Towards prediction of type 1 diabetes patients who fail to achieve glycemic target

Morten Hasselstrøm Jensen; Simon Lebech Cichosz; Ole Hejlesen; Irl B.  Hirsch; Peter Vestergaard

doi:10.3233/SHTI200468

Towards prediction of type 1 diabetes patients who fail to achieve glycemic target

Morten Hasselstrøm Jensen, Simon Lebech Cichosz, Ole Hejlesen, Irl B. Hirsch, Peter Vestergaard

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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Abstract

In this study, we investigated which predictors from people with type 1 diabetes at initiation of intensive treatment that increase the risk of not achieving glycemic target. Data from a clinical trial with type 1 diabetes people (n=460) were used in a logistic regression model to analyze the effect of the predictors on achievement of glycemic target. Results indicate that age, smoking, glycated hemoglobin, 1,5-anhydroglucitol and fluctuation from continuous glucose monitoring are predictors of achievement of glycemic target, which can be used in an algorithm to predict people who fail to achieve glycemic target.

Original language	English
Title of host publication	Digital Personalized Health and Medicine
Number of pages	2
Publisher	IOS Press
Publication date	2020
Pages	1413-1414
ISBN (Print)	978-1-64368-082-8
ISBN (Electronic)	978-1-64368-083-5
DOIs	https://doi.org/10.3233/SHTI200468
Publication status	Published - 2020
Event	Medical Informatics Europe Conference (MIE) - Geneve, Switzerland Duration: 28 Apr 2019 → 1 May 2019 Conference number: 30

Conference

Conference	Medical Informatics Europe Conference (MIE)
Number	30
Country/Territory	Switzerland
City	Geneve
Period	28/04/2019 → 01/05/2019

Series	Studies in Health Technology and Informatics
Volume	270
ISSN	0926-9630

Keywords

Type 1 diabetes
continuous glucose monitoring
prediction

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10.3233/SHTI200468

Open Access articleFinal published version, 146 KBLicence: CC BY-NC 4.0

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title = "Towards prediction of type 1 diabetes patients who fail to achieve glycemic target",

abstract = "In this study, we investigated which predictors from people with type 1 diabetes at initiation of intensive treatment that increase the risk of not achieving glycemic target. Data from a clinical trial with type 1 diabetes people (n=460) were used in a logistic regression model to analyze the effect of the predictors on achievement of glycemic target. Results indicate that age, smoking, glycated hemoglobin, 1,5-anhydroglucitol and fluctuation from continuous glucose monitoring are predictors of achievement of glycemic target, which can be used in an algorithm to predict people who fail to achieve glycemic target.",

keywords = "Type 1 diabetes, continuous glucose monitoring, prediction",

author = "Jensen, {Morten Hasselstr{\o}m} and Cichosz, {Simon Lebech} and Ole Hejlesen and Hirsch, {Irl B.} and Peter Vestergaard",

year = "2020",

doi = "10.3233/SHTI200468",

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publisher = "IOS Press",

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note = "Medical Informatics Europe Conference (MIE), MIE ; Conference date: 28-04-2019 Through 01-05-2019",

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Jensen, MH , Cichosz, SL , Hejlesen, O, Hirsch, IB & Vestergaard, P 2020, Towards prediction of type 1 diabetes patients who fail to achieve glycemic target. in Digital Personalized Health and Medicine. IOS Press, Studies in Health Technology and Informatics, vol. 270, pp. 1413-1414, Medical Informatics Europe Conference (MIE), Geneve, Switzerland, 28/04/2019. https://doi.org/10.3233/SHTI200468

Towards prediction of type 1 diabetes patients who fail to achieve glycemic target. / Jensen, Morten Hasselstrøm ; Cichosz, Simon Lebech ; Hejlesen, Ole et al.
Digital Personalized Health and Medicine. IOS Press, 2020. p. 1413-1414 (Studies in Health Technology and Informatics, Vol. 270).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

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T1 - Towards prediction of type 1 diabetes patients who fail to achieve glycemic target

AU - Jensen, Morten Hasselstrøm

AU - Cichosz, Simon Lebech

AU - Hejlesen, Ole

AU - Hirsch, Irl B.

AU - Vestergaard, Peter

N1 - Conference code: 30

PY - 2020

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AB - In this study, we investigated which predictors from people with type 1 diabetes at initiation of intensive treatment that increase the risk of not achieving glycemic target. Data from a clinical trial with type 1 diabetes people (n=460) were used in a logistic regression model to analyze the effect of the predictors on achievement of glycemic target. Results indicate that age, smoking, glycated hemoglobin, 1,5-anhydroglucitol and fluctuation from continuous glucose monitoring are predictors of achievement of glycemic target, which can be used in an algorithm to predict people who fail to achieve glycemic target.

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T3 - Studies in Health Technology and Informatics

SP - 1413

EP - 1414

BT - Digital Personalized Health and Medicine

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T2 - Medical Informatics Europe Conference (MIE)

Y2 - 28 April 2019 through 1 May 2019

ER -

Towards prediction of type 1 diabetes patients who fail to achieve glycemic target

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