AUTHOR=Xu Meijuan , Zhang Qiuxuan , Mo Xiaohui , Liu Yanmei , Peng Man , Ma Xuexia 

TITLE=Predicting day-one mobility in partial nephrectomy patients using preoperative and intraoperative clinical parameters

JOURNAL=Frontiers in Oncology

VOLUME=Volume 15 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1528834

DOI=10.3389/fonc.2025.1528834

ISSN=2234-943X

ABSTRACT=ObjectiveTo identify key factors influencing early postoperative ambulation in patients undergoing partial nephrectomy for renal tumors and to construct a predictive model for day-one ambulation based on these factors.MethodsThis retrospective study analyzed 137 patients who underwent partial nephrectomy for renal tumors at the Department of Urology, Sun Yat-sen Memorial Hospital, between October 2020 and June 2023. Patients were randomly divided into a training set (n=97) and a test set (n=40) in a 7:3 ratio. Univariate and multivariate logistic regression analyses were conducted to evaluate potential risk factors influencing postoperative ambulation.ResultsOf the 137 patients, 116 were able to ambulate on the first postoperative day. Significant factors associated with early postoperative ambulation included age, hypertension, tumor size, serum cystatin C, blood urea nitrogen, renal artery clamping time, and intraoperative blood loss. A predictive model was constructed based on age, tumor size, and intraoperative blood loss, demonstrating strong accuracy with areas under the receiver operating characteristic (ROC) curve of 0.902 in the training set and 0.975 in the test set. Bootstrap calibration curves confirmed the model’s predictive accuracy, and decision curve analysis (DCA) demonstrated a substantial clinical benefit.ConclusionAge, tumor size, and intraoperative blood loss are key predictors of day-one ambulation in patients undergoing partial nephrectomy. This predictive model provides clinicians with a reliable tool for assessing early postoperative mobility, supporting enhanced recovery protocols and improving patient outcomes.