Abstract

BackgroundAlthough the effect of tumor complexity on perioperative outcome measures is well established, the impact of renal pelvic anatomy on perioperative outcomes remains poorly defined. ObjectiveTo evaluate renal pelvic anatomy as an independent predictor of urine leak in moderate- and high-complexity tumors undergoing nephron-sparing surgery. Design, setting, and participantsPatients undergoing open partial nephrectomy (PN) for localized RCC were stratified into intermediate- and high-complexity groups using a nephrometry score (7–9 and 10–12, respectively). A renal pelvic score (RPS) was defined by the percentage of renal pelvis contained inside the volume of the renal parenchyma. On this basis, patients were categorized as having an intraparenchymal (>50%) or extraparenchymal (<50%) renal pelvis. Outcome measurements and statistical analysisCharacteristics of patients with and without an intraparenchymal renal pelvic anatomy were compared. Results and limitationsInclusion criteria were met by 255 patients undergoing PN for intermediate (73.6%) and complex (26.4%) localized renal tumors (mean size: 4.6±2.9cm). Twenty-four (9.6%) renal pelves were classified as completely intraparenchymal. Following stratification by RPS, groups differed with respect to Charlson comorbidity index, body mass index, and largest tumor size, while no differences were observed between hospital length of stay, nephrometry score, estimated blood loss, operative time, and age. Intrarenal pelvic anatomy was associated with a markedly increased risk of urine leak (75% vs 6.5%; p=0.001), secondary intervention (37.5% vs 3.9%; p<0.001), and prolonged duration of urine leak (93±62 d vs 56±29 d; p=0.025). ConclusionsIntraparenchymal renal pelvic anatomy is an uncommon anatomic variant associated with an increased rate of urine leak following PN. Elevated pressures within a small intraparenchymal renal pelvis might explain the increased risk. Preoperative imaging characteristics suggestive of increased risk for urine leak should be considered in perioperative management algorithms.

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