Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ASCO Annual Meeting 2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

2024 ASCO Annual Meeting

Keep up to date with all the top stories and latest evidence with our hub page, including official congress videos and expert takeaways.
ADVANCED SEARCH
Log in
Top
Cardiovascular Diabetology
Published in: Cardiovascular Diabetology 1/2020

Open Access 01-12-2020 | Stroke | Original investigation

Glucose variability and the risks of stroke, myocardial infarction, and all-cause mortality in individuals with diabetes: retrospective cohort study

Authors: Da Young Lee, Kyungdo Han, Sanghyun Park, Ji Hee Yu, Ji A. Seo, Nam Hoon Kim, Hye Jin Yoo, Sin Gon Kim, Kyung Mook Choi, Sei Hyun Baik, Yong Gyu Park, Nan Hee Kim

Published in: Cardiovascular Diabetology | Issue 1/2020

Login to get access

Abstract

Background

Previous research regarding long-term glucose variability over several years which is an emerging indicator of glycemic control in diabetes showed several limitations. We investigated whether variability in long-term fasting plasma glucose (FG) can predict the development of stroke, myocardial infarction (MI), and all-cause mortality in patients with diabetes.

Methods

This is a retrospective cohort study using the data provided by the Korean National Health Insurance Corporation. A total of 624,237 Koreans ≥ 20 years old with diabetes who had undergone health examinations at least twice from 2005 to 2008 and simultaneously more than once from 2009 to 2010 (baseline) without previous histories of stroke or MI. As a parameter of variability of FG, variability independent of mean (VIM) was calculated using FG levels measured at least three times during the 5 years until the baseline. Study endpoints were incident stroke, MI, and all-cause mortality through December 31, 2017.

Results

During follow-up, 25,038 cases of stroke, 15,832 cases of MI, and 44,716 deaths were identified. As the quartile of FG VIM increased, the risk of clinical outcomes serially increased after adjustment for confounding factors including duration and medications of diabetes and the mean FG. Adjusted hazard ratios (95% confidence intervals) of FG VIM quartile 4 compared with quartile 1 were 1.20 (1.16–1.24), 1.20 (1.15–1.25), and 1.32 (1.29–1.36) for stroke, MI and all-cause mortality, respectively. The impact of FG variability was higher in the elderly and those with a longer duration of diabetes and lower FG levels.

