Discordance Between Mealtimes Reported by Trial Participants with Type 2 Diabetes and Healthcare Professionals...Medical Informatics Europe (MIE) 34th Conference, August 25–29, 2024, Athens, Greece.
Healthy lifestyle behaviors are essential in the treatment of type 2 diabetes, and meal registration is therefore important. Manual meal registration is cumbersome and could be automated using continuous glucose monitoring (CGM). If such an algorithm is based on patient-reported meals, potential err...
| Publicado en: | Studies in Health Technology & Informatics Vol. 316; pp. 1849 - 1854 |
|---|---|
| Autores principales: | , , , , , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2024
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=179286614&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 179286614 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2024 vid: 316 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 179286614 179286614 179286614 10.3233/SHTI240791 179286614 ppf: 1849 ppct: 5 formats: tig: atl: Discordance Between Mealtimes Reported by Trial Participants with Type 2 Diabetes and Healthcare Professionals...Medical Informatics Europe (MIE) 34th Conference, August 25–29, 2024, Athens, Greece. aug: au: HOLDT-CASPERSEN, Nynne Sophie DETHLEFSEN, Claus HEJLESEN, Ole VESTERGAARD, Peter HANGAARD, Stine GIESE, Iben Engelbrecht EGMOSE, Julie JENSEN, Morten Hasselstrøm affil: Department of Data Science, Novo Nordisk, Denmark. sug: subj: Diabetes Mellitus, Type 2 Research Subjects Meals Eating Behavior Health Personnel Congresses and Conferences Greece Greece Human Funding Source Male Female Middle Age Aged Self Report Algorithms Blood Glucose Self-Monitoring Cross Sectional Studies Correlational Studies Descriptive Statistics Continuous Glucose Monitoring Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Healthy lifestyle behaviors are essential in the treatment of type 2 diabetes, and meal registration is therefore important. Manual meal registration is cumbersome and could be automated using continuous glucose monitoring (CGM). If such an algorithm is based on patient-reported meals, potential errors might be induced. Thus, the aim was to investigate potential errors in patient-reported mealtimes and the effect on automatic meal detection. Two healthcare professionals (HCPs) reported the mealtimes of the 18 included patients based on the patients’ CGM data to assess the agreement between HCP- and patient-reported mealtimes. A developed meal detection algorithm based on detecting the post-prandial glucose response using cross-correlation was used to assess the impact of errors in patient reported meals. The results showed poor disagreement between HCP- and patient reported meals and that the meal detection algorithm had a moderately better performance on the HCP-reported meals. Therefore, the possibility of errors in patient-reported mealtimes should be considered in the development of meal detection algorithms. However, more research is needed to confirm the results of this study. pubtype: Academic Journal doctype: proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|