Impact of the Complexity of Glucose Time Series on All-Cause Mortality in Patients With Type 2 Diabetes
Authors' conclusion
Lower CGI is associated with an increased risk of all-cause mortality among patients with type 2 diabetes achieving the HbA1c target. CGI may be a new indicator for the identification of residual risk of death in well-controlled type 2 diabetes.
Study context
- Population
- Adult inpatients with T2D, single centre; CGI from continuous glucose monitoring (CGM) measured at baseline with refined composite multiscale entropy1,217 deaths
- Participants
- 6,000 inpatients
- Exposure
- CGI tertiles: < 2.15 and 2.15 to 2.99 vs ≥ 3.00
- Outcome
- All-cause mortality
- Follow-up
- Median 9.4 years
Methodological detailssingle-centre
- Single-centre
Main finding
As reported in the abstract
All-cause mortality, patients with HbA1c < 7.0%
Multivariable-adjusted HR (95% CI)
2.15-2.99vs ≥ 3.00
0.76(0.52–1.12)
< 2.15vs ≥ 3.00
1.47(1.03–2.09)
- Interaction between hemoglobin A1c (HbA1c) and CGI for all-cause mortality
- P for interaction = 0.016
Observational data: associations, not effects.
Further findings
Restricted cubic spline: CGI and all-cause mortality
- Nonlinear relationship in subjects with HbA1c < 7.0% only
- P for nonlinearity = 0.041
Original publication
Impact of the Complexity of Glucose Time Series on All-Cause Mortality in Patients With Type 2 Diabetes. J Clin Endocrinol Metab. Published 2 December 2022. doi:10.
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