Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery.

ABSTRACT:

Objective

To develop and validate a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection (POI) after radical colorectal cancer (CRC) surgery.

Design

Cross-sectional study.

Participants

This study analysed 866 CRC patients after radical surgery at a tertiary hospital in China.

Methods

Univariable and multivariable logistic regression (LR) analyses were used to explore influence factors of POI. Predictive models were constructed using LR, random forest, support vector machine, K-nearest neighbours, naive Bayes and XGBoost. The LR model was used to generate a nomogram for POI prediction. The discrimination and calibration of the nomogram were assessed using receiver operating characteristic (ROC) curves and ca

SUBMITTER: Han J 

PROVIDER: S-EPMC11749061 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature