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2020•Studies in health technology and informaticsOpen access

Towards Prediction of Type 1 Diabetes Patients Who Fail to Achieve Glycemic Target

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

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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.

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What this paper is about

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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Available 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.

Key concepts: Glycemic, Glycated hemoglobin, Type 2 diabetes, Logistic regression, Medicine, Diabetes mellitus, Internal medicine, Endocrinology

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