Beyond accuracy: The translational case for explainable poststroke anxiety prediction - Takeaways - MDSpire
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Explainable Prediction of Poststroke Anxiety: Translating Model Accuracy into Clinical Practice

  • By

  • Jorge Valle-Reconco

  • Patricia Soriano

  • Isaac Zablah

  • October 15, 2026

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  • 1

    Across 10 Chinese hospitals, logistic regression was selected for the poststroke anxiety nomogram because it generalized better and had the lowest test-set Brier score among 7 models.

  • 2

    The 10-variable nomogram combines neurological, metabolic, and psychosocial factors, including NIHSS score, Barthel index, LDL cholesterol, sleep quality, and income.

  • 3

    SHAP ranked contributions to the fitted logistic regression model, while variable selection also considered redundancy, cost, and bedside feasibility.

  • 4

    The test partition contained approximately 36 patients, and evaluation sets came from the same multicenter cohort, so the reported performance reflects internal rather than external validation.

  • 5

    The article contains inconsistencies in cohort descriptions and reported metrics, including conflicting test-set Brier scores and stacking-model AUCs.

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