Conclusions

In diabetes, long-term glucose variability showed a dose–response relationship with the risk of stroke, MI, and all-cause mortality in this nationwide observational study.
Appendix
Available only for authorised users
Literature
1.
6 Glycemic Targets: standards of medical care in diabetes-2018. Diabetes Care. 2018;41:S55-S64.
2.
Wan EYF, Yu EYT, Fung CSC, Chin WY, Fong DYT, Chan AKC, et al. Relation between HbA1c and incident cardiovascular disease over a period of 6 years in the Hong Kong population. Diabetes Metab. 2018;44:415–23.PubMed
3.
Arem H, Moore SC, Patel A, Hartge P, de Gonzalez BA, Visvanathan K, et al. Leisure time physical activity and mortality: a detailed pooled analysis of the dose-response relationship. JAMA Intern Med. 2015;175:959–67.PubMedPubMedCentral
4.
Škrha J, Šoupal J, Škrha J Jr, Prázný M. Glucose variability, HbA1c and microvascular complications. Rev Endocrine Metab Disorders. 2016;17:103–10.
5.
Siegelaar SE, Holleman F, Hoekstra JBL, DeVries JH. Glucose variability; does it matter? Endocr Rev. 2010;31:171–82.PubMed
6.
Sun B, He F, Gao Y, Zhou J, Sun L, Liu R, et al. Prognostic impact of visit-to-visit glycemic variability on the risks of major adverse cardiovascular outcomes and hypoglycemia in patients with different glycemic control and type 2 diabetes. Endocrine. 2019;64:536–43.PubMed
7.
Zhou JJ, Schwenke DC, Bahn G, Reaven P. Glycemic variation and cardiovascular risk in the Veterans Affairs Diabetes trial. Diabetes Care. 2018;41:2187–94.PubMedPubMedCentral
8.
Ferreira L, Moniz AC, Carneiro AS, Miranda AS, Fangueiro C, Fernandes D, et al. The impact of glycemic variability on length of stay and mortality in diabetic patients admitted with community-acquired pneumonia or chronic obstructive pulmonary disease. Diabetes Metab Syndr. 2019;13:149–53.PubMed
9.
Yokota S, Tanaka H, Mochizuki Y, Soga F, Yamashita K, Tanaka Y, et al. Association of glycemic variability with left ventricular diastolic function in type 2 diabetes mellitus. Cardiovasc Diabetol. 2019;18:166.PubMedPubMedCentral
10.
Lu J, Ma X, Zhang L, Mo Y, Lu W, Zhu W, et al. Glycemic variability modifies the relationship between time in range and hemoglobin A1c estimated from continuous glucose monitoring: a preliminary study. Diabetes Res Clin Pract. 2020;161:108032.PubMed
11.
Besch G, Pili-Floury S, Morel C, Gilard M, Flicoteaux G, du Mont SL, et al. Impact of post-procedural glycemic variability on cardiovascular morbidity and mortality after transcatheter aortic valve implantation: a post hoc cohort analysis. Cardiovasc Diabetol. 2019;18:27.PubMedPubMedCentral
12.
Zhang Y, Dai J, Han X, Zhao Y, Zhang H, Liu X, et al. Glycemic variability indices determined by self-monitoring of blood glucose are associated with β-cell function in Chinese patients with type 2 diabetes. Diabetes Res Clin Pract. 2020;164:108152.PubMed
13.
Takahashi H, Iwahashi N, Kirigaya J, Kataoka S, Minamimoto Y, Gohbara M, et al. Glycemic variability determined with a continuous glucose monitoring system can predict prognosis after acute coronary syndrome. Cardiovasc Diabetol. 2018;17:116.PubMedPubMedCentral
14.
Cardoso CRL, Leite NC, Moram CBM, Salles GF. Long-term visit-to-visit glycemic variability as predictor of micro- and macrovascular complications in patients with type 2 diabetes: the Rio de Janeiro Type 2 Diabetes Cohort Study. Cardiovasc Diabetol. 2018;17:33.PubMedPubMedCentral
15.
Hirakawa Y, Arima H, Zoungas S, Ninomiya T, Cooper M, Hamet P, et al. Impact of visit-to-visit glycemic variability on the risks of macrovascular and microvascular events and all-cause mortality in type 2 diabetes: the ADVANCE trial. Diabetes Care. 2014;37:2359–65.PubMed
16.
Tang X, Li S, Wang Y, Wang M, Yin Q, Mu P, et al. Glycemic variability evaluated by continuous glucose monitoring system is associated with the 10-y cardiovascular risk of diabetic patients with well-controlled HbA1c. Clin Chim Acta. 2016;461:146–50.PubMed
17.
Muggeo M, Zoppini G, Bonora E, Brun E, Bonadonna RC, Moghetti P, et al. Fasting plasma glucose variability predicts 10-year survival of type 2 diabetic patients: the Verona Diabetes Study. Diabetes Care. 2000;23:45–50.PubMed
18.
Zoppini G, Verlato G, Targher G, Bonora E, Trombetta M, Muggeo M. Variability of body weight, pulse pressure and glycaemia strongly predict total mortality in elderly type 2 diabetic patients. The Verona Diabetes Study. Diabetes Metab Res Rev. 2008;24:624–8.PubMed
19.
Rizvi SI, Maurya PK. Markers of oxidative stress in erythrocytes during aging in humans. Ann N Y Acad Sci. 2007;1100:373–82.PubMed
20.
Xu D, Fang H, Xu W, Yan Y, Liu Y, Yao B. Fasting plasma glucose variability and all-cause mortality among type 2 diabetes patients: a dynamic cohort study in Shanghai, China. Sci Rep. 2016;6:39633.PubMedPubMedCentral
21.
Muggeo M, Verlato G, Bonora E, Zoppini G, Corbellini M, de Marco R. Long-term instability of fasting plasma glucose, a novel predictor of cardiovascular mortality in elderly patients with non-insulin-dependent diabetes mellitus: the Verona Diabetes Study. Circulation. 1997;96:1750–4.PubMed
22.
Song SO, Jung CH, Song YD, Park CY, Kwon HS, Cha BS, et al. Background and data configuration process of a nationwide population-based study using the korean national health insurance system. Diabetes Metab J. 2014;38:395–403.PubMedPubMedCentral
23.
Lee YH, Han K, Ko SH, Ko KS, Lee KU. Data analytic process of a nationwide population-based study using National Health Information Database established by National Health Insurance Service. Diabetes Metab J. 2016;40:79–82.PubMedPubMedCentral
24.
