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CN 34-1304/RISSN 1674-3679

Volume 28 Issue 7
Jul.  2024
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Article Contents
GU Shujun, QIN Yu, YU Hao, GUAN Haoyu, CUI Lan, SHEN Chong, LU Yan, CHENG Tingting, ZHANG Ning, ZHOU Jinyi, SU Jian. A prospective cohort study on the long-term fasting plasma glucose variability and risk of stroke among patients with type 2 diabetes mellitus[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(7): 777-783. doi: 10.16462/j.cnki.zhjbkz.2024.07.006
Citation: GU Shujun, QIN Yu, YU Hao, GUAN Haoyu, CUI Lan, SHEN Chong, LU Yan, CHENG Tingting, ZHANG Ning, ZHOU Jinyi, SU Jian. A prospective cohort study on the long-term fasting plasma glucose variability and risk of stroke among patients with type 2 diabetes mellitus[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(7): 777-783. doi: 10.16462/j.cnki.zhjbkz.2024.07.006

A prospective cohort study on the long-term fasting plasma glucose variability and risk of stroke among patients with type 2 diabetes mellitus

doi: 10.16462/j.cnki.zhjbkz.2024.07.006
Funds:

Jiangsu Provincial Health Commission 2020 Medical Research Project Approval M2020085

Gusu Health Talent Training Project of Suzhou GSWS2020107

Jiangsu Province Leading Talents and Innovation Team Program K201105

Jiangsu Provincial Fifth "333 Project" BRA2020090

Suzhou Science and Technology Plan Projects SS202010

Changshu Science and Technology Plan Projects CS201812

More Information
  • Corresponding author: SU Jian,E-mail: sujiangx@163.com
  • Received Date: 2023-07-28
  • Rev Recd Date: 2024-01-09
  • Available Online: 2024-08-19
  • Publish Date: 2024-07-10
  •   Objective   To investigate the association between long-term fasting plasma glucose (FPG) variability and stroke in patients with type 2 diabetes mellitus (T2DM).  Methods  The participants were from a community-based diabetes cohort established in Changshu from 2013 to 2014 (n=6 247). Long-term glucose variability was assessed using the standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) across FPG measurements obtained at the more than three visits. The risk of stroke in patients with T2DM was estimated using Cox proportional risk regression models for SD, CV, ARV, VIM and stratified analysis were conducted according to age, gender and history of diabetes medication.  Results  After an average 7.26 years of follow-up, there were 1 080 incident cases of stroke, giving a crude incidence rate of 23.81/1 000 person-years. The long-term fasting plasma glucose variability was grouped by tertiles (T1-T3). After adjustment, Cox regression analysis showed that compared with the T1 group, FPG-SD, FPG-CV, FPG-ARV and FPG-VIM in T2 and T3 groups were significantly increased the risks of stroke (Ptrend < 0.01). Per 1 standard deviation(SD) higher of FPG-SD, FPG-CV, FPG-ARV and FPG-VIM, the risk of stroke was significantly increased, the HR (95% CI) were 1.09(1.02-1.16), 1.09(1.03-1.16), 1.08(1.02-1.16) and 1.10(1.03-1.16) respectively. Per 1 SD higher of FPG-SD, FPG-CV, FPG-ARV and FPG-VIM, the risk of ischemic stroke was significantly increased, the HR (95% CI) were 1.11(1.03-1.19), 1.11(1.04-1.18), 1.08(1.00-1.15), 1.04(1.04-1.17), respectively. Per 1 SD higher of FPG-ARV, the risk of hemorrhagic stroke was significantly increased, the HR(95% CI) was 1.25(1.05-1.48). Stratified analysis showed that in the patients of ≥65 years of age (except FPG-CV), women and oral hypoglycemic agents, per 1 SD higher of FPG-SD, FPG-CV, FPG-ARV and FPG-VIM, the risk of ischemic stroke increased significantly (P < 0.05).  Conclusions  Long-term FPG glycemic variability is positively associated with the risk of stroke in type 2 diabetes patients.
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  • [1]
    Rawshani A, Rawshani A, Franzén S, et al. Mortality and cardiovascular disease in type 1 and type 2 diabetes[J]. N Engl J Med, 2017, 376(3): 1407-1418. DOI: 10.1056/NEJMoa1608664.
    [2]
    Tuomilehto J, Rastenyte D. Diabetes and glucose intolerance as risk factors for stroke[J]. J Cardiovasc Risk, 1999, 6(4): 241-249. DOI: 10.1177/204748739900600409.
    [3]
    Kilpatrick ES, Rigby AS, Atkin SL. A1C variability and the risk of microvascular complications in type 1 diabetes: data from the Diabetes Control and Complications Trial[J]. Diabetes Care, 2008, 31(11): 2198-2202. DOI: 10.2337/dc08-0864.
    [4]
    Goldstein DE, Little RR, Lorenz RA, et al. American diabetes association: tests of glycemia in diabetes[J]. Diabetes Care, 2003, 26(suppl 1): S106-S108. DOI: 10.2337/diacare.26.2007.S106.
    [5]
    苏健, 覃玉, 沈冲, 等. 吸烟和戒烟行为与男性2型糖尿病血糖控制关系的研究[J]. 中华流行病学杂志, 2017, 38(11): 1454-1459. DOI: 10.3760/cma.j.issn.0254-6450.2017.11.003.

