Abstract

Objective: The aim of this study is to compare the precision and applicability of the Zhongshan (ZS) score against the radius, exophytic/endophytic, nearness, anterior/posterior, and location (RENAL) score in forecasting perioperative outcomes during laparoscopic partial nephrectomy (LPN). Materials and Methods: We retrospectively analyzed data from 99 renal cancer patients who underwent LPN between January 2017 and August 2023. Patients were scored and categorized based on both the ZS and RENAL scores. The study then compared perioperative outcomes across these groups and further investigated the correlation between ZS and RENAL scores and overall complication rates. Results: LPN was successfully accomplished in 94 patients, whereas 5 patients necessitated conversion to open or radical surgery. The high-risk group, according to the ZS score, manifested more warm ischemic time (WIT) than the low-risk group (P = .007). Furthermore, the incidence of overall complications escalated with increase in the ZS score grade (P = .045). A higher RENAL score corresponded to a greater risk of conversion to open or radical treatment (P = .012). Correlation analyses revealed associations between both ZS and RENAL scores and overall complications. The RENAL score also correlated with changes in blood creatinine values, while the ZS score was associated with WIT (all P < .05). In the univariate analysis, both ZS and RENAL scores were substantial factors for the occurrence of total complications (P = .029 and P = .027, respectively), but they were not statistically significant in the multivariate analysis. The receiver operating characteristic curves suggested that both individual and combined ZS and RENAL scores held predictive potential for the onset of overall complications (area under the curve = 0.652, 0.660, and 0.676, respectively). Conclusions: Compared with the RENAL score, the ZS score provides a more comprehensive assessment of tumor complexity in patients undergoing LPN. Integrating these two scores could potentially improve the accuracy of predicting surgical risks.

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