You have accessJournal of UrologyKidney Cancer: Localized: Surgical Therapy V (MP59)1 Sep 2021MP59-13 USEFULNESS OF THE MAYO ADHESIVE PROBABILITY SCORE AS A PREDICTIVE FACTOR FOR RENAL DYSFUNCTION AFTER PARTIAL NEPHRECTOMY Yu Endo, Yuki Yoshida, Yuta Matsuoka, Tomoyuki Koguchi, Junya Hata, Yuichi Sato, Hidenori Akaihata, Masao Kataoka, Soichiro Ogawa, and Yoshiyuki Kojima Yu EndoYu Endo More articles by this author , Yuki YoshidaYuki Yoshida More articles by this author , Yuta MatsuokaYuta Matsuoka More articles by this author , Tomoyuki KoguchiTomoyuki Koguchi More articles by this author , Junya HataJunya Hata More articles by this author , Yuichi SatoYuichi Sato More articles by this author , Hidenori AkaihataHidenori Akaihata More articles by this author , Masao KataokaMasao Kataoka More articles by this author , Soichiro OgawaSoichiro Ogawa More articles by this author , and Yoshiyuki KojimaYoshiyuki Kojima More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002094.13AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: In partial nephrectomy(PN), both cancer control and the preservation of postoperative renal function are important goals. The relationship between perinephric fat and renal dysfunction has recently been attracting a great deal of attention. Therefore, we hypothesized that the PNF environment in the preoperative period might be associated with renal dysfunction after PN. In this study, whether the Mayo adhesive probability (MAP) score, an index of the perinephric fat environment, could be a predictive factor for renal dysfunction after partial nephrectomy was investigated. METHODS: A retrospective case-control study of 78 patients who underwent laparoscopic partial nephrectomy was performed. an estimated glomerular filtration rate preservation rate at <90% at 1 month after surgery was defined as postoperative renal dysfunction. These patients were devided into two groups (non-dysfunction and dysfunction groups). The MAP score is calculated algorithmically from two measures: posterior renal fat thickness and the extent of PNF stranding around the kidney at the level of the renal vein on computed tomography. Patient factors including MAP scores(both tumor and unaffected sides) and surgical factors were evaluated to identify the predictors for postoperative renal dysfunction. The statistical analysis used univariate and multivariate logistic regression analysis. RESULTS: Forty-one (52.6%) patients had postoperative renal dysfunction. Univariate analysis identified MAP score on the unaffected side (p<0.01), sex (p=0.04), hypertension (p=0.02), benign or malignant (p=0.04), operative time (p=0.01), and warm ischemia time (p=0.01) as predictors of postoperative renal dysfunction. On multivariate analysis, MAP score on the unaffected side (p=0.04; odds ratio 1.40[1.05-1.95]) and warm ischemia time (p=0.03; odds ratio 1.04 [1.01-1.08]) were significantly associated with postoperative renal dysfunction. On receive operating characteristic curve analysis, MAP score on the unaffected side (p<0.01; cutoff value 1.5) and warm ischemia time (p=0.01; cutoff value 26.5 min) were significant predictors of renal dysfunction 1 month after surgery. CONCLUSIONS: The MAP score on the unaffected side and warm ischemia time are useful predictors for renal dysfunction after partial nephrectomy. In particular, the deterioration of the PNF environment, which is indicated by a high MAP score, might be related to renal dysfunction after PN. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e1035-e1035 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yu Endo More articles by this author Yuki Yoshida More articles by this author Yuta Matsuoka More articles by this author Tomoyuki Koguchi More articles by this author Junya Hata More articles by this author Yuichi Sato More articles by this author Hidenori Akaihata More articles by this author Masao Kataoka More articles by this author Soichiro Ogawa More articles by this author Yoshiyuki Kojima More articles by this author Expand All Advertisement Loading ...