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A Novel CGM Metric-Gradient and Combining Mean Sensor Glucose Enable to Improve the Prediction of Nocturnal Hypoglycemic Events in Patients with Diabetes
Joint Authors
Li, Jingzhen
Ma, Xiaojing
Tobore, Igbe
Liu, Yuhang
Kandwal, Abhishek
Wang, Lei
Lu, Jingyi
Lu, Wei
Bao, Yuqian
Zhou, Jian
Nie, Zedong
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-03
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Nocturnal hypoglycemia is a serious complication of insulin-treated diabetes, and it is often asymptomatic.
A novel CGM metric-gradient was proposed in this paper, and a method of combining mean sensor glucose (MSG) and gradient was presented for the prediction of nocturnal hypoglycemia.
For this purpose, the data from continuous glucose monitoring (CGM) encompassing 1,921 patients with diabetes were analyzed, and a total of 302 nocturnal hypoglycemic events were recorded.
The MSG and gradient values were calculated, respectively, and then combined as a new metric (i.e., MSG+gradient).
In addition, the prediction was conducted by four algorithms, namely, logistic regression, support vector machine, random forest, and long short-term memory.
The results revealed that the gradient of CGM showed a downward trend before hypoglycemic events happened.
Additionally, the results indicated that the specificity and sensitivity based on the proposed method were better than the conventional metrics of low blood glucose index (LBGI), coefficient of variation (CV), mean absolute glucose (MAG), lability index (LI), etc., and the complex metrics of MSG+LBGI, MSG+CV, MSG+MAG, and MSG+LI, etc.
Specifically, the specificity and sensitivity were greater than 96.07% and 96.03% at the prediction horizon of 15 minutes and greater than 87.79% and 90.07% at the prediction horizon of 30 minutes when the proposed method was adopted to predict nocturnal hypoglycemic events in the aforementioned four algorithms.
Therefore, the proposed method of combining MSG and gradient may enable to improve the prediction of nocturnal hypoglycemic events.
Future studies are warranted to confirm the validity of this metric.
American Psychological Association (APA)
Li, Jingzhen& Ma, Xiaojing& Tobore, Igbe& Liu, Yuhang& Kandwal, Abhishek& Wang, Lei…[et al.]. 2020. A Novel CGM Metric-Gradient and Combining Mean Sensor Glucose Enable to Improve the Prediction of Nocturnal Hypoglycemic Events in Patients with Diabetes. Journal of Diabetes Research،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1183480
Modern Language Association (MLA)
Li, Jingzhen…[et al.]. A Novel CGM Metric-Gradient and Combining Mean Sensor Glucose Enable to Improve the Prediction of Nocturnal Hypoglycemic Events in Patients with Diabetes. Journal of Diabetes Research No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1183480
American Medical Association (AMA)
Li, Jingzhen& Ma, Xiaojing& Tobore, Igbe& Liu, Yuhang& Kandwal, Abhishek& Wang, Lei…[et al.]. A Novel CGM Metric-Gradient and Combining Mean Sensor Glucose Enable to Improve the Prediction of Nocturnal Hypoglycemic Events in Patients with Diabetes. Journal of Diabetes Research. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1183480
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1183480