The ME/CFS study (MECFS-R) aims to create a large-scale registry that provides data on epidemiology, phenotypes, and disease trajectories of and health care for ME/CFS at any age in Germany, which can be used for future clinical trials.
ME/CFS (ICD-10 G93.3) is a multisystem chronic disease that can lead to severe disability. Pre-pandemic prevalence was estimated at approximately 0.3% worldwide, and increasing prevalence is observed due to ME/CFS in the context of long-term sequelae of coronavirus diseases 2019 (COVID-19). In Germany, the number of affected people in Germany was estimated as approximately 350.000-400.000 in 2018/2019 and almost 500.000 in 2021. ME/CFS can manifest at any age, with peak prevalence in adolescents and young adults. Common triggers include COVID, influenza, and Epstein-Barr virus-associated infectious mononucleosis (EBV-IM). Non-infectious triggers are known as well. Autoimmunity and dysfunction of the autonomic nervous system (ANS) were suggested as possible pathomechanisms. Core symptoms include fatigue, post-exertional malaise (PEM), and unrefreshing sleep. Additional symptoms comprise cognitive deficits ("brain fog"), orthostatic intolerance, neuroendocrine, and immunological symptoms. ME/CFS is diagnosed according to clinical criteria (mostly criteria by the Institute of Medicine (IOM) or Canadian Consensus Criteria) and by appropriate differential diagnostics to exclude other disorders with similar symptoms. So far, no biomarker or specific therapy is available. Therapeutic approaches are holistic and aim at the palliation of symptoms as well as psychosocial support. Self-management with pacing is recommended. Knowledge of ME/CFS among healthcare providers is still scarce, and many patients do not receive adequate care. With this web-based, German-wide registry, the investigators aim at deep phenotyping of the disease, identification of subtypes and risk factors, describing trajectories of the disease and patient journeys, and providing clinical data for future clinical trials. Patients are also invited to contribute biosamples for future translational research.
Study Type
OBSERVATIONAL
Enrollment
650
MRI Chronic Fatigue Center for Young People (MCFC) Children's Hospital, Technical University of Munich & Munich Municipal Hospital
Munich, Bavaria, Germany
RECRUITINGPhenotyping ME/CFS: Medical History
Routine assessment of the medical history, such as current and previous medication, vaccinations, comorbidities, and more, to achieve a profound ME/CFS phenotype.
Time frame: 30 years
Assessment of routine physical examination findings
Routine physical examination to achieve a profound and detailed ME/CFS phenotype.
Time frame: 30 years
Number of participants with abnormal laboratory tests results
Measurement of a routine set of laboratory parameters including blood tests (cell count\[cell/µl\], C-reactive protein \[mg/dl\], immunoglobulins A/M/G \[md/dl\], antinuclear antibodies \[titer\], etc.) and urine/stool analysis (e.g. calprotectin \[mg/kg\], positive hemoglobin in urine test stripe) to achieve a profound ME/CFS phenotype.
Time frame: 30 years
Number of participants with abnormal technical exam results
Technical exams (e.g. restrictive and obstructive pattern in pulmonary function tests, conduction in electrocardiography, ultrasound imaging, magnetic resonance imaging, etc.) will be performed as indicated to achieve a profound and detailed ME/CFS phenotype.
Time frame: 30 years
Evaluation of Patient Journeys
Patients' journeys will be analyzed regarding the specialization of involved physicians visited, time to diagnosis, and time to treatment.
Time frame: 30 years
Definition of Sub-cohorts
Using routine data, sub-cohorts will be identified.
Time frame: 30 years
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Prevalence of Comorbidities
Prevalence of comorbidities of patients with ME/CFS will be analyzed.
Time frame: 30 years
Identification of Candidate Prognostic Markers
Correlation of routine clinical data (e.g., medical history, routine laboratory, and physical examination) with clinical outcome (e.g., health-related quality of life, disease severity, and social participation).
Time frame: 30 years