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Risk of chronic kidney disease defined by decreased estimated glomerular filtration rate in individuals with different prediabetic phenotypes: results from a prospective cohort study in China
  1. Wei Li1,
  2. Anping Wang2,
  3. Jiajia Jiang1,
  4. Guangxu Liu1,
  5. Meiping Wang1,
  6. Dongxue Li1,
  7. Jing Wen1,
  8. Yiming Mu2,
  9. Xiaoyan Du3,
  10. Herbert Gaisano4,
  11. Jingtao Dou2,
  12. Yan He5
  1. 1Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China
  2. 2Department of Endocrinology, Chinese PLA General Hospital, Beijing, China
  3. 3Department of Laboratory Animal, School of Basic Medical Sciences, Capital Medical University, Beijing, China
  4. 4Departments of Medicine and Physiology, University of Toronto, Toronto, Ontario, Canada
  5. 5Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
  1. Correspondence to Dr Yan He; yanhe1220{at}126.com; Professor Jingtao Dou; jingtaodou{at}163.com

Abstract

Objective We aimed to investigate the effects of prediabetes and its phenotypes of impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and elevated glycated hemoglobin A1c (EHbA1c) on chronic kidney disease (CKD) occurrence, and define the cut-off point of each glycemic index that significantly increases the risk of CKD.

Research design and methods In this prospective cohort study, 6446 non-diabetic subjects aged 40 years and over were followed over a period of 3 years to track the new onset of CKD. Cox regression was used to assess the association of prediabetes and its phenotypes with CKD. Receiver operating characteristic curves were used to define the cut-off point of each glycemic index that significantly increases the occurrence of CKD. Population attributable risk percent was calculated to estimate the contribution of prediabetes to CKD.

Results Compared to subjects with normal glucose tolerance, patients with prediabetes significantly increased the risk of development of CKD (HR=2.33 (1.19–4.55)). Specifically, this increased risk of CKD development was observed in patients with IFG, IGT and EHbA1c. The cut-off points shown to significantly increase the risk of CKD are fasting plasma glucose of 5.63 mmol/L, 2-hour plasma glucose of 6.80 mmol/L and HbA1c of 5.6%. The contribution of prediabetes to CKD occurrence in the study population was 60.6%.

Conclusions This result suggests that the stricter criteria might be needed to define normal plasma glucose level in China that would not be predisposed to diabetic complications, particularly CKD.

  • chronic kidney disease
  • prediabetes
  • HbA1c
  • population-based studies
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Footnotes

  • WL and AW are joint first authors.

  • WL and AW contributed equally.

  • Contributors WL and AW carried out the statistical analyses and drafted the manuscript. They contributed equally to this study and share first authorship. JJ, GL and MW participated in the data analysis. DL and JW participated in the literature search. YM and XD participated in the data collection, study management and study coordination. HG contributed to correct English language. JD and YH contributed to the study design and review of this manuscript. All authors read and approved the final manuscript.

  • Funding This study was supported by National Natural Science Foundation of China (grant number: 31672375) to YH and National Science and Technology Major Project (grant number: 2018ZX 09201013) to JD.

  • Disclaimer Funding organizations had no role in any aspect of the research or manuscript preparation.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Ethics approval This study was approved by the Medical Ethics Committee of Ruijin Hospital, Shanghai Jiaotong University.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data may be obtained from a third party and are not publicly available. Information on how to access the data can be found on these contact details: Phone: 86-010-5549-9402 Email: jingtaodou@163.com.