Bauhaus Helen, Erdogan Pinar, Braun Hans, Thevis Mario
Institute of Biochemistry, German Sport University Cologne, 50933 Cologne, Germany.
German Research Centre of Elite Sports, German Sport University Cologne, 50933 Cologne, Germany.
Int J Environ Res Public Health. 2023 Jul 25;20(15):6440. doi: 10.3390/ijerph20156440.
The objective of this pilot study was to compare glucose concentrations in capillary blood (CB) samples analysed in a laboratory by a validated method and glucose concentrations measured in the interstitial fluid (ISF) by continuous glucose monitoring (CGM) under different physical activity levels in a postprandial state in healthy athletes without diabetes. As a physiological shift occurs between glucose concentration from the CB into the ISF, the applicability of CGM in sports, especially during exercise, as well as the comparability of CB and ISF data necessitate an in-depth assessment. Ten subjects (26 ± 4 years, 67 ± 11 kg bodyweight (BW), 11 ± 3 h) were included in the study. Within 14 days, they underwent six tests consisting of (a) two tests resting fasted (HC_Rest/Fast and LC_Rest/Fast), (b) two tests resting with intake of 1 g glucose/kg BW (HC_Rest/Glc and LC_Rest/Glc), (c) running for 60 min at moderate (ModExerc/Glc), and (d) high intensity after intake of 1 g glucose/kg BW (IntExerc/Glc). Data were collected in the morning, following a standardised dinner before test day. Sensor-based glucose concentrations were compared to those determined from capillary blood samples collected at the time of sensor-based analyses and subjected to laboratory glucose measurements. Pearson's r correlation coefficient was highest for Rest/Glc (0.92, < 0.001) compared to Rest/Fast (0.45, < 0.001), ModExerc/Glc (0.60, < 0.001) and IntExerc/Glc (0.70, < 0.001). Mean absolute relative deviation (MARD) and standard deviation (SD) was smallest for resting fasted and similar between all other conditions (Rest/Fast: 8 ± 6%, Rest/Glc: 17 ± 12%, ModExerc/Glc: 22 ± 24%, IntExerc/Glc: 18 ± 17%). However, Bland-Altman plot analysis showed a higher range between lower and upper limits of agreement (95% confidence interval) of paired data under exercising compared to resting conditions. Under resting fasted conditions, both methods produce similar outcomes. Under resting postprandial and exercising conditions, respectively, there are differences between both methods. Based on the results of this study, the application of CGM in healthy athletes is not recommended without concomitant nutritional or medical advice.
这项初步研究的目的是比较在实验室中通过验证方法分析的毛细血管血（CB）样本中的葡萄糖浓度，以及在无糖尿病的健康运动员餐后不同身体活动水平下通过连续葡萄糖监测（CGM）测量的组织间液（ISF）中的葡萄糖浓度。由于葡萄糖浓度从CB向ISF发生生理转变，CGM在运动中的适用性，尤其是在运动期间，以及CB和ISF数据的可比性需要深入评估。该研究纳入了10名受试者（26±4岁，体重（BW）67±11kg，11±3小时）。在14天内，他们进行了六项测试，包括：（a）两次空腹休息测试（HC_Rest/Fast和LC_Rest/Fast），（b）两次摄入1g葡萄糖/kg BW后休息测试（HC_Rest/Glc和LC_Rest/Glc），（c）中等强度跑步60分钟（ModExerc/Glc），以及（d）摄入1g葡萄糖/kg BW后进行高强度运动（IntExerc/Glc）。数据在测试日前一天晚餐标准化后于早晨收集。将基于传感器的葡萄糖浓度与在基于传感器分析时采集的毛细血管血样本中测定并进行实验室葡萄糖测量的浓度进行比较。与Rest/Fast（0.45，<0.001）、ModExerc/Glc（0.60，<0.001）和IntExerc/Glc（0.70，<0.001）相比，Rest/Glc的Pearson's r相关系数最高（0.92，<0.001）。空腹休息时平均绝对相对偏差（MARD）和标准差（SD）最小，所有其他条件下相似（Rest/Fast：8±6%，Rest/Glc：17±12%，ModExerc/Glc：22±24%，IntExerc/Glc：18±17%）。然而，Bland-Altman图分析显示，与休息条件相比，运动时配对数据的一致性下限和上限之间的范围（95%置信区间）更高。在空腹休息条件下，两种方法产生相似的结果。在餐后休息和运动条件下，两种方法分别存在差异。基于本研究结果，不建议在没有伴随营养或医学建议的情况下，在健康运动员中应用CGM。