    Su J, Qin Y, Shen C, et al. Association between smoking/smoking cessation and glycemic control in male patients with type2 diabetes[J]. Chin J Epidemiol, 2017, 38(11): 1454-1459. DOI: 10.3760/cma.j.issn.0254-6450.2017.11.003.
    [6]
    Hirakawa Y, Arima H, Zoungas S, 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[J]. Diabetes Care, 2014, 37(8): 2359-2365. DOI: 10.2337/dc14-0199.
    [7]
    Scott ES, Januszewski AS, O'Connell R, et al. Long-term glycemic variability and vascular complications in type 2 diabetes: post hoc analysis of the FIELD study[J]. J Clin Endocrinol Metab, 2020, 105(10): dgaa361. DOI: 10.1210/clinem/dgaa361.
    [8]
    Barzegar N, Ramezankhani A, Tohidi M, et al. Long-term glucose variability and incident cardiovascular diseases and all-cause mortality events in subjects with and without diabetes: tehran lipid and glucose study[J]. Diabetes Res Clin Pract, 2021, 178: 108942. DOI: 10.1016/j.diabres.2021.108942.
    [9]
    Chiang JI, Li TC, Li CI, et al. Visit-to-visit variation of fasting plasma glucose is a predictor of hip fracture in older persons with type 2 diabetes: the Taiwan diabetes study[J]. Osteoporos Int, 2016, 27(12): 3587-3597. DOI: 10.1007/s00198-016-3689-1.
    [10]
    Brownlee M. The pathobiology of diabetic complications: a unifying mechanism[J]. Diabetes, 2005, 54(6): 1615-1625. DOI: 10.2337/diabetes.54.6.1615.
    [11]
    La Sala L, Mrakic-Sposta S, Micheloni S, et al. Glucose-sensing microRNA-21 disrupts ROS homeostasis and impairs antioxidant responses in cellular glucose variability[J]. Cardiovasc Diabetol, 2018, 17(1): 105. DOI: 10.1186/s12933-018-0748-2.
    [12]
    Hu ZJ, Fang WM, Liu Y, et al. Acute glucose fluctuation promotes RAGE expression via reactive oxygen species-mediated NF-κB activation in rat podocytes[J]. Mol Med Rep, 2021, 23(5): 330. DOI: 10.3892/mmr.2021.11969.
    [13]
    Biscetti F, Pitocco D, Straface G, et al. Glycaemic variability affects ischaemia-induced angiogenesis in diabetic mice[J]. Clin Sci, 2011, 121(12): 555-564. DOI: 10.1042/CS20110043.
    [14]
    Del Guerra S, Grupillo M, Masini M, et al. Gliclazide protects human islet beta-cells from apoptosis induced by intermittent high glucose[J]. Diabetes Metab Res Rev, 2007, 23(3): 234-238. DOI: 10.1002/dmrr.680.
    [15]
    Shao C, Gu J, Meng X, et al. Systematic investigation into the role of intermittent high glucose in pancreatic beta- cells[J]. Int J Clin Exp Med, 2015, 8(4): 5462-5469.
    [16]
    Gorni D, Finco A. Oxidative stress in elderly population: a prevention screening study[J]. Aging Med (Milton), 2020, 3(3): 205-213. DOI: 10.1002/agm2.12121.
    [17]
    Meyer MR, Clegg DJ, Prossnitz ER, et al. Obesity, insulin resistance and diabetes: sex differences and role of oestrogen receptors[J]. Acta Physiol (Oxf), 2011, 203(1): 259-269. DOI: 10.1111/j.1748-1716.2010.02237.x.
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