Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Department of Creative IT Engineering, Pohang University of Science and Technology (POSTECH), Pohang, Korea.
Diabetes Metab J. 2020 Feb;44(1):56-66. doi: 10.4093/dmj.2018.0227. Epub 2019 Oct 21.
We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome.
Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (=91), multivariable binary logistic regression analysis models were used to determine the independent associates with a delayed response (taking ≥6.0 hours for entering a glucose range of 70 to 180 mg/dL). The CII protocol was adjusted according to the EHR-based parameters obtained in the first 3 hours of CII.
Use of the CII protocol was associated with fewer subjects with hypoglycemia alert values (=0.003), earlier (=0.002), and more stable (=0.017) achievement of a glucose range of 70 to 180 mg/dL. Initial glucose level (=0.001), change in glucose during the first 2 hours (=0.026), and change in insulin infusion rate during the first 3 hours (=0.029) were independently associated with delayed responses. Increasing the insulin infusion rate temporarily according to these parameters significantly reduced delayed responses (<0.0001) without hypoglycemia, especially in refractory patients.
Our CII protocol enabled faster and more stable glycemic control than conventional care with minimized risk of hypoglycemia. An EHR-based adjustment was simulated to reduce delayed responses without increased incidence of hypoglycemia.
我们旨在描述整合到电子健康记录 (EHR) 系统中的计算机化静脉内胰岛素输注 (CII) 方案的结果，并使用基于 EHR 的结局预测因子在计算机上改进 CII 方案。
评估了 2016 年 7 月至 2017 年 2 月期间接受 CII 方案的患者及其匹配对照的临床结局。在 CII 方案组 (=91)中，使用多变量二项逻辑回归分析模型确定与延迟反应（达到血糖范围 70 至 180mg/dL 需≥6.0 小时）相关的独立因素。根据 CII 开始后 3 小时内获得的基于 EHR 的参数调整 CII 方案。
使用 CII 方案与低血糖警报值减少（=0.003）、更快（=0.002）和更稳定（=0.017）达到 70 至 180mg/dL 血糖范围的患者比例更高。初始血糖水平（=0.001）、前 2 小时血糖变化（=0.026）和前 3 小时胰岛素输注率变化（=0.029）与延迟反应独立相关。根据这些参数暂时增加胰岛素输注率可显著减少延迟反应（<0.0001）而不引起低血糖，尤其是在难治性患者中。
与常规治疗相比，我们的 CII 方案能够更快、更稳定地控制血糖，同时最大限度地降低低血糖风险。模拟基于 EHR 的调整以减少延迟反应，而不增加低血糖发生率。
