Usefulness of subclassification of adult diabetes mellitus among inpatients in Japan

Kohei Saito, Tatsuhide Inoue, Hiroyuki Ariyasu, Toshio Shimada, Hiroshi Itoh, Issei Tanaka, Chikashi Terao

Research output: Contribution to journalArticlepeer-review

Abstract

Aims/Introduction: We aimed to replicate a new diabetes subclassification based on objective clinical information at admission in a diabetes educational inpatient program. We also assessed the educational outcomes for each cluster. Methods: We included diabetes patients who participated in the educational inpatient program during 2009–2020 and had sufficient clinical information for the cluster analysis. We applied a data-driven clustering method proposed in a previous study and further evaluated the clinical characteristics of each cluster. We investigated the association between the clusters and changes in hemoglobin A1c level from the start of the education program. We also assessed the risk of re-admission for the educational program. Results: We divided a total of 651 patients into five clusters. Their clinical characteristics followed the same pattern as in previous studies. The intercluster ranking of the cluster center coordinates showed strong correlation coefficients with those of the previous studies (mean ρ = 0.88). Patients classified as severe insulin-resistant diabetes (cluster 3) showed a more pronounced progression of renal dysfunction than patients classified as the other clusters. The patients classified as severe insulin-deficient diabetes (cluster 2) had the highest rate of reduction in hemoglobin A1c level from the start of the program (P < 0.01) and a tendency toward a lower risk of re-admission for the education program (hazard ratio 0.47, P = 0.09). Conclusion: We successfully replicated the diabetes subclassification using objective clinical information at admission for the education program. In addition, we showed that severe insulin-deficient diabetes patients tended to have better educational outcomes than patients classified as the other clusters.

Original languageEnglish
Pages (from-to)706-713
Number of pages8
JournalJournal of Diabetes Investigation
Volume13
Issue number4
DOIs
Publication statusPublished - 2022 Apr

Keywords

  • Homeostasis model assessment
  • Type 1 diabetes
  • Type 2 diabetes

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

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