Identification of key metabolic indicators associated with the comorbidity of ischemic stroke and diabetes mellitus using an optimal interpretable clinlabomics model - Takeaways - MDSpire

Identification of key metabolic indicators associated with the comorbidity of ischemic stroke and diabetes mellitus using an optimal interpretable clinlabomics model

  • By

  • Yao Jiang

  • Ao Qian

  • Shu Chen

  • Qian Wu

  • Hao Xu

  • Chang Zheng

  • Fengyu Zhang

  • Wenli Xing

  • Jimin He

  • June 24, 2026

  • 0 min

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  • 1

    The study identified 12 metabolic indicators associated with ischemic stroke and diabetes mellitus comorbidity using logistic regression.

  • 2

    The triglyceride glucose index and atherogenic index of plasma were significantly linked to increased risk of IS-DM comorbidity.

  • 3

    The recursive partitioning and regression trees algorithm achieved the best performance metrics for the Clinlabomics model.

  • 4

    Nine candidate metabolic biomarkers for IS-DM comorbidity were identified, including TyG, uric acid, and HbA1c/HDL-C.

  • 5

    The Clinlabomics model demonstrated strong performance in identifying the IS-DM population with high accuracy and AUC values.

Original Source(s)

Identification of key metabolic indicators associated with the comorbidity of ischemic stroke and diabetes mellitus using an optimal interpretable clinlabomics model

  • by Yao Jiang, Ao Qian, Shu Chen, Qian Wu, Hao Xu, Chang Zheng, Fengyu Zhang, Wenli Xing, Jimin He

  • June 24, 2026

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