Identifying Patterns in Long Term CGM and Insulin Data - An Explorative Study

Iben E Giese; Morten H Jensen; Thomas Kronborg; Therese H Søndergaard; Stine Hangaard

doi:10.3233/SHTI240335

Identifying Patterns in Long Term CGM and Insulin Data - An Explorative Study

Stud Health Technol Inform. 2024 Aug 22:316:21-22. doi: 10.3233/SHTI240335.

Authors

Iben E Giese¹, Morten H Jensen^{1

2}, Thomas Kronborg^{1

3}, Therese H Søndergaard¹, Stine Hangaard^{1

3}

Affiliations

¹ Department of Health Science and Technology, Aalborg University, Gistrup, Denmark.
² Data Science, Novo Nordisk A/S, Søborg, Denmark.
³ Steno Diabetes Center North DK, Aalborg University Hospital, Aalborg, Denmark.

PMID: 39176664
DOI: 10.3233/SHTI240335

Abstract

The increased utilization of continuous glucose monitors (CGM) and smart insulin pens (SIP) among people with type 2 diabetes generates significant health data. This study explored possible patterns in long term CGM and SIP data.

Keywords: Long term data; continuous glucose monitor; patterns; smart insulin pen.

MeSH terms

Blood Glucose / analysis
Blood Glucose Self-Monitoring*
Diabetes Mellitus, Type 2* / blood
Diabetes Mellitus, Type 2* / drug therapy
Humans
Hypoglycemic Agents / therapeutic use
Insulin Infusion Systems*
Insulin* / therapeutic use

Substances

Insulin
Blood Glucose
Hypoglycemic Agents