Prediction of Poor Glycemic Control in Children with Type 1 Diabetes

Tanja F Holm; Morten H Jensen; Ole K Hejlesen; Søren Hagstrøm; Mette Madsen; Stine Hangaard

doi:10.3233/SHTI240770

Prediction of Poor Glycemic Control in Children with Type 1 Diabetes

Stud Health Technol Inform. 2024 Aug 22:316:1759-1760. doi: 10.3233/SHTI240770.

Authors

Tanja F Holm^{1

2}, Morten H Jensen^{1

3}, Ole K Hejlesen¹, Søren Hagstrøm^{2

4

5}, Mette Madsen^{2

4

5}, Stine Hangaard^{1

2}

Affiliations

¹ Department of Health Science and Technology, Aalborg University, Gistrup, Denmark.
² Steno Diabetes Center North Denmark, Aalborg University Hospital, Denmark.
³ Data Science, Novo Nordisk A/S, Søborg, Denmark.
⁴ Department of Pediatrics and Adolescent Medicine, Aalborg University Hospital, Aalborg, Denmark.
⁵ Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.

PMID: 39176556
DOI: 10.3233/SHTI240770

Abstract

This study developed and validated a machine learning model for predicting glycemic control in children with type 1 diabetes at the time of diagnosis, revealing age at diagnosis as the most informative predictor.

Keywords: Type 1 diabetes; children; decision support; glycemic control.

MeSH terms

Adolescent
Blood Glucose
Child
Child, Preschool
Diabetes Mellitus, Type 1* / blood
Female
Glycated Hemoglobin / analysis
Glycemic Control*
Humans
Machine Learning*
Male

Substances

Blood Glucose
Glycated Hemoglobin