dc.creatorMurga, Iñigo
dc.creatorAranburu, Larraitz
dc.creatorGargiulo, Pascual Angel
dc.creatorGomez Esteban, Juan Carlos
dc.creatorLafuente, Jose Vicente
dc.date.accessioned2022-05-11T13:39:02Z
dc.date.accessioned2022-10-15T07:46:11Z
dc.date.available2022-05-11T13:39:02Z
dc.date.available2022-10-15T07:46:11Z
dc.date.created2022-05-11T13:39:02Z
dc.date.issued2021-10
dc.identifierMurga, 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.identifier1664-0640
dc.identifierhttp://hdl.handle.net/11336/157197
dc.identifierCONICET Digital
dc.identifierCONICET
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4361987
dc.description.abstractThe 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.languageeng
dc.publisherFrontiers Media
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3389/fpsyt.2021.735784
dc.rightshttps://creativecommons.org/licenses/by/2.5/ar/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectLONG COVID-19
dc.subjectMYALGIC ENCEPHALOMYELITIS
dc.subjectCHRONIC FATIGUE SYNDROME
dc.subjectPOST-VIRAL FATIGUE
dc.subjectDYSAUTONOMIA
dc.subjectCOVID-19
dc.titleClinical Heterogeneity in ME/CFS: A Way to Understand Long-COVID19 Fatigue
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/publishedVersion


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