Evidence map›Paper›PMID 34707521›Full record

ArticleFrontiers in psychiatry2021

Clinical Heterogeneity in ME/CFS. A Way to Understand Long-COVID19 Fatigue.

Iñigo Murga, Larraitz Aranburu, Pascual A Gargiulo, Juan Carlos Gómez Esteban, José-Vicente Lafuente

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.

  1. Recent research in myalgic encephalomyelitis/chronic fatigue syndrome: an evidence map.Health technology assessment (Winchester, England) · 2025
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  20. Autonomic and neuropathic complaints of long-COVID objectified: an investigation from electrophysiological perspective.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Iñigo MurgaLaNCE-Neuropharm Group, Department of Neuroscience, University of the Basque Country (UPV-EHU), Leioa, Spain.
Larraitz AranburuDepartment of Mathematics, University of the Basque Country (UPV-EHU), Leioa, Spain.
Pascual A GargiuloLab Experimental Psychology, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Department of Pathology, Universidad Nacional de Cuyo (UNC), Mendoza, Argentina.
Juan Carlos Gómez EstebanLaNCE-Neuropharm Group, Department of Neuroscience, University of the Basque Country (UPV-EHU), Leioa, Spain.
José-Vicente LafuenteLaNCE-Neuropharm Group, Department of Neuroscience, University of the Basque Country (UPV-EHU), Leioa, Spain.
BioCruces Health research Institute · ESUniversity of the Basque Country · ESConsejo Nacional de Investigaciones Científicas y Técnicas · AR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Chronic Fatigue Syndromedysautonomialong COVID-19Myalgic Encephalomyelitispost-viral fatigue

Identifiers

PMID34707521
PMCPMC8542754
OpenAlexW3205243164

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.