Development and internal validation of El-Shazly-Buchholz's nomogram to predict postoperative complications after...

A model to predict the risk of surgical complications following percutaneous nephrolithotomy (PCNL) could be a useful tool to guide clinical decision-making. The aim of this study was to develop a simple and widely applicable stratification tool to be used for patient counseling, surgical planning, evaluation of outcomes, and academic reporting.

Data of patients who underwent PCNL were retrieved from the database of the collaborating centers including demographics of patients, characteristics of their stones and urinary tracts, and perioperative data. The primary outcome was the development of postoperative complications. Data were randomly split into a training dataset (85%) and a validation dataset (15%). A univariate and multivariate logistic regression analysis of the training dataset was performed to identify independent predictors of postoperative complications. Model variables were used to construct a nomogram that was internally validated on the testing dataset by measuring calibration, discrimination, and plotting the decision curve.

Six hundred thirty one patients (245 Males) with a median (IQR) age of 49 (37-56) years were included. Post-operative complications occurred in 147 (23.3%) patients. Significant predictors of complications included preoperative urine culture (p < 0.001), largest stone diameter (p = 0.02), and intraoperative blood loss (p = 0.002). A nomogram was developed from the predictors and applied to the validation dataset showing an area under the curve (95%CI) of 66.4% (52.2;80.6).

This new scoring system emphasized patient characteristics and operative details rather than stone characters to predict the morbidity of PCNL. Furthermore, it should facilitate risk adjustment, enabling physicians to better define the nephrolithiasis disease continuum and identify patients who should be referred to tertiary care centers.