Yuta Matsukuma1, Kosuke Masutani2,3, Shigeru Tanaka4, Akihiro Tsuchimoto1, Toshiaki Nakano1, Yasuhiro Okabe5, Yoichi Kakuta6, Masayoshi Okumi6, Kazuhiko Tsuruya7, Masafumi Nakamura5, Takanari Kitazono1, Kazunari Tanabe6. 1. Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan. 2. Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan. kmasutani@fukuoka-u.ac.jp. 3. Division of Nephrology and Rheumatology, Department of Internal Medicine, Faculty of Medicine, Fukuoka University, Fukuoka, Japan. kmasutani@fukuoka-u.ac.jp. 4. Division of Internal Medicine, Fukuoka Dental College, Fukuoka, Japan. 5. Department of Surgery and Oncology, Kyushu University, Fukuoka, Japan. 6. Department of Urology, Tokyo Women's Medical University, Tokyo, Japan. 7. Department of Nephrology, Nara Medical University, Nara, Japan.
Abstract
BACKGROUND: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. METHODS: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women's Medical University Hospital (validation cohort). RESULTS: In the derivation cohort, 89 patients (25.9%) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donor hypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer-Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donor hypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the "zero-time" biopsy. CONCLUSIONS: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.
BACKGROUND: Recently, living-donor kidney transplantation from marginal donors has been increasing. However, a simple prediction model for graft function including preoperative marginal factors is limited. Here, we developed and validated a new prediction model for graft function using preoperative marginal factors in living-donor kidney transplantation. METHODS: We retrospectively investigated 343 patients who underwent living-donor kidney transplantation at Kyushu University Hospital (derivation cohort). Low graft function was defined as an estimated glomerular filtration rate of < 45 mL/min/1.73 m2 at 1 year. A prediction model was developed using a multivariable logistic regression model, and verified using data from 232 patients who underwent living-donor kidney transplantation at Tokyo Women's Medical University Hospital (validation cohort). RESULTS: In the derivation cohort, 89 patients (25.9%) had low graft function at 1 year. Donor age, donor-estimated glomerular filtration rate, donorhypertension, and donor/recipient body weight ratio were selected as predictive factors. This model demonstrated modest discrimination (c-statistic = 0.77) and calibration (Hosmer-Lemeshow test, P = 0.83). Furthermore, this model demonstrated good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test, P = 0.54) in the validation cohort. Furthermore, donor age, donor-estimated glomerular filtration rate, and donorhypertension were strongly associated with glomerulosclerosis and atherosclerotic vascular changes in the "zero-time" biopsy. CONCLUSIONS: This model using four pre-operative variables will be a simple, but useful guide to estimate graft function at 1 year after kidney transplantation, especially in marginal donors, in the clinical setting.
Authors: R B Munivenkatappa; E J Schweitzer; J C Papadimitriou; C B Drachenberg; K A Thom; E N Perencevich; A Haririan; F Rasetto; M Cooper; L Campos; R N Barth; S T Bartlett; B Philosophe Journal: Am J Transplant Date: 2008-09-17 Impact factor: 8.086
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