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

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › 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.

Originalsprog	Engelsk
Titel	Digital Personalized Health and Medicine
Antal sider	2
Forlag	IOS Press
Publikationsdato	2020
Sider	1413-1414
ISBN (Trykt)	978-1-64368-082-8
ISBN (Elektronisk)	978-1-64368-083-5
DOI	https://doi.org/10.3233/SHTI200468
Status	Udgivet - 2020
Begivenhed	Medical Informatics Europe Conference (MIE) - Geneve, Schweiz Varighed: 28 apr. 2019 → 1 maj 2019 Konferencens nummer: 30

Konference

Konference	Medical Informatics Europe Conference (MIE)
Nummer	30
Land/Område	Schweiz
By	Geneve
Periode	28/04/2019 → 01/05/2019

Navn	Studies in Health Technology and Informatics
Vol/bind	270
ISSN	0926-9630

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10.3233/SHTI200468

Open Access articleForlagets udgivne version, 146 KBLicens: CC BY-NC 4.0

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Citationsformater

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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",

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language = "English",

isbn = "978-1-64368-082-8",

series = "Studies in Health Technology and Informatics",

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pages = "1413--1414",

booktitle = "Digital Personalized Health and Medicine",

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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. i Digital Personalized Health and Medicine. IOS Press, Studies in Health Technology and Informatics, bind 270, s. 1413-1414, Medical Informatics Europe Conference (MIE), Geneve, Schweiz, 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. s. 1413-1414 (Studies in Health Technology and Informatics, Bind 270).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

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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N2 - 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.

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.

KW - Type 1 diabetes

KW - continuous glucose monitoring

KW - prediction

UR - http://www.scopus.com/inward/record.url?scp=85086917916&partnerID=8YFLogxK

U2 - 10.3233/SHTI200468

DO - 10.3233/SHTI200468

M3 - Article in proceeding

SN - 978-1-64368-082-8

T3 - Studies in Health Technology and Informatics

SP - 1413

EP - 1414

BT - Digital Personalized Health and Medicine

PB - IOS Press

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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