Neuropsychological Predictors of Fatigue in Post-COVID Syndrome



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Matias Guiu, Jordi A. and Delgado Alonso, Cristina and Díez Cirarda, María and Martínez Petit, Álvaro and Oliver Mas, Silvia and Delgado Álvarez, Alfonso and Cuevas, Constanza and Valles Salgado, María and Gil, María José and Yus, Miguel and Gómez Ruiz, Natividad and Polidura, Carmen and Pagán, Josué and Matias Guiu, Jorge and Ayala, José Luis (2022) Neuropsychological Predictors of Fatigue in Post-COVID Syndrome. Journal of Clinical Medicine, 11 (13). p. 3886. ISSN 2077-0383

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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 R2 metrics. Our study did not find reliable neuropsychological predictors of cognitive fatigue in the post-COVID syndrome. This has important implications for the interpretation of fatigue and cognitive assessment. Specifically, MFIS cognitive domain could not properly capture actual cognitive fatigue. In addition, our findings suggest different pathophysiological mechanisms of fatigue and cognitive dysfunction in post-COVID syndrome.

Item Type:Article
Uncontrolled Keywords:fatigue; cognitive; neuropsychological; machine learning; post-COVID syndrome
Subjects:Sciences > Computer science > Artificial intelligence
Medical sciences > Medicine > Immunology
Medical sciences > Medicine > Neurosciences
ID Code:73679
Deposited On:19 Jul 2022 14:18
Last Modified:02 Aug 2022 11:52

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