Yaqi Hou ^1,2 Xiaohua Wu ^3* Yiheng Shi ^4* Xiaotian Xu ^5* Yu Zhang ^6* Lei Jiang ^6* Wei Wang ^5* Yan Yang ^5* Lanying Hu ^7*

• ¹ School of Nursing and School of Public Health, Medical College, Yangzhou University, Yangzhou, China
• ² Yangzhou University, Yangzhou, Jiangsu Province, China
• ³ Department of Endocrinology and Hematology, Affiliated Hospital of Yangzhou University, Yangzhou, China
• ⁴ Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, China
• ⁵ Department of Neurology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu Province, China
• ⁶ School of Nursing, Yangzhou University, Yangzhou, China
• ⁷ Department of Nursing, Affiliated Hospital of Yangzhou University, Yangzhou, Yangzhou, China

Background: Insulin resistance (IR) is linked to an increased risk of neurological impairment following a stroke and may contribute to poor neurological prognosis in affected patients. The metabolic score for the insulin resistance index, shortened as the METS-IR, generally serves as a surrogate index for IR. However, its association with the severity of neurological impairment in patients with severe cerebral infarction (CI) in neurological intensive care units (ICU) has not been fully established. Methods: Patients with a diagnosis of CI, admitted to the neurological ICUs of Yangzhou University's Affiliated Hospital and Xuzhou Medical University's Affiliated Hospital, were included in the study. A multivariate logistic regression model and restricted cubic splines (RCS) were employed to explore the relationship between the METS-IR index and the severity of neurological impairment in these patients. The predictive capabilities of the METS-IR index and the triglyceride-glucose (TyG) index for outcome measures were compared through the ROC curve. Furthermore, a decision curve analysis was executed, and the integrated discrimination improvement (IDI) index was computed to evaluate the enhancements in predictive performance and clinical utility of various scoring systems with the inclusion of the METS-IR index. Subgroup analysis was conducted regarding age, BMI, and smoking status. Results: The study ultimately included 504 participants. Adjusted logistic regression and RCS results showed that as the METS-IR index increases, the risk of neurological impairment in patients with severe CI consistently grows (P for overall = 0.0146, P-nonlinear: 0.0689). The METS-IR index's predictive capability for neurological impairment (AUC = 0.669) was superior to that of the TyG index (AUC = 0.519). Conclusion: From the study results, the METS-IR index can serve as an important predictor for neurological impairment in ICU patients with severe CI. It can aid in the identification and early intervention of neurological impairment in these patients.