Improving glucose control with advanced technology designed for high risk patients with type 1 diabetes

利用专为 1 型糖尿病高危患者设计的先进技术改善血糖控制

• 批准号: 9789266
• 负责人: Jessica R Castle
• 金额: $ 62.12万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789266
• 关键词: Acute; Address; Adult; Adverse event; Algorithms; Artificial Pancreas; Awareness; Behavioral; Blindness; Bluetooth; Calibration; Carbohydrates; Categories; Cellular Phone; Characteristics; Chronic; Clinical Research; Clinical Trials; Cognitive; Computer Simulation; Decision Support Systems; Detection; Diabetes Mellitus; Diabetic Ketoacidosis; Distress; Dose; Emotional; Event; Exercise; Failure; Fright; Glycosylated hemoglobin A; Grant; Guidelines; Hormones; Human; Hybrids; Hyperglycemia; Hypoglycemia; Infusion procedures; Injection of therapeutic agent; Injections; Inpatients; Insulin; Insulin Infusion Systems; Insulin-Dependent Diabetes Mellitus; Intervention; Kidney Failure; Machine Learning; Manuals; Modification; Multicenter Trials; Outcome; Outcome Measure; Outcome Study; Outpatients; Patients; Pattern Recognition; Performance; Personality; Pump; Quality of life; Questionnaires; Randomized; Randomized Clinical Trials; Reporting; Risk; Running; Surveys; System; Technology; Testing; Time; Update; arm; base; blood glucose regulation; clinically relevant; clinically significant; cohort; design; engineering design; expectation; falls; glucose monitor; glycemic control; high risk; high risk population; improved; patient population; primary outcome; research clinical testing; response; risk minimization; risk mitigation; secondary outcome; sensor; smart watch; support tools

Summary The objective of this proposal is to optimize the design and evaluate a robust artificial pancreas (R-AP) system for use in patients with uncontrolled type 1 diabetes (T1D) with HbA1C greater than 8% and compare HbA1C outcomes in these patients relative to a decision support system that utilizes continuous glucose monitoring (CGM) and multiple daily injection (MDI) therapy. Although high risk patients have possibly the most to gain from usage of AP technology, they are oftentimes under-represented or excluded from clinical trials. This has been because of the increased risk of failure of these AP systems that were not designed to handle inconsistent reporting of meals, variable activity level, and infusion set failures. An AP system for high risk patients needs to be designed to achieve maximal benefit, including reducing the risk of acute and chronic complications. A major obstacle for enabling the AP for usage by high-risk patients is that these patients may be less compliant with use guidelines for the system including missed meal announcements, infrequent sensor calibrations, and prolonged infusion set wear leading to infusion set failures. In this grant, we will integrate new risk-mitigation features into the OHSU single-hormone AP to enable usage by high-risk patients that fall into the categories described above. We present new algorithms for automating the detection of missed meal announcements, missed calibrations, and robust handling of hybrid usage mode. While AP systems may be an optimal choice for improving glycemic control, many people with T1D prefer MDI therapy. Decision support systems such as the DailyDose decision support system developed at OHSU can be used to improve glycemic control for patients who prefer MDI therapy. The DailyDose decision support system is designed for CGM augmented MDI therapy. It enables on-demand calculation of insulin doses, automates insulin dose adjustments based on pattern recognition, and uses machine learning approaches to alert the patients to events such as predicted hypoglycemia and missed meal doses.The benefit of the DailyDose system is that it is a simple system and does not require use of an insulin pump, which may be a challenge for some patients with uncontrolled type 1 diabetes as pump therapy is more intensive and requires infusion set changes. It is unknown in this high risk group of people whether patient needs, quality of life, and glycemic control are best addressed with an AP system or decision support tool or if both treatments are appropriate. We have designed a 3-month clinical study to compare glycemic outcomes during AP vs. decision support interventions in a high- risk T1D cohort (HbA1C 8-10.5%), with the aim of demonstrating a significant clinically relevant reduction in HbA1C. Our hypothesis is that both AP and decision support therapies will decrease HbA1C relative to baseline but that the AP will provide further benefit over DailyDose.

总结 本研究的目的是优化设计和评估一个强大的人工胰腺（R-AP）系统 用于HbA 1C大于8%的未控制的1型糖尿病（T1 D）患者，并比较HbA 1C 这些患者相对于使用连续血糖监测的决策支持系统的结局 (CGM)和每日多次注射（MDI）疗法。虽然高风险患者可能会获得最大的收益， 由于AP技术的使用，他们往往代表性不足或被排除在临床试验之外。这 是因为这些AP系统的故障风险增加， 进餐报告不一致、活动水平可变和输注管路故障。高风险的AP系统 患者需要被设计为实现最大益处，包括降低急性和慢性疾病的风险。 并发症使AP能够被高风险患者使用的主要障碍是这些患者可能 不太符合系统的使用指南，包括错过用餐通知，不频繁的传感器 校准和长时间的输液器磨损导致输液器故障。在这一补助金，我们将整合新的 风险缓解功能到OHSU单激素AP，使高风险患者的使用， 上述类别。我们提出了新的算法，自动检测错过吃饭 公告、错过校准以及对混合使用模式的稳健处理。虽然AP系统可能 作为改善血糖控制的最佳选择，许多T1 D患者更喜欢MDI治疗。决策支持 OHSU开发的DailyDose决策支持系统等系统可用于改善血糖控制， 对于偏好MDI治疗的患者进行对照。针对CGM设计了DailyDose决策支持系统 加强MDI治疗。它能够按需计算胰岛素剂量，自动化胰岛素剂量 基于模式识别进行调整，并使用机器学习方法提醒患者 事件，如预测的低血糖和错过的膳食剂量。DailyDose系统的好处是， 是一个简单的系统，不需要使用胰岛素泵，这对一些患者来说可能是一个挑战 对于未控制的1型糖尿病，因为泵治疗更密集，需要更换输液器。是 尚不清楚在这一高危人群中，患者需求、生活质量和血糖控制是否最佳 使用AP系统或决策支持工具解决，或者如果两种治疗都合适。我们设计了 一项为期3个月的临床研究，旨在比较AP与决策支持干预期间的血糖结局， 风险T1 D队列（HbA 1C 8-10.5%），目的是证明 HbA1C。我们的假设是，AP和决策支持疗法都将降低HbA 1C， 但AP将提供超过DailyDose的进一步获益。