Predictive value of R.E.N.A.L. nephrometry score in robotic assisted partial nephrectomy

Abstract

Abstract Objective: In this study, we evaluated the predictive value of R.E.N.A.L. Nephrometry Score (RNS), a system to standardize the renal tumors according to size, location, and depth, for surgical outcomes of robotic partial nephrectomy. Materials and methods: Twenty-nine cases who underwent robotic partial nephrectomy in two institutions between 2008 and 2010 were included in the study. RNS was calculated from preoperative computed tomography and/or magnetic resonance images by considering tumor size, exophytic/endophytic properties, distance to the collecting system, anterior or posterior location, and distance to the polar lines. Total RNS less than 7 was considered as low and ≥7 as high complexity lesions. Operative time, estimated blood loss, warm ischemia time, and positive surgical margin were analyzed. Results: There were 14 low complexity tumors with a mean RNS of 5 and 15 high complexity tumors with a mean RNS of 7.9. The mean warm ischemia time was 18.6 min in low complexity tumors and 29.8 min in high complexity tumors (p=0.01). There was a strong positive correlation between RNS and warm ischemia time (r=0.57, p=0.002). The difference between low and high complexity tumors was not statistically significant in terms of operative time, estimated blood loss, length of hospital stay, and positive surgical margins. Conclusion: Preoperative RNS can predict the warm ischemia time in robotic assisted partial nephrectomy. High RNS results in longer warm ischemia time. RNS may be useful in determining surgical approach to preserve renal function in high-risk patients.