Scidà Giuseppe, Corrado Alessandra, Abuqwider Jumana, Lupoli Roberta, Rainone Carmen, Della Pepa Giuseppe, Masulli Maria, Annuzzi Giovanni, Bozzetto Lutgarda
Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy.
Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy.
J Diabetes Sci Technol. 2024 Jun 5:19322968241256475. doi: 10.1177/19322968241256475.
Hybrid Closed-Loop Systems (HCLs) may not perform optimally on postprandial glucose control. We evaluated how first-generation and advanced HCLs manage meals varying in carbohydrates, fat, and protein.
According to a cross-sectional design, seven-day food records and HCLs reports from 120 adults with type 1 diabetes (MiniMed670G: n = 40, MiniMed780G: n = 49, Control-IQ [C-IQ]: n = 31) were analyzed. Breakfasts (n = 570), lunches (n = 658), and dinners (n = 619) were divided according to the median of their carbohydrate (g)/fat (g) protein (g) ratio (C/FP). After breakfast (4-hour), lunch (6-hour), and dinner (6-hour), continuous glucose monitoring (CGM) metrics and early and late glucose incremental area under the curves (iAUCs) and delivered insulin doses were evaluated. The association of C/FP and HCLs with postprandial glucose and insulin patterns was analyzed by univariate analysis of variance (ANOVA) with a two-factor design.
Postprandial glucose time-in-range 70 to 180 mg/dL was optimal after breakfast (78.3 ± 26.9%), lunch (72.7 ± 26.1%), and dinner (70.8 ± 27.3%), with no significant differences between HCLs. Independent of C/FP, late glucose-iAUC after lunch was significantly lower in C-IQ users than 670G and 780G ( < .05), with no significant differences at breakfast and dinner. Postprandial insulin pattern (Ins Ins) differed by type of HCLs at lunch ( = .026) and dinner ( < .001), being the early insulin dose (Ins) higher than the late dose (Ins) in 670G and 780G users with an opposite pattern in C-IQ users.
Independent of different proportions of dietary carbohydrates, fat, and protein, postprandial glucose response was similar in users of different HCLs, although obtained through different automatic insulin delivery patterns.
混合闭环系统(HCLs)在餐后血糖控制方面可能无法达到最佳效果。我们评估了第一代和先进的HCLs如何管理碳水化合物、脂肪和蛋白质含量不同的餐食。
根据横断面设计,分析了120名1型糖尿病成年人的七天食物记录和HCLs报告(美敦力670G:n = 40,美敦力780G:n = 49,Control-IQ [C-IQ]:n = 31)。早餐(n = 570)、午餐(n = 658)和晚餐(n = 619)根据其碳水化合物(克)/脂肪(克) 蛋白质(克)比例(C/FP)的中位数进行划分。早餐后(4小时)、午餐后(6小时)和晚餐后(6小时),评估连续血糖监测(CGM)指标、血糖曲线下早期和晚期葡萄糖增量面积(iAUCs)以及胰岛素给药剂量。通过双因素设计的单因素方差分析(ANOVA)分析C/FP和HCLs与餐后血糖和胰岛素模式的关联。
早餐后(78.3 ± 26.9%)、午餐后(72.7 ± 26.1%)和晚餐后(70.8 ± 27.3%),餐后血糖在70至180 mg/dL范围内的时间最佳,不同HCLs之间无显著差异。与C/FP无关,午餐后C-IQ用户的晚期葡萄糖-iAUC显著低于670G和780G用户(< .05),早餐和晚餐时无显著差异。午餐(= .026)和晚餐(< .001)时,餐后胰岛素模式(Ins Ins)因HCLs类型而异,670G和780G用户的早期胰岛素剂量(Ins)高于晚期剂量(Ins),而C-IQ用户则相反。
尽管通过不同的自动胰岛素给药模式实现,但独立于膳食碳水化合物、脂肪和蛋白质的不同比例,不同HCLs用户的餐后血糖反应相似。