Interpreting the clinical utility and generalizability of a multitask perioperative prediction model

This Matters Arising comments on Yoon et al.'s multitask gradient boosting model for predicting acute kidney injury, postoperative respiratory failure and in-hospital mortality after non-cardiac surgery. We ask for clarification on the clinical decision context and threshold ranges in the decision curve analyses, the absolute impact of the model for rare outcomes, and calibration and potential recalibration in external cohorts to support implementation.

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Publication Details

Journal
npj Digital Medicine
Published
2026-08-03
DOI
https://doi.org/10.1038/s41746-026-02813-0
Primary Topic
Cardiac, Anesthesia and Surgical Outcomes
Type
article
Field-Weighted Citation Impact
0.00
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article

Interpreting the clinical utility and generalizability of a multitask perioperative prediction model

Guo-Ming Zhang, Xiao-Min Wo
npj Digital Medicine
Cardiac, Anesthesia and Surgical Outcomes
article

Interpreting the clinical utility and generalizability of a multitask perioperative prediction model

Guo-Ming Zhang, Xiao-Min Wo
article en

Abstract

This Matters Arising comments on Yoon et al.'s multitask gradient boosting model for predicting acute kidney injury, postoperative respiratory failure and in-hospital mortality after non-cardiac surgery. We ask for clarification on the clinical decision context and threshold ranges in the decision curve analyses, the absolute impact of the model for rare outcomes, and calibration and potential recalibration in external cohorts to support implementation.

npj Digital MedicineVol. 9(1)
Xuzhou Medical College (CN), Yang Hospital (KR)
Good health and well-being
Openalex Percentile: Top 9%
Cardiac, Anesthesia and Surgical Outcomes
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