Evidence map›Paper›PMID 39385817›Full record

ArticleFrontiers in neurology2024

METS-IR as an important predictor of neurological impairment severity in patients with severe cerebral infarction: a multicenter study based on the Chinese population.

Yaqi Hou, Xiaohua Wu, Yiheng Shi, Xiaotian Xu, Yu Zhang, Lei Jiang, Wei Wang, Yan Yang, Lanying Hu

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Article in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Yaqi Hou *School of Nursing, Yangzhou University, Yangzhou, Jiangsu, China.
Xiaohua Wu *Department of Endocrinology and Hematology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, China.
Yiheng Shi *Department of Gastroenterology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou Jiangsu, China.
Xiaotian XuDepartment of Neurology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, China.
Yu ZhangSchool of Nursing, Yangzhou University, Yangzhou, Jiangsu, China.
Lei JiangSchool of Nursing, Yangzhou University, Yangzhou, Jiangsu, China.
Wei WangDepartment of Neurology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, China.
Yan YangDepartment of Neurology, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, China.
Lanying HuDepartment of Nursing, Affiliated Hospital of Yangzhou University, Yangzhou, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 ( 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.

Indexed as

cerebral infarctionICUMETS-IRneurological functionNIHSS

Identifiers

PMID39385817
PMCPMC11461195

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