The Use of Extreme Value Statistics to Characterize Blood Glucose Curves and Patient Level Risk Assessment of Patients With Type I Diabetes
An erratum to this article was published (J Diabetes Sci Technol, Jul 2023 ↗)
Authors' conclusion
Through these estimates it is possible to assess each patient's individual clinical risk of hyperglycemia even beyond the observed blood glucose levels and detection limits. Additionally, it allows the assessment of the impact of clinical characteristics and treatments on blood glucose control in a novel, mathematically well-founded and potentially clinically more useful way than the already existing indicators.
Study context
- Population
- Patients with T1D
- Participants
- 226 patients170.8 patient-years
- Comparison
- Extreme value statistics metrics vs traditional glycemic variability metrics
- Outcome
- Patient-level risk of hyperglycemia: 1-year return level, probability of exceeding and expected time spent above 600 and 400 mg/dL per year
- Follow-up
- Per year
Methodological detailsextreme value statistics, non-stationary models
- Extreme value statistics
- Non-stationary models
Main finding
As reported in the abstract
High-risk patients identified with novel metrics
- High-risk patients (estimated time above 600 mg/dL per year >2 hours)
- 9
Further findings
Effect of BMI on extremes
- Higher BMI associated with more extreme glucose levels
Original publication
The Use of Extreme Value Statistics to Characterize Blood Glucose Curves and Patient Level Risk Assessment of Patients With Type I Diabetes. J Diabetes Sci Technol. Published 24 November 2021. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →