Junichi Hoshino1, Ryoya Tsunoda2, Kei Nagai2, Hirayasu Kai2, Chie Saito2, Yukiko Ito3, Koichi Asahi4, Masahide Kondo5, Kunitoshi Iseki6, Chiho Iseki6, Hirokazu Okada7, Naoki Kashihara8, Ichiei Narita9, Takashi Wada10, Christian Combe11, Ronald L Pisoni12, Bruce M Robinson12, Kunihiro Yamagata13. 1. Nephrology Center, Toranomon Hospital, 2-2-2, Toranomon, Minato-ku, Tokyo, 105-8470, Japan. hoshino@toranomon.gr.jp. 2. Department of Nephrology, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. 3. Tsukuba Clinical Research & Development Organization (T-CReDO), University of Tsukuba, Tsukuba, Ibaraki, Japan. 4. Department of Nephrology and Hypertension, Iwate Medical University, Morioka, Japan. 5. Department of Health Care Policy and Health Economics, Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan. 6. Okinawa Heart and Renal Association, Naha, Okinawa, Japan. 7. Department of Nephrology, Saitama Medical University, Saitama, Japan. 8. Department of Nephrology and Hypertension, Kawasaki Medical School, Okayama, Japan. 9. Division of Clinical Nephrology and Rheumatology, Niigata University Graduate School of Medical and Dental Science, Niigata, Japan. 10. Department of Nephrology and Laboratory Medicine, Kanazawa University, Ishikawa, Japan. 11. Unité INSERM 1026 Biotis, Univ. Bordeaux, Bordeaux, France. 12. Arbor Research Collaborative for Health, Ann Arbor, MI, USA. 13. Department of Nephrology, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. k-yamaga@md.tsukuba.ac.jp.
Abstract
BACKGROUND: Disease-specific trajectories of renal function in advanced chronic kidney disease (CKD) are not well defined. Here, we compared these trajectories in the estimated glomerular filtration rate (eGFR) by CKD stages. METHODS: Patients with multiple eGFR measurements during the 5-year preregistration period of the REACH-J study were enrolled. Mean annual eGFR declines were calculated from linear mixed effect models with the adjustment variables of baseline CKD stage, age, sex and the current CKD stage and the level of proteinuria (CKDA1-3). RESULTS: Among 1,969 eligible patients with CKDG3b-5, the adjusted eGFR decline (ml/min/1.73 m2/year) was significantly faster in diabetic kidney disease (DKD) patients and polycystic kidney disease (PKD) patients than in patients with other kidney diseases (DKD, - 2.96 ± 0.13; PKD, - 2.82 ± 0.17; and others, - 1.95 ± 0.05, p < 0.01). The declines were faster with higher CKD stages. In DKD patients, the eGFR decline was significantly faster in CKDG5 than CKDG4 (- 4.10 ± 0.18 vs - 2.76 ± 0.20, p < 0.01), while these declines in PKD patients were similar. The eGFR declines in PKD patients were significantly faster than DKD patients in CKDG4 (- 2.92 ± 0.23 vs - 2.76 ± 0.20, p < 0.01) and in CKDA2 (- 3.36 ± 0.35 vs - 1.40 ± 0.26, p < 0.01). CONCLUSION: Our study revealed the disease-specific annual eGFR declines by CKD stages and the level of proteinuria. Comparing to the other kidney diseases, the declines in PKD patients were getting faster from early stages of CKD. These results suggest the importance of CKD managements in PKD patients from the early stages.
BACKGROUND: Disease-specific trajectories of renal function in advanced chronic kidney disease (CKD) are not well defined. Here, we compared these trajectories in the estimated glomerular filtration rate (eGFR) by CKD stages. METHODS: Patients with multiple eGFR measurements during the 5-year preregistration period of the REACH-J study were enrolled. Mean annual eGFR declines were calculated from linear mixed effect models with the adjustment variables of baseline CKD stage, age, sex and the current CKD stage and the level of proteinuria (CKDA1-3). RESULTS: Among 1,969 eligible patients with CKDG3b-5, the adjusted eGFR decline (ml/min/1.73 m2/year) was significantly faster in diabetic kidney disease (DKD) patients and polycystic kidney disease (PKD) patients than in patients with other kidney diseases (DKD, - 2.96 ± 0.13; PKD, - 2.82 ± 0.17; and others, - 1.95 ± 0.05, p < 0.01). The declines were faster with higher CKD stages. In DKD patients, the eGFR decline was significantly faster in CKDG5 than CKDG4 (- 4.10 ± 0.18 vs - 2.76 ± 0.20, p < 0.01), while these declines in PKD patients were similar. The eGFR declines in PKD patients were significantly faster than DKD patients in CKDG4 (- 2.92 ± 0.23 vs - 2.76 ± 0.20, p < 0.01) and in CKDA2 (- 3.36 ± 0.35 vs - 1.40 ± 0.26, p < 0.01). CONCLUSION: Our study revealed the disease-specific annual eGFR declines by CKD stages and the level of proteinuria. Comparing to the other kidney diseases, the declines in PKD patients were getting faster from early stages of CKD. These results suggest the importance of CKD managements in PKD patients from the early stages.