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1000
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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Purpose</jats:title>
<jats:p>The aim was to assess the accuracy of a continuous blood glucose monitoring (CGM) device (Abbott FreeStyle Libre 3) against capillary blood glucose measurement (BGM) before, during, and after an intense lower body strength training session in connection with high- versus low-carbohydrate breakfasts.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>Nine adults (22 ± 2 years) completed a strength training session (10 × 10 at 60% 1RM) twice after high-carbohydrate and twice after low-carbohydrate breakfasts. CGM accuracy versus BGM was assessed across four phases: post-breakfast, pre-exercise, exercise, and post-exercise.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>Overall fed state mean BGM levels were 84.4 ± 20.6 mg/dL. Group-level Bland–Altman analysis showed acceptable agreement between CGM and BGM across all phases, with mean biases between − 7.95 and − 17.83 mg/dL; the largest discrepancy was in the post-exercise phase. Mean absolute relative difference was significantly higher post-exercise compared to pre-exercise and exercise phases, for overall data and after the high-carbohydrate breakfast (all <jats:italic>p</jats:italic> ≤ 0.02). Clark Error Grid analysis showed 50.5–64.3% in Zone A and 31.7–44.6% in Zone B, with an increase in treatment errors during and after exercise.</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusion</jats:title>
<jats:p>In this group of healthy participants undergoing strength training, CGM showed satisfactory accuracy in glucose monitoring but varied substantially between individuals compared to BGM and fails in meeting clinical criteria for diabetic monitoring. CGM could aid non-diabetic athletes by tracking glucose fluctuations due to diet and exercise. Although utilization of CGM shows potential in gathering, analyzing, and interpreting interstitial glucose for improving performance, the application in sports nutrition is not yet validated, and challenges in data interpretation could limit its adoption.</jats:p>
</jats:sec>
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1000
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Hinweis
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DeepGreen-ID: d3e7f19a8eb145eb805b2cbe4b6188fb ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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