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Impact of Glucose Fluctuation on Acute Cerebral Infarction in Type 2 Diabetes

Published online by Cambridge University Press:  20 October 2014

Jinxin Huang
Affiliation:
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing, China
Xingguang Zhang
Affiliation:
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing, China
Juan Li
Affiliation:
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing, China
Liya Tang
Affiliation:
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing, China
Xiumin Jiao
Affiliation:
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing, China
Xiaofeng Lv*
Affiliation:
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing, China
*
Beijing Military General Hospital, No. 5 Nan Men Cang, Dongcheng district, Beijing 100700, China. Email: xiaofenglv7966@163.com.
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Abstract

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Objective:

This study aimed to describe the frequency and temporal profile of acute cerebral infarction (ACI) using a continuous glucose monitoring system (CGMS) in patients with and without type 2 diabetes mellitus (T2DM) and explore the impact of blood glucose fluctuations on the short-term prognosis of ACI.

Methods:

The subjects were divided into four groups: T2DM with acute cerebral infarction (DMCI, Group A, n=56); T2DM without acute cerebral infarction (DM-NCI, Group B, n=36); Acute cerebral infarction patients without T2DM (NDM-CI, Group C, n=54); Healthy control group (NG, Group D, n=36). The National Institutes of Health Stoke Scale (NIHSS) and modified Rankin scale (mRs) were collected in Group A and C. All subjects were monitored for 72 hours using the CGMS. Indices such as fasting blood glucose (FBG) and mean amplitude of glycemic excursions (MAGE) were calculated. Glycemic excursions were compared between Group A, B, C and Group D, respectively. Multiple linear regression analysis and logistic analysis was applied.

Results:

MAGE is related to NIHSS, homocysteine (HCY), HOMA-IR, FBG, CRP and IMT, while NIHSS is related to CRP, HCY, HOMA-IR, IMT. The factors impacting the short-term prognosis of ACI were NIHSS, HBA1C and MAGE.

Conclusion:

Larger glucose fluctuations are associated with more stroke risk factors and are associated with a poorer short-term prognosis. More attention should be paid to glucose fluctuations in patients with ACI and a history of T2DM.

Type
Original Article
Copyright
Copyright © The Canadian Journal of Neurological 2014

References

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