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

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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 languageEnglish
Title of host publicationDigital Personalized Health and Medicine
Number of pages2
PublisherIOS Press
Publication date2020
Pages1413-1414
ISBN (Print)978-1-64368-082-8
ISBN (Electronic)978-1-64368-083-5
DOIs
Publication statusPublished - 2020
EventMedical Informatics Europe Conference (MIE) - Geneve, Switzerland
Duration: 28 Apr 20191 May 2019
Conference number: 30

Conference

ConferenceMedical Informatics Europe Conference (MIE)
Number30
Country/TerritorySwitzerland
CityGeneve
Period28/04/201901/05/2019
SeriesStudies in Health Technology and Informatics
Volume270
ISSN0926-9630

Keywords

  • Type 1 diabetes
  • continuous glucose monitoring
  • prediction

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