A mathematical model to estimate mean blood glucose by oral glucose tolerance test

Objective To establish a method for estimating mean blood glucose using oral glucose tolerance test (OGTT). Methods A retrospective study was conducted on the patients with type 2 diabetes mellitus (T2DM) in our department between January 2014 and December 2017. All the patients underwent continuou...

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Autores principales: LIU Xiaoxiao, LI Qiang, HE Hongbo, LI Yingsha, YANG Liqin, ZHU Zhiming, YAN Zhencheng
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Publicado: Editorial Office of Journal of Third Military Medical University 2021
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spelling oai:doaj.org-article:a630557800464ce994c1cdf1dde0df642021-11-12T05:13:43ZA mathematical model to estimate mean blood glucose by oral glucose tolerance test10.16016/j.1000-5404.20210050491000-5404https://doaj.org/article/a630557800464ce994c1cdf1dde0df642021-11-01T00:00:00Zhttp://aammt.tmmu.edu.cn/Upload/rhtml/2021005049.htmhttps://doaj.org/toc/1000-5404 Objective To establish a method for estimating mean blood glucose using oral glucose tolerance test (OGTT). Methods A retrospective study was conducted on the patients with type 2 diabetes mellitus (T2DM) in our department between January 2014 and December 2017. All the patients underwent continuous glucose monitoring (CGM) and OGTT. The basic demographic characteristics and results of laboratory tests of the patients were collected. Then relevant mathematical models were established and modified. In the end, external validation was carried out according to the goodness of fit formula. Results Thirty-six diabetic patients who met the enrollment criteria were recruited. The 24-hour mean blood glucose (24 h MBG) was estimated to be 9.66±3.34 mmol/L by OGTT (MBGOGTT), to be 9.40±2.67 mmol/L through CGM calculation. MBGOGTT showed significantly positive correlation with both glycosylated hemoglobin (HbA1c, r=0.582, P < 0.001) and 24 h MBG (r=0.674, P < 0.001). We used linear regression model and established following equation to estimate 24 h MBG by OGTT: 24 h MBGmmol/L=4.166+0.545×MBGOGTT, (r=0.674, P < 0.001). Furthermore, a modified model incorporating HbA1c effect was also obtained: 24 h MBGmmol/L=1.797+0.359×MBGOGTT+0.565×HbA1c (R=0.768, P < 0.001). We selected 18 patients admitted to our department for external validation. In this verification result, we obtained a RNL value of 0.81, which implied a high fit degree. Conclusion A model to evaluate mean blood glucose by OGTT is successfully established, and can be used as a simple method to evaluate blood glucose status in diabetic patients.LIU XiaoxiaoLI Qiang HE HongboLI Yingsha YANG LiqinZHU ZhimingYAN ZhenchengEditorial Office of Journal of Third Military Medical Universityarticlediabetes mellitusoral glucose tolerance testblood glucose monitoringmathematical modelMedicine (General)R5-920ZHDi-san junyi daxue xuebao, Vol 43, Iss 21, Pp 2389-2394 (2021)
institution DOAJ
collection DOAJ
language ZH
topic diabetes mellitus
oral glucose tolerance test
blood glucose monitoring
mathematical model
Medicine (General)
R5-920
spellingShingle diabetes mellitus
oral glucose tolerance test
blood glucose monitoring
mathematical model
Medicine (General)
R5-920
LIU Xiaoxiao
LI Qiang
HE Hongbo
LI Yingsha
YANG Liqin
ZHU Zhiming
YAN Zhencheng
A mathematical model to estimate mean blood glucose by oral glucose tolerance test
description Objective To establish a method for estimating mean blood glucose using oral glucose tolerance test (OGTT). Methods A retrospective study was conducted on the patients with type 2 diabetes mellitus (T2DM) in our department between January 2014 and December 2017. All the patients underwent continuous glucose monitoring (CGM) and OGTT. The basic demographic characteristics and results of laboratory tests of the patients were collected. Then relevant mathematical models were established and modified. In the end, external validation was carried out according to the goodness of fit formula. Results Thirty-six diabetic patients who met the enrollment criteria were recruited. The 24-hour mean blood glucose (24 h MBG) was estimated to be 9.66±3.34 mmol/L by OGTT (MBGOGTT), to be 9.40±2.67 mmol/L through CGM calculation. MBGOGTT showed significantly positive correlation with both glycosylated hemoglobin (HbA1c, r=0.582, P < 0.001) and 24 h MBG (r=0.674, P < 0.001). We used linear regression model and established following equation to estimate 24 h MBG by OGTT: 24 h MBGmmol/L=4.166+0.545×MBGOGTT, (r=0.674, P < 0.001). Furthermore, a modified model incorporating HbA1c effect was also obtained: 24 h MBGmmol/L=1.797+0.359×MBGOGTT+0.565×HbA1c (R=0.768, P < 0.001). We selected 18 patients admitted to our department for external validation. In this verification result, we obtained a RNL value of 0.81, which implied a high fit degree. Conclusion A model to evaluate mean blood glucose by OGTT is successfully established, and can be used as a simple method to evaluate blood glucose status in diabetic patients.
format article
author LIU Xiaoxiao
LI Qiang
HE Hongbo
LI Yingsha
YANG Liqin
ZHU Zhiming
YAN Zhencheng
author_facet LIU Xiaoxiao
LI Qiang
HE Hongbo
LI Yingsha
YANG Liqin
ZHU Zhiming
YAN Zhencheng
author_sort LIU Xiaoxiao
title A mathematical model to estimate mean blood glucose by oral glucose tolerance test
title_short A mathematical model to estimate mean blood glucose by oral glucose tolerance test
title_full A mathematical model to estimate mean blood glucose by oral glucose tolerance test
title_fullStr A mathematical model to estimate mean blood glucose by oral glucose tolerance test
title_full_unstemmed A mathematical model to estimate mean blood glucose by oral glucose tolerance test
title_sort mathematical model to estimate mean blood glucose by oral glucose tolerance test
publisher Editorial Office of Journal of Third Military Medical University
publishDate 2021
url https://doaj.org/article/a630557800464ce994c1cdf1dde0df64
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