Patients with pathologically proven renal disease have similar declines in renal function following robot-assisted partial nephrectomy - Abstract

OBJECTIVE: To determine if patients with pathological, medical renal disease, defined as evidence of pathological abnormalities indicative of renal damage in the non-neoplastic partial nephrectomy specimens, have worsened functional outcomes following robot-assisted partial nephrectomy.

MATERIALS AND METHODS: Sixty patients with and 101 without pathologically proven renal disease on non-neoplastic renal specimens were evaluated for differences in postoperative outcomes following robot-assisted partial nephrectomy. Multiple linear regression modeling assessed for factors influencing early and late declines in renal function.

RESULTS: The two groups were similar in all preoperative parameters. Both patients with and without pathological renal disease had similar lengths of hospitalization, transfusions, and complication rates. The percent change in glomerular filtration rate was similar for patients with and without pathological renal disease (-8.8% vs. -12.2%, p=0.194). Patients with pathological renal disease had less chronic kidney disease upstaging than patients without renal disease (18.3% vs. 39.6%, p=0.006). Increasing age (p=0.030) and higher preoperative glomerular filtration rates (p=0.044) predicted worse late percentage declines in renal function, while increased warm ischemia time predicted late chronic kidney disease upstaging (p=0.043).

CONCLUSION: The presence of pathological renal disease in non-neoplastic renal tissue did not place patients at risk for worsened postoperative complications or renal function deterioration following robot-assisted partial nephrectomy.

Written by:
Mobley JM, Kim EH, Larson JA, Figenshau RS, Vetter JM, Johnson MH, Bhayani S.   Are you the author?
Washington University School of Medicine, Division of Urology, 4960 Children's Place, Campus Box 8242, St. Louis, Missouri, United States.  

Reference: J Endourol. 2014 Aug 6. Epub ahead of print.
doi: 10.1089/end.2014-0228.ECC14


PubMed Abstract
PMID: 25100054

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