Insulin Resistance Predicts Prognosis in Patients With Subarachnoid Hemorrhage.

Abstract

Objective: The objective of this study was to determine whether insulin resistance (IR) could be used as a predictor of poor prognosis at 3 months after subarachnoid hemorrhage (SAH).

Methods: The study included patients aged 18 years or older with a confirmed diagnosis of SAH due to ruptured aneurysm from January 2021 to March 2024. Patients with confirmed diabetes mellitus and taking glucose-lowering drugs, or taking lipid-lowering drugs, or SAH not due to ruptured aneurysm, or comorbid systemic diseases were excluded. Patients were classified into good prognosis (modified Rankin scale [MRS] 0-2) and poor prognosis (MRS 3-6). Receiver operating characteristic curve (ROC), least absolute shrinkage and selection operator (LASSO) analysis, and multivariate logistic regression analysis were used to determine the potential of triglyceride-glucose (TyG) index and the triglyceride to high-density lipoprotein cholesterol (TG/HDL) ratio as predictors of poor prognosis. Finally, a prognostic prediction model based on IR was constructed.

Results: A total of 358 patients were included in this study. Poor prognosis patients had higher age, BMI, hypertension percentage, glucose, triglycerides, TyG index and TG/HDL ratio, and lower HDL. ROC, LASSO, and multivariate logistic regression analysis revealed that age, glucose, TyG index, and TG/HDL ratio had significant potential to predict the prognosis of SAH patients. The prognostic prediction model constructed by combining age, glucose, TyG index, and TG/HDL ratio had high discriminatory power (area under the curve [AUC] = 0.80), satisfactory calibration curves, and good clinical utility.

Conclusion: IR is strongly associated with the prognosis of SAH patients, and the combination of age, glucose, TyG index, and TG/HDL ratio can provide a new direction for future treatment.