Prediction and Prevention of Nocturnal Hypoglycemia in Persons With Type 1 Diabetes With Multiple Doses of Insulin Using Machine Learning Techniques.
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 10
- 试验地点
- 2
- 主要终点
- Sensitivity (SE) and specificity (SP) to predict Level 1 hypoglycemia
研究概览
简要总结
The objective is to develop a novel system to predict and prevent nocturnal hypoglycemia in type 1 diabetic (T1D) patients, focused in patients with multiple daily injections (MDI) therapy. The general idea is to make use of previous-day information in the moment when patients go to sleep, and then predict if in the next following hours any hypoglycemic event will occur. If the system will have predicted any hypoglycemic event in that moment, it is expected that it will be able to warn the patient to take some action: such as reduce basal insulin dose or to consume a snack before sleep.
10 patients with T1D for more than five years will be included.
It is a longitudinal, prospective, interventional study in which every patient will use intermittently scanned Continuous Glucose Monitoring (isCGM) and a physical activity tracker during 12 weeks. Moreover, during this period, patients will store in a mobile application (Freestyle LibreLink) or in a reader information regarding their diabetes management activities, such as insulin delivery doses and meal consumption.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients > 18 years with Type 1 Diabetes:
- •> 4 hypoglycemia / week (< 70 mg/dl, including day and night), last 2 weeks and / or
- •One severe hypoglycemia during the last year and / or
- •Hypoglycemia unawareness (Clarke Test >3)
- •Disease duration > 5 years
- •On multiple doses of insulin (MDI) therapy using a rapid acting insulin analogue as prandial insulin (lispro, aspart or glulisine) and any basal analogue as basal insulin.
- •A1c 6.5 - 9.5 %
- •Able to use an intermittently scanned continuous glucose monitoring (isCGM) system.
- •Performing >4 self-monitoring blood glucose (SMBG) per day
- •Using carb-counting
- •Providing an informed consent
- •No CGM user previously (during the last 3 months).
排除标准
- •Patients with a previous Diabetic Ketoacidosis (DKA) episode in the previous 6 months.
- •Patients with a severe hypoglycemia in the previous 6 months.
- •Severe diabetic complications or comorbidities: eye, renal, cardiovascular...from the clinicians point of view.
- •Pregnancy and breastfeeding.
- •History of drug or alcohol abuse.
- •Scheduled surgery during the study period.
- •Mental conditions that prevent the subject to understand the nature, purpose and possible consequences of the study.
- •Subjects those are unlikely to meet the clinical study protocol, eg uncooperative attitude, inability to return for follow-up visits, or poor probability of completing the study.
- •Using an experimental drug or device during the past 30 days.
研究组 & 干预措施
isCGM and Physical exercise tracker
Participants will perform CGM during 12 weeks using an isCGM (intermittently scanned Continuous Glucose Monitoring), Freestyle Libre, (Abbott Diabetes Care, Witney, Oxon, UK). Insulin dose (rapid-acting and long acting), carbohydrates and Self-monitoring blood glucose (SMBG) per day will be recorded by the patient in the reader or in the App (LibreLink, Abbott Diabetes Care, Witney, Oxon, UK). Moreover, participants will be instructed to collect data about moderate or high intensity exercise, illness and other disturbances occurring during the study period at home.
Patients will wear a physical exercise tracker (Fitbit Alta HR® wristband (Fitbit, Inc., San Francisco, California, USA)) to track physiological variables such as heart rate, steps, activity level and sleep quality.
干预措施: isCGM (intermittently scanned Continuous Glucose Monitoring) (Device)
isCGM and Physical exercise tracker
Participants will perform CGM during 12 weeks using an isCGM (intermittently scanned Continuous Glucose Monitoring), Freestyle Libre, (Abbott Diabetes Care, Witney, Oxon, UK). Insulin dose (rapid-acting and long acting), carbohydrates and Self-monitoring blood glucose (SMBG) per day will be recorded by the patient in the reader or in the App (LibreLink, Abbott Diabetes Care, Witney, Oxon, UK). Moreover, participants will be instructed to collect data about moderate or high intensity exercise, illness and other disturbances occurring during the study period at home.
Patients will wear a physical exercise tracker (Fitbit Alta HR® wristband (Fitbit, Inc., San Francisco, California, USA)) to track physiological variables such as heart rate, steps, activity level and sleep quality.
干预措施: Physical exercise tracker (Device)
结局指标
主要结局
Sensitivity (SE) and specificity (SP) to predict Level 1 hypoglycemia
时间窗: 90 days
Primary outcome will be sensitivity (SE) and specificity (SP) to predict Level 1 hypoglycemia. Level 1: a hypoglycemia alert glucose value between 54-70 mg/dL (3.0-3.9 mmol/L) with or without symptoms. A hypoglycemic event should be defined as follows. Beginning of a CGM event: readings below the threshold for at least 15 min are considered an event. For example, at least 15min, \<70 mg/dL (3.9 mmol/L) to define a significant hypoglycemic event. End of a CGM event: readings for 15 min at \>70 mg/dL (3.9 mmol/L).
次要结局
- Percentage of time in target range(90 days)
- Predicted HbA1c from the sensor data(90 days)
- Level 3 hypoglycaemia(90 days)
- Mean glucose(90 days)
- Glucose variability LBGI(90 days)
- Number of Level 3: severe hypoglycemia(90 days)
- Sensitivity (SE) and specificity (SP) to predict Level 2 hypoglycemia(90 days)
- Percentage of time in hypoglycemic ranges(90 days)
- Percentage of time in hyperglycemic range >250(90 days)
- Glucose variability HBGI(90 days)
- standard deviation (SD)(90 days)
- Percentage of time in hyperglycemic range >180(90 days)
研究者
Ignacio Conget
Head of Endocrinology and Nutrition Department, Principal Investigator
Hospital Clinic of Barcelona