title: Correlation of the RENAL nephrometry score with warm ischemia time after robotic partial nephrectomy.
abstract: OBJECTIVE
  The RENAL nephrometry score (RNS) was developed to quantify complexity of renal tumors in a reproducible manner. We aim to determine whether individual categories of the RNS have different impact on the warm ischemia time (WIT) for patients undergoing robotic partial nephrectomy (RPN).
  
  
  METHODS
  In a retrospective analysis of a prospectively maintained database, we identified 251 consecutive patients who underwent RPN between January 2007 and June 2010. RNS was determined in 187 with available imaging. Univariable analysis and multivariable linear regression analysis were performed to identify which factors were more significantly associated with WIT.
  
  
  RESULTS
  Overall RNS was of low (4-6), moderate (7-9), and high complexity (10-12) in 84 (45 %), 80 (43 %), and 23 (12 %) patients, respectively. There was no association between gender (p = 0.6), BMI (p = 0.3), or anterior/posterior location (A) (p = 0.8), and WIT. On univariable analysis, longer WIT was associated with size (R) >4 cm (p < 0.0001), entirely endophytic properties (E) (p = 0.005), tumor <4 mm from the collecting system/sinus (N) (p < 0.0001), and location between the polar lines (L) (p = 0.004). Total RNS and WIT were highly correlated (Spearman correlation coefficient = 0.54, p < 0.0001). There was a significant trend of higher WIT with increased tumor complexity (p for trend <0.0001). After multivariable analysis, only R (p = 0.0003), E (p = 0.003), and N (p = 0.00002) components of the RNS were significantly associated with WIT.
  
  
  CONCLUSIONS
  The A and L subcategories of the RNS have no significant impact on the WIT of patients undergoing RPN. WIT is significantly dependent upon the other subcategories, as well as the overall RNS. These findings can be used to preoperatively predict which tumor characteristics will likely affect WIT and may be useful in preoperative counseling as well as planning of approach.
authors.affiliation: Center for Laparoscopic and Robotic Surgery-Urology, Glickman Urology and Kidney Institute, Cleveland Clinic Foundation, 9500, Euclid Avenue, Q10-1, Cleveland, OH, 44195, USA.
authors.forename: Fatih
authors.initials: F
authors.lastname: Altunrende
authors.forename: Humberto
authors.initials: H
authors.lastname: Laydner
authors.forename: Adrian V
authors.initials: AV
authors.lastname: Hernandez
authors.forename: Riccardo
authors.initials: R
authors.lastname: Autorino
authors.forename: Rakesh
authors.initials: R
authors.lastname: Khanna
authors.forename: Michael A
authors.initials: MA
authors.lastname: White
authors.forename: Wahib
authors.initials: W
authors.lastname: Isac
authors.forename: Gregory
authors.initials: G
authors.lastname: Spana
authors.forename: Shahab
authors.initials: S
authors.lastname: Hillyer
authors.forename: Bo
authors.initials: B
authors.lastname: Yang
authors.forename: Rachid
authors.initials: R
authors.lastname: Yakoubi
authors.forename: Georges-Pascal
authors.initials: GP
authors.lastname: Haber
authors.forename: Jihad H
authors.initials: JH
authors.lastname: Kaouk
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Stein
mesh_terms: D000368:Aged; D005260:Female; D005919:Glomerular Filtration Rate / Q000502:physiology; D006801:Humans; D007668:Kidney / Q000473:pathology / Q000502:physiology* / Q000601:surgery; D007680:Kidney Neoplasms / Q000503:physiopathology / Q000601:surgery*; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009392:Nephrectomy / Q000379:methods*; D011446:Prospective Studies; D012189:Retrospective Studies; D012371:Robotics; D012720:Severity of Illness Index; D016896:Treatment Outcome; D052096:Warm Ischemia