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September 10, 2025Journal of Orthopaedic Surgery and ResearchOpen Access

A development of machine learning models to preoperatively predict insufficient clinical improvement after total knee arthroplasty

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Authors

GGGeunwu GimmBJByoungjun JeonSKSung Eun Kim

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Overview

Retrospective analysis identifies machine learning models that predict clinical improvement post TKA, suggesting key preoperative variables.

Key Points

  • Machine learning models effectively predicted insufficient clinical improvement after total knee arthroplasty.
  • The ExtraTrees model achieved high performance metrics, with AUCs of up to 0.92 for WOMAC scores.
  • Shapley additive explanations revealed key predictors of insufficient clinical improvement, including older age and diabetes.
  • These findings may enhance shared decision-making and patient management preoperatively for TKA candidates.

Cite This Study

Gimm et al. (2025) studied this question.

synapsesocial.com/papers/68c1cc3754b1d3bfb60f46f9https://doi.org/10.1186/s13018-025-06206-z
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