MATERIALS AND METHODS: Seventy-four participants, with type 1 (T1D, n = 24), type 2 (T2D, n = 11), or gestational (n = 39) diabetes, were enrolled across 13 sites (9 in United Kingdom, 4 in Austria). Average gestation was 26.6 ± 6.8 weeks (mean ± standard deviation), age was 30.5 ± 5.1 years, diabetes duration was 13.1 ± 7.3 years for T1D and 3.2 ± 2.5 years for T2D, and 49/74 (66.2%) used insulin to manage their diabetes. Sensors were worn for up to 14 days. Sensor glucose values (masked) were compared with capillary SMBG values (made at least 4 times/day).
RESULTS: Clinical accuracy of sensor results versus SMBG results was demonstrated, with 88.1% and 99.8% of results within Zone A and Zones A and B of the Consensus Error Grid, respectively. Overall mean absolute relative difference was 11.8%. Sensor accuracy was unaffected by the type of diabetes, the stage of pregnancy, whether insulin was used, age or body mass index. User questionnaires indicated high levels of satisfaction with sensor wear, system use, and comparison to SMBG. There were no unanticipated device-related adverse events.
CONCLUSIONS: Good agreement was demonstrated between the FreeStyle Libre System and SMBG. Accuracy of the system was unaffected by patient characteristics, indicating that the system is safe and accurate to use by pregnant women with diabetes.
METHODS: A retrospective observational study of 60 type 1 and 100 type 2 diabetes subjects. All underwent professional continuous glucose monitoring (CGM) for 3-6 days and recorded self-monitored blood glucose (SMBG). Indices were calculated from both CGM and SMBG. Statistical analyses included regression and area under receiver operator curve (AUC) analyses.
RESULTS: Hypoglycemia frequency (53.3% vs. 24%, P
MATERIALS AND METHODS: A literature search was performed in 10 databases from inception until February 2018. All economic evaluations assessing the economic evaluation of telemedicine in diabetes were eligible for inclusion. We subsequently evaluated the study quality in terms of effectiveness measures, cost measure, economic model, as well as time horizon.
RESULTS: Of the 1877 studies identified, 14 articles were included in our final review. The healthcare providers' fees are a major predictor for total cost. In particular, the use of telemedicine for retinal screening was beneficial and cost-effective for diabetes management, with an incremental cost-effectiveness ratio between $113.48/quality-adjusted life year (QALY) and $3,328.46/QALY (adjusted to 2017 inflation rate). Similarly, the use of telemonitoring and telephone reminders was cost-effective in diabetes management.
CONCLUSIONS: Among all telemedicine strategies examined, teleophthalmology was the most cost-effective intervention. Future research is needed to provide evidence on the long-term experience of telemedicine and facilitate resource allocation.