Predicting Pain Exacerbations in Children With Complex Regional Pain Syndrome (CRPS)

Complex Regional Pain Syndromes

Child, Pediatrics, Pain, Neuropathic, CRPS

objectives: identify physiologic, dietary, and environment triggers of severe pain exacerbations in children with CRPS.

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.

No related papers found yet.

United States