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The metabolic score for insulin resistance as a predictor of clinical outcome in stroke patients treated by intravenous thrombolysis

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Abstract

Background and purpose

Insulin resistance is associated with clinical outcomes among patients with ischemic stroke. We aimed to investigate the association between metabolic score for insulin resistance (METS-IR) and clinical outcomes in stroke patients treated by intravenous thrombolysis (IVT).

Methods

We recruited participants treated with IVT from a prospective registry including 3 stroke centers. Poor outcome was defined as a modified Rankin scale score ≥ 3 points at 90 days after the index stroke. We performed logistic regression models to investigate the association between METS-IR and the risk of poor outcome. We used the receiver operative characteristic to assess the discriminative ability and the restricted cubic spline to explore the relationship between METS-IR and the poor outcome.

Results

This study enrolled a total of 1074 patients (median age, 68; 63.8% male). Three hundred sixty (33.5%) patients had poor outcome after IVT. METS-IR was associated with the risk of the poor outcome with the increase of confounding factors in models (odds ratio [OR], 1.078; 95% confidence interval [CI], 1.058–1.099; P < 0.001). The area under the curve for METS-IR for predicting the poor outcome was 0.790 (95% CI, 0.761–0.819). The restricted cubic spline revealed an increasing and non-linear association between METS-IR and the poor outcome (P for non-linearity < 0.001).

Conclusion

Our study found that METS-IR was associated with an increased risk of poor outcome after IVT. Further studies are warranted to investigate the efficacy of anti-diabetic agents regarding IR on clinical outcomes after IVT.

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Data availability

The data that support the findings of this study are available on request from the corresponding author.

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Funding

The work was supported by Grants from the Traditional Chinese Medicine Research Program of Shanghai Municipal Health Commission (2020LZ002); the project was funded by the Shanghai Health Committee (201840154) and by the Shanghai Science and Technology Commission (22S31902300).

Author information

Author notes

  1. Mingzhe Wang, Zheng Dai, and Xiaohao Zhang contributed equally to this work.

Authors and Affiliations

  1. Department of Neurology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 528 Zhang-Heng Road, Pu-Dong New Area, Shanghai, 201203, China

    Mingzhe Wang, Xiaochen Xu, Yan Sun, Fan Gong, Baofeng Qin, Jun Wang, Bin Liu, Haiyan Tang, Tingting Li, Jinsi Zhang & Dezhi Liu

  2. Department of Neurology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi People’s Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, Jiangsu Province, 214023, China

    Zheng Dai

  3. Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210000, Jiangsu, China

    Xiaohao Zhang

  4. Department of Encephalopathy, Qinghai Provincial Hospital of Traditional Chinese Medicine, Xining, 810000, Qinghai Province, China

    Jiecheng Wang & Ling Ma

  5. Department of Neurology, Nanping People’s Hospital Affiliated to Fujian University of Traditional Chinese Medicine, Nanping, 353000, Fujian Province, China

    Wenjie Chen

  6. Department of Neurology and Rehabilitation, Seventh People’s Hospital of Shanghai University of TCM, 200137, No 358 Datong Road, Shanghai, 200137, China

    Zhenxiang Han

Authors
  1. Mingzhe Wang
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  2. Zheng Dai
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  17. Dezhi Liu
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Contributions

DL and ZH designed the study. MW, ZD, XZ, XX, YS, and FG recorded the clinical data. MW, ZD, and XZ carried out the data analysis and wrote the manuscript. Important data analysis suggestions were made by BQ, JW, JW, WC, and LM. Manuscript revisions were made by DL and ZH.

Corresponding authors

Correspondence to Zhenxiang Han or Dezhi Liu.

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This study received approvement from each participating center. Informed constants were waived because of the retrospective design of this study.

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Wang, M., Dai, Z., Zhang, X. et al. The metabolic score for insulin resistance as a predictor of clinical outcome in stroke patients treated by intravenous thrombolysis. Neurol Sci 44, 3587–3594 (2023). https://doi.org/10.1007/s10072-023-06848-z

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