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dc.contributor.author
Murga, Iñigo  
dc.contributor.author
Aranburu, Larraitz  
dc.contributor.author
Gargiulo, Pascual Angel  
dc.contributor.author
Gomez Esteban, Juan Carlos  
dc.contributor.author
Lafuente, Jose Vicente  
dc.date.available
2022-05-11T13:39:02Z  
dc.date.issued
2021-10  
dc.identifier.citation
Murga, Iñigo; Aranburu, Larraitz ; Gargiulo, Pascual Angel; Gomez Esteban, Juan Carlos; Lafuente, Jose Vicente; Clinical Heterogeneity in ME/CFS: A Way to Understand Long-COVID19 Fatigue; Frontiers Media; Frontiers in Psychiatry; 10-2021; 1-9  
dc.identifier.issn
1664-0640  
dc.identifier.uri
http://hdl.handle.net/11336/157197  
dc.description.abstract
The aim of present paper is to identify clinical phenotypes in a cohort of patients affected of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Ninety-one patients and 22 healthy controls were studied with the following questionnaires, in addition to medical history: visual analogical scale for fatigue and pain, DePaul questionnaire (post-exertional malaise, immune, neuroendocrine), Pittsburgh sleep quality index, COMPASS-31 (dysautonomia), Montreal cognitive assessment, Toulouse-Piéron test (attention), Hospital Anxiety and Depression test and Karnofsky scale. Co-morbidities and drugs-intake were also recorded. A hierarchical clustering with clinical results was performed. Final study group was made up of 84 patients, mean age 44.41 ± 9.37 years (66 female/18 male) and 22 controls, mean age 45 ± 13.15 years (14 female/8 male). Patients meet diagnostic criteria of Fukuda-1994 and Carruthers-2011. Clustering analysis identify five phenotypes. Two groups without fibromyalgia were differentiated by various levels of anxiety and depression (13 and 20 patients). The other three groups present fibromyalgia plus a patient without it, but with high scores in pain scale, they were segregated by prevalence of dysautonomia (17), neuroendocrine (15), and immunological affectation (19). Regarding gender, women showed higher scores than men in cognition, pain level and depressive syndrome. Mathematical tools are a suitable approach to objectify some elusive features in order to understand the syndrome. Clustering unveils phenotypes combining fibromyalgia with varying degrees of dysautonomia, neuroendocrine or immune features and absence of fibromyalgia with high or low levels of anxiety-depression. There is no a specific phenotype for women or men.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Frontiers Media  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
LONG COVID-19  
dc.subject
MYALGIC ENCEPHALOMYELITIS  
dc.subject
CHRONIC FATIGUE SYNDROME  
dc.subject
POST-VIRAL FATIGUE  
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DYSAUTONOMIA  
dc.subject
COVID-19  
dc.subject.classification
Psiquiatría  
dc.subject.classification
Medicina Clínica  
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CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
Clinical Heterogeneity in ME/CFS: A Way to Understand Long-COVID19 Fatigue  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2022-05-06T16:27:13Z  
dc.journal.pagination
1-9  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Murga, Iñigo. Universidad del País Vasco; España  
dc.description.fil
Fil: Aranburu, Larraitz. Universidad del País Vasco; España  
dc.description.fil
Fil: Gargiulo, Pascual Angel. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina  
dc.description.fil
Fil: Gomez Esteban, Juan Carlos. Universidad del País Vasco; España  
dc.description.fil
Fil: Lafuente, Jose Vicente. Universidad del País Vasco; España  
dc.journal.title
Frontiers in Psychiatry  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3389/fpsyt.2021.735784