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- Title
A Combination of the Mayo Adhesive Probability Score and the RENAL Score to Predict Intraoperative Complications in Small Renal Masses.
- Authors
Jin, Dachun; Zhang, Junyong; Zhang, Yuanfeng; Ren, Dong; Xu, Guangyong; Ge, Chengguo; Wang, Delin; Zhang, Weili
- Abstract
Introduction: To evaluate the potential predictive value of the Mayo Adhesive Probability (MAP) score combined with the RENAL score for intraoperative outcomes in retroperitoneal laparoscopic nephron-sparing surgery (NSS) in an Eastern Asian population. Methods: An initial of 388 patients undergoing retroperitoneal laparoscopic NSS were identified. MAP and RENAL scores were calculated according to CT and a logistic regression model was adopted as a combination of the RENAL score and the MAP score. Results: A total of 293 patients were included. The overall intraoperative complication rate was 7.5% (21 cases). The MAP score was found to correlate with operation time (OT; r = 0.169), estimated blood loss (EBL; r = 0.318), and intraoperative complications (r = 0.242). The RENAL score was correlated with warm is-chemia time (r = 0.503), OT (r = 0.334), intraoperative complications (r = 0.178), and EBL (r = 0.218). The MAP score and the RENAL score were reliable predictors of overall intraoperative complications, with areas under the curve (AUC) of 0.728 and 0.759, respectively. After combination of these 2 scores, the AUC of overall intra-operative complications was improved with statistical significance (AUC = 0.847, combination vs. RENAL score: p = 0.044 < 0.05; combination vs. MAP score: p = 0.005 < 0.05). Conclusion: The MAP score is an important predictor of EBL, OT, and intraoperative complications in retroperitoneal laparoscopic NSS and its combination with the RENAL score showed a superior predictive value compared to a single score in overall intraoperative complications. The MAP score might be considered in preoperative radiologic aspects as regularly as the RENAL score.
- Subjects
SURGICAL complications; ASIANS; LAPAROSCOPIC surgery; PROBABILITY theory; LOGISTIC regression analysis
- Publication
Urologia Internationalis, 2020, Vol 104, Issue 1/2, p142
- ISSN
0042-1138
- Publication type
Article
- DOI
10.1159/000504767