The MLC-R aims to create a large-scale registry that provides data on epidemiology, phenotypes, and disease trajectories of and health care for Long COVID at any age in Germany, which can be used for future clinical trials.
Infections with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been observed in Germany since January 2020 and can result in acute coronavirus disease 2019 (COVID-19) as well as in long-term sequela, referred to as Long COVID. The umbrella term Long COVID comprises ongoing new SARS-CoV-2-associated symptoms later than four weeks from the onset of acute COVID-19. The term Post-COVID-Condition (PCC) was introduced by the WHO and stands for ongoing or new SARS-CoV-2-associated symptoms, which persisted for at least two months. These symptoms often include fatigue, brain fog, dyspnea, orthostatic intolerance, as well as exercise intolerance, with a worsening of symptoms after mild daily activities (post-exertional malaise, PEM). PCC can severely impair daily function, social participation, and health-related quality of life. The prevalence was estimated as up to 15% in infected people with pre-Omicron variants and lower with Omicron variants. Risk factors include female gender and pre-existing morbidity, with low risk in young children. The most severe form of PCC in people with initially mild or moderate COVID-19 is myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The prevalence of ME/CFS was shown to increase in the context of the pandemic. While progress has been made in deciphering the pathogenesis of acute COVID-19, the mechanisms of Long COVID/PCC are poorly understood. Increasing evidence indicates that remaining viral particles, as well as inflammation, altered microcirculation, dysfunction of the autonomic nervous system, and/or autoimmunity, may contribute. With the web-based German MLC-R, we aim at deep phenotyping of PCC, 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
1,000
MRI Chronic Fatigue Center for Young People (MCFC) Children's Hospital, Technical University of Munich & Munich Municipal Hospital
Munich, Bavaria, Germany
RECRUITINGPhenotyping of Post-COVID condition: Medical History
Routine assessment of the medical history, such as current and previous medication, vaccinations, comorbidities, and more, to achieve a profound and detailed Post-COVID condition phenotype.
Time frame: 5 years
Phenotyping of Post-COVID condition: Physical Examination
Routine physical examination to achieve a profound and detailed Post-COVID condition phenotype.
Time frame: 5 years
Phenotyping of Post-COVID condition: Laboratory Parameters
Measurement of a routine set of laboratory parameters including blood tests (cell count, C-reactive protein, organ function, immunoglobulins, antibodies, etc.) and urine/stool analysis (calprotectin, blood) to achieve a profound Post-COVID condition phenotype.
Time frame: 5 years
Phenotyping of Post-COVID condition: Functional Tests
Technical exams (e.g. pulmonary function tests, electrocardiography, ultrasound, magnetic resonance imaging, etc.) will be performed as indicated to achieve a profound and detailed Post-COVID condition phenotype.
Time frame: 5 years
Analyzation of numbers of physicians involved
Patients' journeys will be analyzed in terms of the number of physicians involved
Time frame: 5 years
Evaluation of kind of spezializations of physicians involved
Patients' journeys will be analyzed in terms of the kind of specializations of physicians involved
Time frame: 5 years
Evaluation of kind of the latency of symptoms
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Patients' journeys will be analyzed in terms of the kind of specializations of physicians involved
Time frame: 5 years
Evaluation of kind of the onset of therapy
Patients' journeys will be analyzed in terms of the latency from symptom onset to initiation of therapy in months.
Time frame: 5 years
Definition of Sub-cohorts
Sub-cohorts are identified using routine data. By means of e.g. trigger, disease severity (e.g. Bell score from the worst outcome with 0 points till the best outcome with 100 points), daily functioning (e.g. SF-36).
Time frame: 5 years
Prevalence of Comorbidities
Prevalence of comorbidities of patients with Post-COVID condition will be analyzed.
Time frame: 5 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: 5 years