2025-02-26 バース大学
<関連情報>
- https://www.bath.ac.uk/announcements/researchers-warn-continuous-glucose-monitors-can-overestimate-blood-sugar-levels/
- https://www.sciencedirect.com/science/article/pii/S0002916525000929
持続グルコースモニターは血糖値を過大評価し、バイアスの大きさは食後試験と個人によって異なる-無作為クロスオーバー試験 Continuous glucose monitor overestimates glycemia, with the magnitude of bias varying by postprandial test and individual – A randomized crossover trial.
Katie M. Hutchins, James A. Betts, Dylan Thompson, Aaron Hengist, Javier T. Gonzalez
The American Journal of Clinical Nutrition Available online: 26 February 2025
DOI:https://doi.org/10.1016/j.ajcnut.2025.02.024
Abstract
Background
Continuous glucose monitors (CGM) are used to characterize postprandial glycemia, yet no study has directly tested how different test foods/beverages alter CGM accuracy.
Objective
Assess glycemic responses to test foods/drinks using CGM versus capillary sampling (criterion).
Methods
Fifteen healthy females(n=9) and males(n=6) completed 7 laboratory visits in a randomized crossover design with ≥48h washout between visits. During each visit, participants consumed an oral carbohydrate challenge comprising either 50g glucose(CONTROL), or equivalent carbohydrate as whole-fruits(WHOLE), blended-fruits(BLEND), commercial fruit smoothie(PRODUCT), commercial smoothie ingested over 30±4min(SLOW), commercial smoothie with 5g inulin(FIBER), commercial smoothie providing 30g carbohydrate(DOSE). Glycemia was recorded from both CGM and capillary samples every 15min for 120min and expressed as incremental areas under the curve(iAUC). Glycemic index(GI) was calculated relative to CONTROL where appropriate. Exploratory analyses examined 1) inter-individual heterogeneity of CGM bias versus criterion; and 2) whether CGM bias could be improved with adjustment for baseline differences.
Results
CGM-estimated fasting and postprandial glucose concentrations were(mean±SD) 0.9±0.6 and 0.9±0.5 mmol/L higher than capillary estimates, respectively(both, p<0.001). CGM bias varied by postprandial test such that GI for PRODUCT was higher with CGM(69, 95%CI: 48, 99) versus capillary(53, 95%CI: 40,69; P=0.05). Furthermore, differences in CGM versus capillary fasting glucose concentrations varied by participant(p=0.001). Unadjusted, CGM overestimated time >7.8mmol/L by ∼4-fold, and adjustment for baseline differences reduced this overestimate to ∼2-fold(both p<0.01).
Conclusions
CGM overestimated glycemic responses in numerous contexts. At times this can mischaracterize the GI. In addition, there is inter-individual heterogeneity of the accuracy of CGM to estimate fasting glucose concentrations. Correction for this difference reduces, but does not eliminate, postprandial overestimate of glycemia by CGM. Caution should be applied when inferring absolute or relative glycemic responses to foods using CGM, and capillary sampling should be prioritised for accurate quantification of glycemic response. Clinical Trial Registry: https://clinicaltrials.gov/study/NCT06333184
