キクチ　エイジ   KIKUCHI EIJI
  菊地栄次
   所属   医学部医学科 腎泌尿器外科学
   職種   主任教授
論文種別 原著
言語種別 英語
査読の有無 査読あり
表題 Preserved Kidney Volume, Body Mass Index, and Age Are Significant Preoperative Factors for Predicting Estimated Glomerular Filtration Rate in Living Kidney Donors at 1 Year After Donation.
掲載誌名 正式名：Transplantation proceedings
略　 称：Transplant Proc
ISSNコード：1873262300411345
掲載区分国外
巻・号・頁 51(5),1306-1310頁
著者・共著者 Shinoda Kazunobu, Morita Shinya, Akita Hirotaka, Washizuka Fuyuki, Tamaki Satoshi, Takahashi Ryohei, Oguchi Hideyo, Sakurabayashi Kei, Mizutani Toshihide, Takahashi Yusuke, Hyodo Yoji, Itabashi Yoshihiro, Muramatsu Masaki, Kawamura Takeshi, Asanuma Hiroshi, Kikuchi Eiji, Jinzaki Masahiro, Shiraga Nobuyuki, Nakagawa Ken, Oya Mototsugu, Shishido Seiichiro, Sakai Ken
発行年月 2019/06
概要 BACKGROUND:Securing postdonation renal function in the lifetime of donors is a consequential subject for physicians, and precise prediction of postdonation renal function would be considerably beneficial when judging the feasibility of kidney donation. The aim of this study was to investigate the optimum model for predicting eGFR at 1 year after kidney donation.METHODS:We enrolled 101 living-related kidney donors for the development cohort and 44 for the external validation cohort. All patients in each cohort underwent thin-sliced (1 mm) enhanced computed tomography (CT) scans. We excluded individuals with diabetes, glucose intolerance, or albuminuria from this study. We evaluated preoperative factors including age, sex, hypertension, body mass index (BMI), serum uric acid, baseline eGFR, and body surface area (BSA)-adjusted preserved kidney volume (PKV) by using 3-dimensional reconstruction of thin-sliced enhanced CT images. To detect independent predictors, we performed multivariable regression analysis.RESULTS:The multivariable regression analysis revealed that age, BMI, predonation eGFR, and BSA-adjusted PKV were independent predictors of eGFR at 1 year after kidney donation (correlation coefficient: -0.15, -0.476, 0.521, 0.127, respectively). A strong correlation between predicted eGFR and observed eGFR was obtained in the development cohort (r = 0.839, P <.0001). The significance of this predictive model was also confirmed with the external validation cohort (r = 0.797, P <.0001).CONCLUSIONS:Age, BMI, predonation eGFR, and BSA-adjusted PKV may be useful for precisely predicting eGFR at 1 year after living kidney donation and be helpful to determine the feasibility of kidney donation from marginal donors.
DOI 10.1016/j.transproceed.2019.01.142
PMID 31076152

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