Analysis of factors affecting intraoperative hemorrhage during percutaneous nephrolithotomy and establishment of nomogram model.

ABSTRACT

Intraoperative hemorrhage is an important factor affecting intraoperative safety and postoperative patient recovery in percutaneous nephrolithotomy (PCNL). This study aimed to identify the factors that influence intraoperative hemorrhage during PCNL and develop a predictive nomogram model based on these factors.A total of 118 patients who underwent PCNL at the Department of Urology, The Affiliated Huai'an No.1 People's Hospital of Nanjing Medical University from January 2021 to September 2023 was included in this study. The patients were divided into a hemorrhage group (58 cases) and a control group (60 cases) based on the decrease in hemoglobin levels after surgery. The clinical data of all patients were collected, and both univariate analysis and multivariate logistic regression analysis were conducted to identify the independent risk factors for intraoperative hemorrhage during PCNL. The independent risk factors were used to construct a nomogram model using R software. Additionally, receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA) were utilized to evaluate the model.Multivariate logistic regression analysis revealed that diabetes, long operation time and low psoas muscle mass index (PMI) were independent risk factors for intraoperative hemorrhage during PCNL (P < 0.05). A nomogram model was developed incorporating these factors, and the areas under the ROC curve (AUCs) in the training set and validation set were 0.740 (95% CI 0.637-0.843) and 0.742 (95% CI 0.554-0.931), respectively. The calibration curve and Hosmer-Lemeshow test (P = 0.719) of the model proved that the model was well fitted and calibrated. The results of the DCA showed that the model had high value for clinical application.Diabetes, long operation time and low PMI were found to be independent risk factors for intraoperative hemorrhage during PCNL. The nomogram model based on these factors can be used to predict the risk of intraoperative hemorrhage, which is beneficial for perioperative intervention in high-risk groups to improve the safety of surgery and reduce the incidence of postoperative complications.