Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Center for Translational Research in Aging and Longevity, Texas A&M University, College Station, TX, USA.
Am J Clin Nutr. 2022 Oct 6;116(4):1059-1069. doi: 10.1093/ajcn/nqac181.
There has been growing interest in studying postprandial glucose responses using continuous glucose monitoring (CGM) in nondiabetic individuals. Accurate measurement of glucose responses to meals can facilitate applications such as precision nutrition and early detection of diabetes.
We aimed to quantify the discordance between simultaneous postprandial glucose measurements made using plasma and CGM.
We studied 10 nondiabetic older adults who randomly consumed 9 predefined meals of varying macronutrient compositions. Glucose was measured for 8 h after the meal by the CGM, blood samples for plasma collection were taken regularly, and plasma glucose was quantified using gold-standard laboratory measurement and a fingerstick blood glucose meter. The primary outcome measured was the mean absolute relative difference (MARD) of CGM and fingerstick measurements relative to the gold standard. Secondary outcomes were Bland-Altman statistics, Clarke Error Grid, and time in range metrics. Additional subgroup analyses were performed by stratifying the postprandial glucose measurements based on the macronutrient composition of the meals.
When compared against the gold-standard postprandial glucose measurements, the fingerstick meter was more accurate (MARD: 8.0%; 95% CI: 7.6%, 8.6%) than the CGM (MARD: 13.7%; 95% CI: 13.1%, 14.3%; P < 0.0001). After the meals, Bland-Altman analysis demonstrated that the CGM underestimated the 8-h gold-standard glucose rise by 12.8 mg/dL on average (P < 0.0001), whereas the fingerstick meter did so by 5.5 mg/dL on average (P < 0.0001). The CGM underestimated the time spent in the 70-180 mg/dL range (P = 0.002) and overestimated the time spent <70 mg/dL (P < 0.0001) compared with the other 2 methods.
We discovered discordance between gold standard, fingerstick, and CGM in measuring plasma glucose concentrations after a meal. Consequently, emerging applications of CGM in healthy individuals, such as precision nutrition and diabetes onset prediction, may need to account for these discordances.This trial was registered at clinicaltrials.gov as NCT04928872.
人们对使用连续血糖监测（CGM）研究非糖尿病个体的餐后血糖反应越来越感兴趣。准确测量膳食引起的血糖反应有助于实现精准营养和早期发现糖尿病等应用。
我们旨在量化使用血浆和 CGM 同时测量餐后血糖时的差异。
我们研究了 10 名非糖尿病老年个体，他们随机摄入了 9 种不同宏量营养素组成的预定义餐食。餐后 8 小时内通过 CGM 测量血糖，定期采集血浆样本，并使用金标准实验室测量和指尖血糖计定量检测血浆血糖。主要结局指标是 CGM 和指尖测量值与金标准相比的平均绝对相对差异（MARD）。次要结局指标为 Bland-Altman 统计、Clarke 误差网格和达标时间（TIR）指标。还进行了基于餐食宏量营养素组成的亚组分析。
与金标准餐后血糖测量相比，指尖血糖仪（MARD：8.0%；95%CI：7.6%，8.6%）比 CGM 更准确（MARD：13.7%；95%CI：13.1%，14.3%；P<0.0001）。餐后，Bland-Altman 分析表明，CGM 平均低估了 8 小时金标准血糖升高 12.8mg/dL（P<0.0001），而指尖血糖仪平均低估 5.5mg/dL（P<0.0001）。CGM 低估了 70-180mg/dL 范围内的时间（P=0.002），高估了 <70mg/dL 的时间（P<0.0001），与其他 2 种方法相比。
我们发现金标准、指尖和 CGM 在测量餐后血浆葡萄糖浓度时存在差异。因此，CGM 在健康个体中的新兴应用，如精准营养和糖尿病发病预测，可能需要考虑这些差异。该试验在 clinicaltrials.gov 注册为 NCT04928872。
