Machine Learning-Based Prediction of Post-PKP Frailty: A Retrospective Cohort Study
ML models effectively predict post-PKP frailty, highlighting modifiable risk factors. Standardized anti-osteoporosis therapy, residual LBP prevention, and reduced postoperative recumbency may mitigate frailty risk.
Authors
- Quan Zhou (ORCID: https://orcid.org/0000-0002-8358-7577)
- Cheng Xie (ORCID: https://orcid.org/0000-0002-5165-9900)
- Dingjun Xu (ORCID: https://orcid.org/0000-0002-5511-7439)
- Yizhe Shen
- Mengxian Jia (ORCID: https://orcid.org/0009-0005-7121-4596)
- Xiang Fang (ORCID: https://orcid.org/0000-0002-9170-0293)
- Zhiyuan Li (ORCID: https://orcid.org/0000-0001-6662-2636)
- Honglin Teng (ORCID: https://orcid.org/0000-0003-0700-7574)
- Ziwei Fan (ORCID: https://orcid.org/0000-0003-3887-5470)
Institutions
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
Publication Details
- Journal
- Clinical Interventions in Aging
- Published
- 2025-09-01
- DOI
- https://doi.org/10.2147/cia.s537151
- Primary Topic
- Hip and Femur Fractures
- Type
- article
- Field-Weighted Citation Impact
- 0.00