Machine learning-based prediction of early-onset peritoneal dialysis-associated peritonitis: the role of the CONUT score
The 6-month CONUT score is an independent predictor of early-onset PDAP and was among the top contributing features in multiple machine learning models. Integrating SHAP-based feature selection with gradient boosting improved model accuracy and interpretability. Dynamic monitoring of nutritional-immune status may aid in early risk stratification and guide personalized prevention strategies in patients undergoing PD.
Authors
- Shengjia Zhao
- Huiyue Hu (ORCID: https://orcid.org/0000-0002-6930-6425)
- Chunlei Yao
- Yi-Tong Ma
- Min Yang (ORCID: https://orcid.org/0000-0002-4611-827X)
- Ye Yuan (ORCID: https://orcid.org/0000-0002-1355-1974)
- Kai Song (ORCID: https://orcid.org/0000-0003-0752-6198)
- Hua Zhou
- Xiangyin Chen
Institutions
- Nantong University (CN)
- Soochow University (CN)
- Taizhou Second People's Hospital (CN)
- The Affiliated Taizhou People's Hospital of Nanjing Medical University (CN)
- Second Affiliated Hospital of Soochow University (CN)
Publication Details
- Journal
- Frontiers in Nutrition
- Published
- 2025-12-11
- DOI
- https://doi.org/10.3389/fnut.2025.1681169
- Primary Topic
- Dialysis and Renal Disease Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Jiangsu Commission of Health