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

Kazunobu Shinoda, Shinya Morita, Hirotaka Akita, Fuyuki Washizuka, Satoshi Tamaki, Ryohei Takahashi, Hideyo Oguchi, Kei Sakurabayashi, Toshihide Mizutani, Yusuke Takahashi, Yoji Hyodo, Yoshihiro Itabashi, Masaki Muramatsu, Takeshi Kawamura, Hiroshi Asanuma, Eiji Kikuchi, Masahiro Jinzaki, Nobuyuki Shiraga, Ken Nakagawa, Mototsugu OyaSeiichiro Shishido, Ken Sakai

研究成果: Article

抄録

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.

元の言語English
ジャーナルTransplantation Proceedings
DOI
出版物ステータスPublished - 2019 1 1

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Living Donors
Glomerular Filtration Rate
Body Mass Index
Kidney
Body Surface Area
Tissue Donors
Tomography
Regression Analysis
Albuminuria
Glucose Intolerance
Age Factors
Uric Acid
Hypertension
Physicians

ASJC Scopus subject areas

  • Surgery
  • Transplantation

これを引用

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. / 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.

:: Transplantation Proceedings, 01.01.2019.

研究成果: Article

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. / 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. :: Transplantation Proceedings. 2019.
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abstract = "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.",
author = "Kazunobu Shinoda and Shinya Morita and Hirotaka Akita and Fuyuki Washizuka and Satoshi Tamaki and Ryohei Takahashi and Hideyo Oguchi and Kei Sakurabayashi and Toshihide Mizutani and Yusuke Takahashi and Yoji Hyodo and Yoshihiro Itabashi and Masaki Muramatsu and Takeshi Kawamura and Hiroshi Asanuma and Eiji Kikuchi and Masahiro Jinzaki and Nobuyuki Shiraga and Ken Nakagawa and Mototsugu Oya and Seiichiro Shishido and Ken Sakai",
year = "2019",
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T1 - 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

AU - Shinoda, Kazunobu

AU - Morita, Shinya

AU - Akita, Hirotaka

AU - Washizuka, Fuyuki

AU - Tamaki, Satoshi

AU - Takahashi, Ryohei

AU - Oguchi, Hideyo

AU - Sakurabayashi, Kei

AU - Mizutani, Toshihide

AU - Takahashi, Yusuke

AU - Hyodo, Yoji

AU - Itabashi, Yoshihiro

AU - Muramatsu, Masaki

AU - Kawamura, Takeshi

AU - Asanuma, Hiroshi

AU - Kikuchi, Eiji

AU - Jinzaki, Masahiro

AU - Shiraga, Nobuyuki

AU - Nakagawa, Ken

AU - Oya, Mototsugu

AU - Shishido, Seiichiro

AU - Sakai, Ken

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

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U2 - 10.1016/j.transproceed.2019.01.142

DO - 10.1016/j.transproceed.2019.01.142

M3 - Article

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JO - Transplantation Proceedings

JF - Transplantation Proceedings

SN - 0041-1345

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