title: Dynamic Stress Factor (DySF): A Significant Predictor of Severe Hypoglycemic Events in Children with Type 1 Diabetes.
abstract: Hemoglobin A1c (HbA1c) is the current standard used in the clinical treatment of patients with diabetes. However, it has been shown that patients with similar HbA1c values may have widely different fluctuations in blood glucose values over the same period of time, including time spent in hyper- and/or hypo-glycemia. Hence, there exists a need for quantitative measures that can supplement HbA1c in managing patients with diabetes. We introduce and compare the Dynamic Stress Factor, DySF, a newly developed metric that quantifies glycemic volatility based on patient-specific glucose transition density profiles with HbA1c and with currently used glucose variability metrics in predicting severe hypoglycemia in children with type 1 diabetes. DySF, the daily weighted number of large monotonic glycemic transitions that occur within one hour, was calculated for 441 total subjects with type 1 diabetes (146 children, aged 8-14 yrs) to assess the magnitude and frequency of glucose transitions per day. Severe hypoglycemic episodes (HE) were quantified for all subjects and evaluated against HbA1c and existing measures of glucose variability, including SD, MAGE, MODD, and CONGA using logistic regression models. DySF was found to be a predictor of severe HE in children (p = 0.018) with the likelihood of a child, aged 8-14 yrs, experiencing severe hypoglycemia increasing by up to 20% with decreasing values of up to 60% of DySF. Patients of any age who had one or multiple severe hypoglycemic episodes had on average a lower DySF when compared to those with no HE. Additionally, when considering mean glucose levels, DySF/mean was a preliminary predictor of severe HE in patients with HbA1c ≤ 6.5% (p = 0.062). DySF is a dynamic, quantitative, measure of daily glucose "volatility" that separates patients, within the same strata of HbA1c, into visually distinct patient profiles. DySF can be used as a preliminary predictor of clinically severe hypoglycemia in children and "well-controlled" patients with HbA1c ≤ 6.5%.
authors.affiliation: Center for Computational Medicine and Bioinformatics, University of Michigan, USA ; Departments of Biophysics, University of Michigan, USA.
authors.forename: Ra
authors.initials: R
authors.lastname: Rawlings
authors.affiliation: Departments of Mathematics, University of Michigan, USA ; University of Michigan Program in Informatics, University of Michigan, USA.
authors.forename: L
authors.initials: L
authors.lastname: Yuan
authors.affiliation: University of Michigan Medical School, USA.
authors.forename: H
authors.initials: H
authors.lastname: Shi
authors.affiliation: Brehm Center for Diabetes Research, University of Michigan, USA.
authors.forename: W
authors.initials: W
authors.lastname: Brehm
authors.affiliation: Brehm Center for Diabetes Research, University of Michigan, USA ; Internal Medicine, Division of Metabolism, Endocrinology and Diabetes, University of Michigan, USA.
authors.forename: R
authors.initials: R
authors.lastname: Pop-Busui
authors.affiliation: Center for Computational Medicine and Bioinformatics, University of Michigan, USA.
authors.forename: Pw
authors.initials: P
authors.lastname: Nelson