Displaying all 4 publications

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  1. Scott EM, Bilous RW, Kautzky-Willer A
    Diabetes Technol Ther, 2018 03;20(3):180-188.
    PMID: 29470094 DOI: 10.1089/dia.2017.0386
    BACKGROUND: Accuracy of the FreeStyle Libre™ Flash Glucose Monitoring System has not been evaluated in pregnant women with diabetes. The aim of this study was to determine accuracy (compared to self-monitoring of blood glucose [SMBG]), clinical safety, and acceptability of the FreeStyle Libre System when used at home by this population.

    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.

  2. Rama Chandran S, Tay WL, Lye WK, Lim LL, Ratnasingam J, Tan ATB, et al.
    Diabetes Technol Ther, 2018 05;20(5):353-362.
    PMID: 29688755 DOI: 10.1089/dia.2017.0388
    BACKGROUND: Hypoglycemia is the major impediment to therapy intensification in diabetes. Although higher individualized HbA1c targets are perceived to reduce the risk of hypoglycemia in those at risk of hypoglycemia, HbA1c itself is a poor predictor of hypoglycemia. We assessed the use of glycemic variability (GV) and glycemic indices as independent predictors of hypoglycemia.

    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 

  3. Lee JY, Lee SWH
    Diabetes Technol Ther, 2018 Jul;20(7):492-500.
    PMID: 29812965 DOI: 10.1089/dia.2018.0098
    BACKGROUND: Telemedicine has been utilized increasingly worldwide for diabetes management, due to its potential to improve healthcare access and clinical outcomes. Few studies have assessed the economic benefits of telemedicine, which may contribute to underfunding in potentially important programs. We aim to systematically review the literature on economic evaluations of telemedicine in diabetes care, assess the quality, and summarize the evidence on driver of cost-effectiveness.

    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.

  4. Rama Chandran S, A Vigersky R, Thomas A, Lim LL, Ratnasingam J, Tan A, et al.
    Diabetes Technol Ther, 2020 02;22(2):103-111.
    PMID: 31502876 DOI: 10.1089/dia.2019.0277
    Background:
    Complex changes of glycemia that occur in diabetes are not fully captured by any single measure. The Comprehensive Glucose Pentagon (CGP) measures multiple aspects of glycemia to generate the prognostic glycemic risk (PGR), which constitutes the relative risk of hypoglycemia combined with long-term complications. We compare the components of CGP and PGR across type 1 and type 2 diabetes.
    Methods:
    Participants: n = 60 type 1 and n = 100 type 2 who underwent continuous glucose monitoring (CGM). Mean glucose, coefficient of variation (%CV), intensity of hypoglycemia (INThypo), intensity of hyperglycemia (INThyper), time out-of-range (TOR <3.9 and >10 mmol/L), and PGR were calculated. PGR (median, interquartile ranges [IQR]) for diabetes types, and HbA1c classes were compared.
    Results:
    While HbA1c was lower in type 1 (type 1 vs. type 2: 8.0 ± 1.6 vs. 8.6 ± 1.7, P = 0.02), CGM-derived mean glucoses were similar across both groups (P > 0.05). TOR, %CV, INThypo, and INThyper were all higher in type 1 [type 1 vs. type 2: 665 (500, 863) vs. 535 (284, 823) min/day; 39% (33, 46) vs. 29% (24, 34); 905 (205, 2951) vs. 18 (0, 349) mg/dL × min2; 42,906 (23,482, 82,120) vs. 30,166 (10,276, 57,183) mg/dL × min2, respectively, all P 
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