A nomogram integrating machine learning with clinical predictors for osteosarcopenia risk prediction in type 2 diabetes mellitus - Takeaways - MDSpire

A nomogram integrating machine learning with clinical predictors for osteosarcopenia risk prediction in type 2 diabetes mellitus

  • By

  • Dan Liang

  • Zhenrun Zhan

  • Yongze Zhang

  • Sunjie Yan

  • July 15, 2026

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  • 1

    A nomogram was developed to predict osteosarcopenia risk in patients with type 2 diabetes mellitus aged 40 years and older.

  • 2

    The study identified eight independent predictors for osteosarcopenia, including gender, age, BMI, and WHtR.

  • 3

    The nomogram demonstrated AUCs of 0.864 and 0.904 in the test and validation cohorts, respectively.

  • 4

    Higher BMI was found to be a protective factor, while higher WHtR was identified as a risk factor for osteosarcopenia.

  • 5

    The study emphasizes the need for further multicenter external validation of the nomogram for clinical application.

Original Source(s)

A nomogram integrating machine learning with clinical predictors for osteosarcopenia risk prediction in type 2 diabetes mellitus

  • by Dan Liang, Zhenrun Zhan, Yongze Zhang, Sunjie Yan

  • July 15, 2026

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