Abstract
In this study, we investigated which predictors from people with type 1 diabetes at initiation of intensive treatment that increase the risk of not achieving glycemic target. Data from a clinical trial with type 1 diabetes people (n=460) were used in a logistic regression model to analyze the effect of the predictors on achievement of glycemic target. Results indicate that age, smoking, glycated hemoglobin, 1,5-anhydroglucitol and fluctuation from continuous glucose monitoring are predictors of achievement of glycemic target, which can be used in an algorithm to predict people who fail to achieve glycemic target.
Original language | English |
---|---|
Title of host publication | Digital Personalized Health and Medicine |
Number of pages | 2 |
Publisher | IOS Press |
Publication date | 2020 |
Pages | 1413-1414 |
ISBN (Print) | 978-1-64368-082-8 |
ISBN (Electronic) | 978-1-64368-083-5 |
DOIs | |
Publication status | Published - 2020 |
Event | Medical Informatics Europe Conference (MIE) - Geneve, Switzerland Duration: 28 Apr 2019 → 1 May 2019 Conference number: 30 |
Conference
Conference | Medical Informatics Europe Conference (MIE) |
---|---|
Number | 30 |
Country/Territory | Switzerland |
City | Geneve |
Period | 28/04/2019 → 01/05/2019 |
Series | Studies in Health Technology and Informatics |
---|---|
Volume | 270 |
ISSN | 0926-9630 |
Keywords
- Type 1 diabetes
- continuous glucose monitoring
- prediction