Predicting postoperative fever in culture-negative patients undergoing mini-PCNL using MAP score-augmented machine learning: a retrospective cohort study

The proposed tool, combining MAP scores with ML, significantly enhances the accuracy of predicting the risk of postoperative fever following mini-PCNL in patients with sterile urine cultures. The LR model demonstrates strong utility and interpretability, offers personalised risk assessments preoperatively and constitutes a practical and accessible online tool for individualised clinical decision-making.