Rothwell PM, Howard SC, Dolan E, O’Brien E, Dobson JE, Dahlof B, et al. Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. Lancet. 2010;375:895–905.PubMed
25.
Oh JY, Yang YJ, Kim BS, Kang JH. Validity and reliability of Korean version of International Physical Activity Questionnaire (IPAQ) short form. J Korean Acad Fam Med. 2007;28:532–41.
26.
Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006;145:247–54.PubMed
27.
Group KDIGOCW. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease: Chapter 1: definition and classification of CKD. Kidney Int Suppl. 2013;2013(3):19–62.
28.
Zhang XG, Zhang YQ, Zhao DK, Wu JX, Zhao J, Jiao XM, et al. Relationship between blood glucose fluctuation and macrovascular endothelial dysfunction in type 2 diabetic patients with coronary heart disease. Eur Rev Med Pharm Sci. 2014;18:3593–600.
29.
Ceriello A, Esposito K, Piconi L, Ihnat MA, Thorpe JE, Testa R, et al. Oscillating glucose is more deleterious to endothelial function and oxidative stress than mean glucose in normal and type 2 diabetic patients. Diabetes. 2008;57:1349–54.PubMed
30.
Salisbury D, Bronas U. Reactive oxygen and nitrogen species: impact on endothelial dysfunction. Nurs Res. 2015;64:53–66.PubMed
31.
El-Osta A, Brasacchio D, Yao D, Pocai A, Jones PL, Roeder RG, et al. Transient high glucose causes persistent epigenetic changes and altered gene expression during subsequent normoglycemia. J Exp Med. 2008;205:2409–17.PubMedPubMedCentral
32.
Okada K, Hibi K, Gohbara M, Kataoka S, Takano K, Akiyama E, et al. Association between blood glucose variability and coronary plaque instability in patients with acute coronary syndromes. Cardiovasc Diabetol. 2015;14:111.PubMedPubMedCentral
33.
Yamazaki M, Hasegawa G, Majima S, Mitsuhashi K, Fukuda T, Iwase H, et al. Effect of repaglinide versus glimepiride on daily blood glucose variability and changes in blood inflammatory and oxidative stress markers. Diabetol Metab Syndr. 2014;6:54.PubMedPubMedCentral
34.
Suh S, Kim H, Dang-Vu TT, Joo E, Shin C. Cortical thinning and altered cortico-cortical structural covariance of the default mode network in patients with persistent insomnia symptoms. Sleep. 2016;39:161–71.PubMedPubMedCentral
35.
Heinemann L, Fleming GA, Petrie JR, Holl RW, Bergenstal RM, Peters AL. Insulin pump risks and benefits: a clinical appraisal of pump safety standards, adverse event reporting, and research needs. Diabetes Care. 2015;38:716–22.PubMed
36.
Vora J, Cariou B, Evans M, Gross JL, Harris S, Landstedt-Hallin L, et al. Clinical use of insulin degludec. Diabetes Res Clin Pract. 2015;109:19–31.PubMed
37.
Inzucchi SE, Umpierrez G, DiGenio A, Zhou R, Kovatchev B. How well do glucose variability measures predict patient glycaemic outcomes during treatment intensification in type 2 diabetes? Diabetes Res Clin Pract. 2015;108:179–86.PubMed
38.
Hansen TW, Thijs L, Li Y, Boggia J, Kikuya M, Björklund-Bodegård K, et al. Prognostic value of reading-to-reading blood pressure variability over 24 hours in 8938 subjects from 11 populations. Hypertension. 2010;55:1049–57.PubMed
39.
Mena L, Pintos S, Queipo NV, Aizpúrua JA, Maestre G, Sulbarán T. A reliable index for the prognostic significance of blood pressure variability. J Hypertens. 2005;23:505–11.PubMed
40.
Lee HJ, Choi EK, Han KD, Lee E, Moon I, Lee SR, et al. Bodyweight fluctuation is associated with increased risk of incident atrial fibrillation. Heart Rhythm. 2020;17:365–71.PubMed
41.
Yano Y. Visit-to-visit blood pressure variability-what is the current challenge? Am J Hypertens. 2017;30:112–4.PubMed
42.
Bangalore S, Breazna A, DeMicco DA, Wun CC, Messerli FH. Visit-to-visit low-density lipoprotein cholesterol variability and risk of cardiovascular outcomes: insights from the TNT trial. J Am Coll Cardiol. 2015;65:1539–48.PubMed
43.
Dolan E, O’Brien E. Blood pressure variability: clarity for clinical practice. Hypertension. 2010;56:179–81.PubMed
Metadata
Title
Glucose variability and the risks of stroke, myocardial infarction, and all-cause mortality in individuals with diabetes: retrospective cohort study
Authors
Da Young Lee
Kyungdo Han
Sanghyun Park
Ji Hee Yu
Ji A. Seo
Nam Hoon Kim
Hye Jin Yoo
Sin Gon Kim
Kyung Mook Choi
Sei Hyun Baik
Yong Gyu Park
Nan Hee Kim
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Cardiovascular Diabetology / Issue 1/2020
Electronic ISSN: 1475-2840
DOI
https://doi.org/10.1186/s12933-020-01134-0

Other articles of this Issue 1/2020

Cardiovascular Diabetology 1/2020 Go to the issue

Original investigation

Load-independent effects of empagliflozin contribute to improved cardiac function in experimental heart failure with reduced ejection fraction

Original investigation

The additive effects of type 2 diabetes mellitus on left ventricular deformation and myocardial perfusion in essential hypertension: a 3.0 T cardiac magnetic resonance study

Original investigation

Association between adipocyte fatty acid-binding protein with left ventricular remodelling and diastolic function in type 2 diabetes: a prospective echocardiography study

Original investigation

Incidence of idiopathic cardiomyopathy in patients with type 2 diabetes in Taiwan: age, sex, and urbanization status-stratified analysis

Original investigation

Long-term LVEF trajectories in patients with type 2 diabetes and heart failure: diabetic cardiomyopathy may underlie functional decline

Original investigation

Change in glucose intolerance status and risk of incident cardiovascular disease: Tehran Lipid and Glucose Study
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

Read more

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine
Image Credits