title: Robotic partial nephrectomy for small renal masses in patients with pre-existing chronic kidney disease.
abstract: OBJECTIVE
  To assess the outcomes of robotic partial nephrectomy in patients with pre-existing chronic kidney disease (CKD).
  
  
  METHODS
  Patients who underwent robotic partial nephrectomy for renal tumors between 2007 and 2011 were identified from our prospectively maintained institutional database. Perioperative as well as short-term oncological and functional outcomes were assessed. A comparative analysis was performed between patients with pre-existing CKD (estimated glomerular filtration rate [eGFR] 15-60 mL/min, group 1, n = 52) and patients with eGFR >60 mL/min (group 2, n = 303).
  
  
  RESULTS
  Group 1 patients were older (median 68 vs 57 years, P < .001), with higher American Society of Anesthesiology (ASA) score (3 vs 2, P < .001) and a higher Charlson comorbidity index (7 vs 4, P < .001). Warm ischemia time (WIT) was similar in both groups (18 vs 18 minutes, P = .52). Group 1 had a higher postoperative complication rate (40.4% vs 21.1%, P = .003). Pathologic and oncological data were similar. After a median follow-up of 3 months (interquartile: 1-10), deterioration of eGFR was lower in group 1 patients (-5% vs -12%, P = .004). No endstage renal disease was noted in either group. There was significantly less CKD upstaging in group 1 than in group 2 (11.5% vs 33.9%, P = .001). After multivariate analysis, preoperative eGFR and WIT were independent predictors of latest eGFR. Less than 15% of patients with normal baseline renal function developed CKD stage III or higher.
  
  
  CONCLUSIONS
  Despite a high risk of surgical complications, robotic partial nephrectomy only marginally affects renal function in patients with pre-existing CKD.
authors.affiliation: Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA.
authors.forename: Julien
authors.initials: J
authors.lastname: Guillotreau
authors.forename: Rachid
authors.initials: R
authors.lastname: Yakoubi
authors.forename: Jean-Alexandre
authors.initials: JA
authors.lastname: Long
authors.forename: Joseph
authors.initials: J
authors.lastname: Klink
authors.forename: Riccardo
authors.initials: R
authors.lastname: Autorino
authors.forename: Shahab
authors.initials: S
authors.lastname: Hillyer
authors.forename: Ranko
authors.initials: R
authors.lastname: Miocinovic
authors.forename: Emad
authors.initials: E
authors.lastname: Rizkala
authors.forename: Humberto
authors.initials: H
authors.lastname: Laydner
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Stein
authors.forename: Jihad H
authors.initials: JH
authors.lastname: Kaouk
authors.forename: Georges-Pascal
authors.initials: GP
authors.lastname: Haber
mesh_terms: D000368:Aged; D002292:Carcinoma, Renal Cell / Q000150:complications / Q000473:pathology / Q000601:surgery*; D003404:Creatinine / Q000097:blood; D005260:Female; D005500:Follow-Up Studies; D005919:Glomerular Filtration Rate; D006801:Humans; D007680:Kidney Neoplasms / Q000150:complications / Q000473:pathology / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009392:Nephrectomy / Q000009:adverse effects; D051436:Renal Insufficiency, Chronic / Q000097:blood / Q000150:complications / Q000503:physiopathology*; D012189:Retrospective Studies; D012371:Robotics; D012720:Severity of Illness Index; D016896:Treatment Outcome; D052096:Warm Ischemia
chemical_list: D003404:Creatinine