Development and validation of a predictive model of acute glucose response to exercise in individuals with type 2 diabetes

Our purpose was to develop and test a predictive model of the acute glucose response to exercise in individuals with type 2 diabetes. Data from three previous exercise studies (56 subjects, 488 exercise sessions) were combined and used as a development dataset. A mixed-effects Least Absolute Shrinka...

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Bibliographic Details
Published in:Diabetology and metabolic syndrome 2013-07, Vol.5 (1), p.33-33, Article 33
Main Authors: Gibson, Bryan S, Colberg, Sheri R, Poirier, Paul, Vancea, Denise Maria Martins, Jones, Jason, Marcus, Robin
Format: Article
Language:English
Subjects:
Blood sugar
Care and treatment
Diabetes
Exercise
Glucose
Glycosylated hemoglobin
Health aspects
Physiological aspects
Studies
Type 2 diabetes
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Summary:Our purpose was to develop and test a predictive model of the acute glucose response to exercise in individuals with type 2 diabetes. Data from three previous exercise studies (56 subjects, 488 exercise sessions) were combined and used as a development dataset. A mixed-effects Least Absolute Shrinkage Selection Operator (LASSO) was used to select predictors among 12 potential predictors. Tests of the relative importance of each predictor were conducted using the Lindemann Merenda and Gold (LMG) algorithm. Model structure was tested using likelihood ratio tests. Model accuracy in the development dataset was assessed by leave-one-out cross-validation.Prospectively captured data (47 individuals, 436 sessions) was used as a test dataset. Model accuracy was calculated as the percentage of predictions within measurement error. Overall model utility was assessed as the number of subjects with ≤1 model error after the third exercise session. Model accuracy across individuals was assessed graphically. In a post-hoc analysis, a mixed-effects logistic regression tested the association of individuals' attributes with model error. Minutes since eating, a non-linear transformation of minutes since eating, post-prandial state, hemoglobin A1c, sulfonylurea status, age, and exercise session number were identified as novel predictors. Minutes since eating, its transformations, and hemoglobin A1c combined to account for 19.6% of the variance in glucose response. Sulfonylurea status, age, and exercise session each accounted for
ISSN:1758-5996
1758-5996
DOI:10.1186/1758-5996-5-33