Digital monitoring for integrated progression assessment of myalgic encephalomyelitis / chronic fatigue syndrome
Aim
2. Deployment of a digital interface in a simplified web application and pilot use of the web interface with 4-5 trained ME/CFS patients to optimize the PHDA design.
3. Development of an optimized prototype for ME/CFS PHDA.
4. App-based PHDA study in a small group (10-12) to evaluate functionality and obtain results on the relationship between clinical, laboratory, and digital biomarkers, integrated health and care systems.
5. Submission of a proposal for a clinical validation and scaling project.
Description
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic condition with unclear etiology and a lack of diagnostic and progression biomarkers. Despite numerous studies investigating various biomedical aspects of ME/CFS, questions about recovery, reversibility, and progression remain unclear. At the same time, recent studies indicate biomarker patterns characteristic of severity classes, but given the fluctuating nature and the fact that most markers do not leave the normal range or no normal range is defined, diagnostic and prognostic capabilities are limited and have fewer chances for integration into the healthcare system. A digital assistant that follows patients at different stages and is integrated into the functional areas of the healthcare system could fill the gap. The proposed study will develop a digitally integrated assistance solution based on digital phenotyping, connecting digital biomarkers with the best possible set of serum biomarkers. The results will be ready for integration into symptom checker applications and, using the relevant ontology approach, in artificial intelligence systems. An important enabler of the digital assistant and digital health is coaching to improve patient self-management skills.
