J-CKD-DB: a nationwide multicentre electronic health record-based chronic kidney disease database in Japan

Naoki Nakagawa, Tadashi Sofue, Eiichiro Kanda, Hajime Nagasu, Kunihiro Matsushita, Masaomi Nangaku, Shoichi Maruyama, Takashi Wada, Yoshio Terada, Kunihiro Yamagata, Ichiei Narita, Motoko Yanagita, Hitoshi Sugiyama, Takashi Shigematsu, Takafumi Ito, Kouichi Tamura, Yoshitaka Isaka, Hirokazu Okada, Kazuhiko Tsuruya, Hitoshi YokoyamaNaoki Nakashima, Hiromi Kataoka, Kazuhiko Ohe, Mihoko Okada, Naoki Kashihara

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31 Citations (Scopus)


The Japan Chronic Kidney Disease (CKD) Database (J-CKD-DB) is a large-scale, nation-wide registry based on electronic health record (EHR) data from participating university hospitals. Using a standardized exchangeable information storage, the J-CKD-DB succeeded to efficiently collect clinical data of CKD patients across hospitals despite their different EHR systems. CKD was defined as dipstick proteinuria ≥1+ and/or estimated glomerular filtration rate <60 mL/min/1.73 m2 base on both out- and inpatient laboratory data. As an initial analysis, we analyzed 39,121 CKD outpatients (median age was 71 years, 54.7% were men, median eGFR was 51.3 mL/min/1.73 m2) and observed that the number of patients with a CKD stage G1, G2, G3a, G3b, G4 and G5 were 1,001 (2.6%), 2,612 (6.7%), 23,333 (59.6%), 8,357 (21.4%), 2,710 (6.9%) and 1,108 (2.8%), respectively. According to the KDIGO risk classification, there were 30.1% and 25.5% of male and female patients with CKD at very high-risk, respectively. As the information from every clinical encounter from those participating hospitals will be continuously updated with an anonymized patient ID, the J-CKD-DB will be a dynamic registry of Japanese CKD patients by expanding and linking with other existing databases and a platform for a number of cross-sectional and prospective analyses to answer important clinical questions in CKD care.

Original languageEnglish
Article number7351
JournalScientific reports
Issue number1
Publication statusPublished - Dec 1 2020

All Science Journal Classification (ASJC) codes

  • General


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