study
In one paragraph

Article in Lipids in health and disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Chen Jiang *Department of Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Zhanfei Li *Trauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Qiqi Wu *Trauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
Jian ChenDepartment of Nephrology, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Huangshi, 435000, China. tiger822816@126.com.
Ying YaoDepartment of Nutrition, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. yaoyingkk@126.com.
Kan WangTrauma Center, Department of Emergency and Traumatic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. kanwang_tj@126.com.

Funding

China Postdoctoral Science Foundation 2025M772263
6 · The paper itself

Abstract

backgroundTrauma surgical intensive care unit (TSICU) patients frequently present with metabolic dysregulation. However, the combined prognostic value of the triglyceride-glucose–body mass index (TyG-BMI) and the stress hyperglycemia ratio (SHR) remains unclear.

methodsA retrospective cohort study was conducted using the MIMIC-IV database, with external validation in a TSICU cohort from Tongji Hospital. Adult patients admitted to the TSICU were classified into four groups based on joint TyG-BMI and SHR categories. The endpoints were 28-day and 180-day all-cause mortality. Cox regression, restricted cubic splines, Kaplan–Meier survival curves, and 33 machine learning models were employed to evaluate associations and predictive performance.

resultsA total of 872 patients were included in the training cohort and 525 in the validation cohort. Overall, 19.0% and 25.8% of patients died within 28 and 180 days, respectively. Joint SHR–TyG-BMI stratification revealed distinct prognostic profiles. Patients with high SHR and low TyG-BMI had the highest mortality risk, while those with low SHR and high TyG-BMI had the most favorable outcomes. TyG-BMI demonstrated a U-shaped association with short- and mid-term mortality, whereas SHR alone showed limited prognostic value. Machine learning analyses confirmed SHR and TyG-BMI as top predictors, outperforming traditional severity scores. Subgroup analyses across age, diabetes, hypertension, and cardiovascular disease consistently supported their prognostic utility.

conclusionsTyG-BMI and SHR are complementary predictors of short- and mid-term mortality in TSICU patients. High SHR combined with low TyG-BMI identifies patients at greatest risk, whereas preserved metabolic reserve mitigates the adverse effects of stress hyperglycemia. Integrating both acute and chronic metabolic indices may enhance risk stratification and guide individualized metabolic management in surgical intensive care.

Indexed as

Blood GlucoseBody Mass IndexHyperglycemiaTriglyceridesWounds and InjuriesAdultAgedCohort StudiesCritical CareFemaleHumansIntensive Care UnitsMaleMiddle AgedPrognosisRetrospective StudiesBlood GlucoseTriglyceridesMetabolic reserveMortalityStress hyperglycemia ratioSurgical intensive careTraumaTriglyceride–glucose–body mass index

Identifiers

PMID41723444
PMCPMC13032211

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