Identifying Factors Associated With Acute Pain Exacerbation in Children With Complex Regional Pain Syndrome (CRPS): A Novel Research Plan
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 入组人数
- 150
- 试验地点
- 1
- 主要终点
- Change from baseline in pain score
研究概览
简要总结
objectives: identify physiologic, dietary, and environment triggers of severe pain exacerbations in children with CRPS.
详细描述
Hypothesis(es) and Aims: Investigators hypothesize that spontaneous exacerbations ("flares") of limb pain caused by CRPS have identifiable and predictable precipitants and timing. The aim of this trial is (1) to aggregate large databases of real-time physiological, psychological, subjective pain, environmental and dietary data and analyze these data with artificial intelligence (AI) to identify temporal precipitants to pain exacerbations, and (2) to identify potential strategies to interrupt the progression of acute pain flares based upon what is learned. Early treatment and strategies to interrupt acute pain flares would have a significant effect on quality of life in this patient population while undergoing treatment and resolution of the ongoing condition.
Design: Design of the study: prospective observational study. Subjects: will be recruited from Stanford's pediatric pain clinic and other like centers nation-wide. Subjects will be issued an Apple Watch and the Medeloop app for data collection. Data collection: Medeloop will collect subjects' electronic medical records (existing and prospective) if subjects sign into the hospital's patient portal through Medeloop.
The Apple Watch will transmit physiologic data to Medeloop in real time for a period of 6 months to derive physiologic parameters from Apple Watch measured pulse rate, oxygen saturation, time in daylight, ECG measurement, and movement/activity. Derived variables include heart rate variability, sleep hours, daily distance walked, right/left weight bearing and gait and others. Using a paired smartphone, subjects will photograph all meals for analysis of the dietary content by AI, which will be transmitted to Medeloop after capture for AI analysis. Medeloop software will use location data and cross-reference corresponding environmental and weather data (e.g., atmospheric conditions, air and water quality) on a daily basis. All pain flares will be recorded in real time via the Medeloop app.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 8 Years 至 17 Years(Child)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Clinical diagnosis of...
排除标准
- 未提供
研究组 & 干预措施
Children & Adolescents with Active CRPS
Subjects between the ages of 10 and 18 years, who have CRPS diagnosed in a pediatric pain center or clinic and whose CRPS is presently active (i.e. unresolved), of either gender, and any ethnicity or racial group.
For 6 months subjects will wear an Apple Watch, transmitting physiologic and movement data to the investigators, will photograph their meals for AI analysis of content, and log their pain scores and episodes of pain flares, and independently the investigators will collect weather and environmental data in the subject's location. These data will be analyzed by AI to identify chronologic triggers of pain flares.
干预措施: Apple Watch v8 (Device)
结局指标
主要结局
Change from baseline in pain score
时间窗: Baseline through month 6
Pain assessed on an 11-point Likert Scale (score range: 0 to 10)
次要结局
未报告次要终点
研究者
Elliot Krane
Professor Emeritus, Dept of Anesthesiology
Stanford University
