Literature DB >> 35263738

Impact of Glucose Tolerance and Its Change on Incident Proteinuria: Analysis of a Nationwide Population-Based Dataset.

Yuta Suzuki1,2, Hidehiro Kaneko1,3, Akira Okada4, Hidetaka Itoh1, Katsuhito Fujiu1,3, Nobuaki Michihata5, Taisuke Jo5, Norifumi Takeda1, Hiroyuki Morita1, Satoko Yamaguchi4, Kentaro Kamiya6, Atsuhiko Matsunaga2, Junya Ako7, Koichi Node8, Toshimasa Yamauchi9, Masaomi Nangaku10, Hideo Yasunaga11, Issei Komuro1.   

Abstract

INTRODUCTION: Although diabetes mellitus (DM) increases the risk of proteinuria, the relationship between prediabetes and proteinuria remains not fully understood. Further, whether the change in glucose is associated with the risk for proteinuria is unknown.
METHODS: This was a retrospective cohort study that included 1,849,074 participants (median age, 45 years; 59.3% men). No participants were taking glucose-lowering medications, and none had positive proteinuria at the initial health check-up. Each participant was categorized into three groups: normal (hemoglobin A1c [HbA1c] of <5.7%, n = 1,563,121), prediabetes (HbA1c of 5.7-6.4%, n = 253,490), and DM (HbA1c of ≥6.5%, n = 32,463) groups. We investigated the association between each HbA1c category and incident proteinuria using Cox proportional hazards models. We analyzed the association between the annual change in HbA1c and the risk for proteinuria.
RESULTS: A total of 65,954 participants developed proteinuria during the observation period. Not only DM (hazard ratio [HR]: 2.15, 95% confidence interval [CI]: 2.07-2.24) but also prediabetes (HR: 1.14, 95% CI: 1.12-1.17) was associated with a greater risk for proteinuria. The relative risk reduction for proteinuria that was associated with prediabetes and DM was 12.3% and 53.5%, respectively. An annual increase in HbA1c was associated with a greater risk for proteinuria. This association was more pronounced in participants having prediabetes.
CONCLUSION: Not only DM but also prediabetes increased the risk for proteinuria. The influence of change in HbA1c on incident proteinuria was pronounced in people with prediabetes. Optimizing glucose would provide more benefit to individuals having prediabetes for proteinuria prevention.
© 2022 The Author(s). Published by S. Karger AG, Basel.

Entities:  

Keywords:  Diabetes mellitus; Epidemiology; Prediabetes; Proteinuria

Mesh:

Substances:

Year:  2022        PMID: 35263738      PMCID: PMC9216314          DOI: 10.1159/000522280

Source DB:  PubMed          Journal:  Am J Nephrol        ISSN: 0250-8095            Impact factor:   4.605


  37 in total

Review 1.  Japanese Clinical Practice Guideline for Diabetes 2016.

Authors:  Masakazu Haneda; Mitsuhiko Noda; Hideki Origasa; Hiroshi Noto; Daisuke Yabe; Yukihiro Fujita; Atsushi Goto; Tatsuya Kondo; Eiichi Araki
Journal:  Diabetol Int       Date:  2018-03-27

2.  Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis.

Authors:  Kunihiro Matsushita; Marije van der Velde; Brad C Astor; Mark Woodward; Andrew S Levey; Paul E de Jong; Josef Coresh; Ron T Gansevoort
Journal:  Lancet       Date:  2010-05-17       Impact factor: 79.321

Review 3.  2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2021.

Authors: 
Journal:  Diabetes Care       Date:  2021-01       Impact factor: 19.112

4.  Diagnostic accuracy of urine dipstick for proteinuria category in Japanese workers.

Authors:  Tomoko Usui; Yui Yoshida; Hiroshi Nishi; Shintaro Yanagimoto; Yutaka Matsuyama; Masaomi Nangaku
Journal:  Clin Exp Nephrol       Date:  2019-11-16       Impact factor: 2.801

5.  Proteinuria as a surrogate outcome in CKD: report of a scientific workshop sponsored by the National Kidney Foundation and the US Food and Drug Administration.

Authors:  Andrew S Levey; Daniel Cattran; Aaron Friedman; W Greg Miller; John Sedor; Katherine Tuttle; Bertram Kasiske; Thomas Hostetter
Journal:  Am J Kidney Dis       Date:  2009-07-03       Impact factor: 8.860

Review 6.  2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020.

Authors: 
Journal:  Diabetes Care       Date:  2020-01       Impact factor: 19.112

7.  Analysis of partially observed clustered data using generalized estimating equations and multiple imputation.

Authors:  Kathryn M Aloisio; Sonja A Swanson; Nadia Micali; Alison Field; Nicholas J Horton
Journal:  Stata J       Date:  2014-10-01       Impact factor: 2.637

8.  Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage.

Authors:  Shinya Kimura; Toshihiko Sato; Shunya Ikeda; Mitsuhiko Noda; Takeo Nakayama
Journal:  J Epidemiol       Date:  2010-08-07       Impact factor: 3.211

9.  Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant-Based Meta-analysis.

Authors:  Keiichi Sumida; Girish N Nadkarni; Morgan E Grams; Yingying Sang; Shoshana H Ballew; Josef Coresh; Kunihiro Matsushita; Aditya Surapaneni; Nigel Brunskill; Steve J Chadban; Alex R Chang; Massimo Cirillo; Kenn B Daratha; Ron T Gansevoort; Amit X Garg; Licia Iacoviello; Takamasa Kayama; Tsuneo Konta; Csaba P Kovesdy; James Lash; Brian J Lee; Rupert W Major; Marie Metzger; Katsuyuki Miura; David M J Naimark; Robert G Nelson; Simon Sawhney; Nikita Stempniewicz; Mila Tang; Raymond R Townsend; Jamie P Traynor; José M Valdivielso; Jack Wetzels; Kevan R Polkinghorne; Hiddo J L Heerspink
Journal:  Ann Intern Med       Date:  2020-07-14       Impact factor: 25.391

10.  The retinopathy-derived HbA1c threshold of 6.5% for type 2 diabetes also captures the risk of diabetic nephropathy in NHANES.

Authors:  Stephen L Atkin; Alexandra E Butler; Steven C Hunt; Eric S Kilpatrick
Journal:  Diabetes Obes Metab       Date:  2021-06-09       Impact factor: 6.577

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