Literature DB >> 30615479

The Effects and Effect Sizes of Real-Time Continuous Glucose Monitoring on Patient-Reported Outcomes: A Secondary Analysis of the HypoDE Study.

Dominic Ehrmann1,2, Lutz Heinemann3, Guido Freckmann4, Delia Waldenmaier4, Gabriele Faber-Heinemann3, Norbert Hermanns1,2,5.   

Abstract

BACKGROUND: While real-time continuous glucose monitoring (rtCGM) has proven its efficacy for glycemic control and avoidance of hypoglycemia, evidence on its effects on patient-reported outcomes is still inconclusive. This secondary analysis of the HypoDE study analyzed effect sizes of rtCGM on patient-reported outcomes and compared them with the effect sizes for glycemic outcomes.
MATERIALS AND METHODS: The intervention group using rtCGM (n = 75) and the control group using self-monitored blood glucose measurements (n = 66) in the HypoDE study were compared. Effect sizes for the patient-reported outcome measures were calculated as the standardized between-group difference in baseline-adjusted follow-up scores (Cohen's d).
RESULTS: rtCGM had significant effects with medium effect sizes on satisfaction with the glucose monitoring device (d = 0.50; 95% confidence interval [CI] 0.84-0.17), fear of hypoglycemia (d = 0.32; 95% CI 0.66 to -0.01), and hypoglycemia-related distress (d = 0.41; 95% CI 0.74-0.08). However, nonsignificant effects and rather small effect sizes were found for general diabetes distress (d = 0.21; 95% CI 0.54 to -0.12), hypoglycemia unawareness (d = 0.03; 95% CI 0.37 to -0.30), and self-reported health status (d = 0.27; 95% CI 0.60 to -0.08), while the effect sizes for the hypoglycemia-related glycemic endpoints were large (d > 1.0). Based on these effect sizes for patient-reported outcomes, a much larger sample size would result in detecting significant differences in patient-reported outcomes.
CONCLUSIONS: Effect sizes of rtCGM on patient-reported outcomes are substantially smaller than those on glycemic outcomes. Studies on the efficacy of rtCGM previously had a glycemic endpoint with sample size calculations based on the larger effect sizes for glycemic outcomes. Thus, previous studies were neither powered to detect effects on patient-reported outcomes nor was the participant recruitment tailored to specific patient-reported outcomes. To demonstrate whether rtCGM affects patient-reported outcomes, future studies should consider this comparison of effect sizes.

Entities:  

Keywords:  Continuous glucose monitoring; Effect sizes.; Hypoglycemia; Patient-reported outcomes

Mesh:

Substances:

Year:  2019        PMID: 30615479     DOI: 10.1089/dia.2018.0332

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  3 in total

1.  Health care effects and medical benefits of a smartphone-based diabetes self-management application: study protocol for a randomized controlled trial.

Authors:  D Ehrmann; V Eichinger; I Vesper; J Kober; M Kraus; V Schäfer; N Hermanns; B Kulzer; S Silbermann
Journal:  Trials       Date:  2022-04-11       Impact factor: 2.279

2.  Impaired awareness of hypoglycaemia in women with type 1 diabetes in pregnancy: Hypoglycaemia fear, glycaemic and pregnancy outcomes.

Authors:  Jasmine Bahrami; George Tomlinson; Helen R Murphy; Denice S Feig
Journal:  Diabet Med       Date:  2022-01-30       Impact factor: 4.213

3.  Associations of Time in Range and Other Continuous Glucose Monitoring-Derived Metrics With Well-Being and Patient-Reported Outcomes: Overview and Trends.

Authors:  Dominic Ehrmann; Lilli Priesterroth; Andreas Schmitt; Bernhard Kulzer; Norbert Hermanns
Journal:  Diabetes Spectr       Date:  2021-05-25
  3 in total

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