Department of Information Engineering, University of Padova, Padova, Italy.
Department of Medicine, University of Padova, Padova, Italy.
J Diabetes Sci Technol. 2023 Jan;17(1):107-116. doi: 10.1177/19322968211043162. Epub 2021 Sep 6.
Providing real-time magnitude and direction of glucose rate-of-change (ROC) via trend arrows represents one of the major strengths of continuous glucose monitoring (CGM) sensors in managing type 1 diabetes (T1D). Several literature methods were proposed to adjust the standard formula (SF) used for insulin bolus calculation by accounting for glucose ROC, but each of them provides different suggestions, making it difficult to understand which should be applied in practice. This work aims at performing an extensive in-silico assessment of their performance and safety.
The methods of Buckingham (BU), Scheiner (SC), Pettus/Edelman (PE), Klonoff/Kerr (KL), Aleppo/Laffel (AL), Ziegler (ZI), and Bruttomesso (BR) were evaluated using the UVa/Padova T1D simulator, in single-meal scenarios, where ROC and glucose at mealtime varied between [-2,+2] mg/dL/min and [80,200] mg/dL, respectively. Efficacy of postprandial glucose control was quantitatively assessed by time in, above and below range (TIR, TAR, and TBR, respectively).
For negative ROCs, all methods proved to increase TIR and decrease TAR and TBR vs SF, with KL, PE, and BR being the most effective. For positive ROCs, a general worsening of the performances is present, only BR improved the glycemic control when mealtime glucose was close to hypoglycemia, while SC resulted the safest in the other conditions.
Insulin bolus adjustment methods are effective for negative ROCs, but they generally appear to overdose for positive ROCs, calling for safer strategies in such a scenario. These results can be useful in outlining guidelines to identify which adjustment to apply based on the mealtime condition.
通过趋势箭头提供实时血糖变化率（ROC）的幅度和方向是连续血糖监测（CGM）传感器在管理 1 型糖尿病（T1D）方面的主要优势之一。已经提出了几种文献方法来调整用于胰岛素推注计算的标准公式（SF），以考虑血糖 ROC，但每种方法都提供了不同的建议，因此很难理解在实践中应该应用哪种方法。这项工作旨在对它们的性能和安全性进行广泛的计算机评估。
使用 UVa/Padova T1D 模拟器评估 Buckingham（BU）、Scheiner（SC）、Pettus/Edelman（PE）、Klonoff/Kerr（KL）、Aleppo/Laffel（AL）、Ziegler（ZI）和 Bruttomesso（BR）方法，在单餐场景中，ROC 和用餐时的血糖分别在[-2,+2]mg/dL/min 和[80,200]mg/dL 之间变化。通过餐后血糖控制的时间（TIR）、高于范围的时间（TAR）和低于范围的时间（TBR）来定量评估。
对于负 ROC，所有方法都证明与 SF 相比，TIR 增加，TAR 和 TBR 减少，KL、PE 和 BR 最有效。对于正 ROC，存在性能普遍恶化的情况，只有 BR 在进餐时血糖接近低血糖时改善了血糖控制，而 SC 在其他情况下则是最安全的。
胰岛素推注调整方法对负 ROC 有效，但它们通常对正 ROC 似乎剂量过高，因此在这种情况下需要更安全的策略。这些结果可用于概述指南，根据进餐情况确定应用哪种调整。
