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

• Nakagawa, Naoki

• Sofue, Tadashi

• Kanda, Eiichiro

• Nagasu, Hajime

• Matsushita, Kunihiro

• Nangaku, Masaomi

• Maruyama, Shoichi

• Wada, Takashi

• Terada, Yoshio

• Yamagata, Kunihiro

• Narita, Ichiei

• Yanagita, Motoko

• Sugiyama, Hitoshi

• Shigematsu, Takashi

• Ito, Takafumi

• Tamura, Kouichi

• Isaka, Yoshitaka

• Okada, Hirokazu

• Tsuruya, Kazuhiko

• Yokoyama, Hitoshi

• Nakashima, Naoki

• Kataoka, Hiromi

• Ohe, Kazuhiko

• Okada, Mihoko

• Kashihara, Naoki

Abstract

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.

Journal

• Scientific reports

  Scientific reports 10 7351-, 2020

  Springer Nature

Keywords

• Multidisciplinary

Details

• CRID: 1050005667219994496
• NII Article ID: 120006958093
• ISSN: 20452322
• DOI: 10.1038/s41598-020-64123-z
• HANDLE: 2433/261691
• Web Site: https://www.nature.com/articles/s41598-020-64123-z.pdf
• Web Site: https://www.nature.com/articles/s41598-020-64123-z
• Text Lang: en
• Article Type: journal article
• Data Source:
  • IRDB
  • Crossref
  • CiNii Articles
  • KAKEN