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

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Abstrakt

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.

OriginalsprogEngelsk
TitelDigital Personalized Health and Medicine
Antal sider2
ForlagIOS Press
Publikationsdato2020
Sider1413-1414
ISBN (Trykt)978-1-64368-082-8
ISBN (Elektronisk)978-1-64368-083-5
DOI
StatusUdgivet - 2020
BegivenhedMedical Informatics Europe Conference (MIE) - Geneve, Schweiz
Varighed: 28 apr. 20191 maj 2019
Konferencens nummer: 30

Konference

KonferenceMedical Informatics Europe Conference (MIE)
Nummer30
LandSchweiz
ByGeneve
Periode28/04/201901/05/2019
NavnStudies in Health Technology and Informatics
Vol/bind270
ISSN0926-9630

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  • Citationsformater

    Jensen, M. H., Cichosz, S. L., Hejlesen, O., Hirsch, I. B., & Vestergaard, P. (2020). Towards prediction of type 1 diabetes patients who fail to achieve glycemic target. I Digital Personalized Health and Medicine (s. 1413-1414). IOS Press. Studies in Health Technology and Informatics, Bind. 270 https://doi.org/10.3233/SHTI200468