Evidence map›Paper›PMID 35807173›Full record

ArticleJournal of clinical medicine2022

Neuropsychological Predictors of Fatigue in Post-COVID Syndrome.

Jordi A Matias-Guiu, Cristina Delgado-Alonso, María Díez-Cirarda, Álvaro Martínez-Petit, Silvia Oliver-Mas, Alfonso Delgado-Álvarez, Constanza Cuevas, María Valles-Salgado, María José Gil, Miguel Yus and 5 more

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

13 citing papers in PubMed, 25 citations in OpenAlex.

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  12. Fatigue and Cognitive Dysfunction Are Associated with Occupational Status in Post-COVID Syndrome.International journal of environmental research and public health · 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

15 authors at 2 institutions in 1 country.

Jordi A Matias-GuiuDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0001-5520-2708
Cristina Delgado-AlonsoDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.
María Díez-CirardaDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0001-6768-189X
Álvaro Martínez-PetitDepartment of Electronic Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain.
Silvia Oliver-MasDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.
Alfonso Delgado-ÁlvarezDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0002-1889-4503
Constanza CuevasDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.
María Valles-SalgadoDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.
María José GilDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.
Miguel YusDepartment of Radiology, Clinico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.
Natividad Gómez-RuizDepartment of Radiology, Clinico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0002-1182-5513
Carmen PoliduraDepartment of Radiology, Clinico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0003-2021-0374
Josué PagánDepartment of Electronic Engineering, Universidad Politécnica de Madrid, 28040 Madrid, Spain.ORCID 0000-0002-8357-7950
Jorge Matías-GuiuDepartment of Neurology, Hospital Clínico San Carlos Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0001-8162-9043
José Luis AyalaCenter for Computational Simulation, Universidad Politécnica de Madrid, Campus de Montegancedo, Boadilla del Monte, 28223 Madrid, Spain.ORCID 0000-0001-7236-5330
Universidad Complutense de Madrid · ESHospital Clínico San Carlos · ES

Funding

Comunidad de Madrid FIBHCSC 2020 COVIDComunidad de Madrid G63-Healthstart Plus HSP3Instituto de Salud Carlos III INT20/00079
6 · The paper itself

Abstract

Fatigue is one of the most disabling symptoms in several neurological disorders and has an important cognitive component. However, the relationship between self-reported cognitive fatigue and objective cognitive assessment results remains elusive. Patients with post-COVID syndrome often report fatigue and cognitive issues several months after the acute infection. We aimed to develop predictive models of fatigue using neuropsychological assessments to evaluate the relationship between cognitive fatigue and objective neuropsychological assessment results. We conducted a cross-sectional study of 113 patients with post-COVID syndrome, assessing them with the Modified Fatigue Impact Scale (MFIS) and a comprehensive neuropsychological battery including standardized and computerized cognitive tests. Several machine learning algorithms were developed to predict MFIS scores (total score and cognitive fatigue score) based on neuropsychological test scores. MFIS showed moderate correlations only with the Stroop Color-Word Interference Test. Classification models obtained modest F1-scores for classification between fatigue and non-fatigued or between 3 or 4 degrees of fatigue severity. Regression models to estimate the MFIS score did not achieve adequate

Indexed as

cognitivefatiguemachine learningneuropsychologicalpost-COVID syndrome

Identifiers

PMID35807173
PMCPMC9267301
OpenAlexW4283792812

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.