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Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression

Introduction: Post-stroke depression (PSD) has complex pathophysiology determined by various biological and psychological factors. Although it is a long-term complication of stroke, PSD is often underdiagnosed. Given the diagnostic role of quantitative electroencephalography (qEEG) in depression, it...

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Autores principales: Livinț Popa, Livia, Chira, Diana, Dăbală, Victor, Hapca, Elian, Popescu, Bogdan Ovidiu, Dina, Constantin, Cherecheș, Răzvan, Strilciuc, Ștefan, Mureșanu, Dafin F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818970/
https://www.ncbi.nlm.nih.gov/pubmed/36611341
http://dx.doi.org/10.3390/diagnostics13010049
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author Livinț Popa, Livia
Chira, Diana
Dăbală, Victor
Hapca, Elian
Popescu, Bogdan Ovidiu
Dina, Constantin
Cherecheș, Răzvan
Strilciuc, Ștefan
Mureșanu, Dafin F.
author_facet Livinț Popa, Livia
Chira, Diana
Dăbală, Victor
Hapca, Elian
Popescu, Bogdan Ovidiu
Dina, Constantin
Cherecheș, Răzvan
Strilciuc, Ștefan
Mureșanu, Dafin F.
author_sort Livinț Popa, Livia
collection PubMed
description Introduction: Post-stroke depression (PSD) has complex pathophysiology determined by various biological and psychological factors. Although it is a long-term complication of stroke, PSD is often underdiagnosed. Given the diagnostic role of quantitative electroencephalography (qEEG) in depression, it was investigated whether a possible marker of PSD could be identified by observing the evolution of the (Delta + Theta)/(Alpha + Beta) Ratio (DTABR), respectively the Delta/Alpha Ratio (DAR) values in post-stroke depressed patients (evaluated through the HADS-D subscale). Methods: The current paper analyzed the data of 57 patients initially selected from a randomized control trial (RCT) that assessed the role of N-Pep 12 in stroke rehabilitation. EEG recordings from the original trial database were analyzed using signal processing techniques, respecting the conditions (eyes open, eyes closed), and several cognitive tasks. Results: We observed two significant associations between the DTABR values and the HADS-D scores of post-stroke depressed patients for each of the two visits (V1 and V2) of the N-Pep 12 trial. We recorded the relationships in the Global (V1 = 30 to 120 days after stroke) and Frontal Extended (V2 = 90 days after stroke) regions during cognitive tasks that trained attention and working memory. For the second visit, the association between the analyzed variables was negative. Conclusions: As both our relationships were described during the cognitive condition, we can state that the neural networks involved in processing attention and working memory might go through a reorganization process one to four months after the stroke onset. After a period longer than six months, the process could localize itself at the level of frontal regions, highlighting a possible divergence between the local frontal dynamics and the subjective well-being of stroke survivors. QEEG parameters linked to stroke progression evolution (like DAR or DTABR) can facilitate the identification of the most common neuropsychiatric complication in stroke survivors.
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spelling pubmed-98189702023-01-07 Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression Livinț Popa, Livia Chira, Diana Dăbală, Victor Hapca, Elian Popescu, Bogdan Ovidiu Dina, Constantin Cherecheș, Răzvan Strilciuc, Ștefan Mureșanu, Dafin F. Diagnostics (Basel) Article Introduction: Post-stroke depression (PSD) has complex pathophysiology determined by various biological and psychological factors. Although it is a long-term complication of stroke, PSD is often underdiagnosed. Given the diagnostic role of quantitative electroencephalography (qEEG) in depression, it was investigated whether a possible marker of PSD could be identified by observing the evolution of the (Delta + Theta)/(Alpha + Beta) Ratio (DTABR), respectively the Delta/Alpha Ratio (DAR) values in post-stroke depressed patients (evaluated through the HADS-D subscale). Methods: The current paper analyzed the data of 57 patients initially selected from a randomized control trial (RCT) that assessed the role of N-Pep 12 in stroke rehabilitation. EEG recordings from the original trial database were analyzed using signal processing techniques, respecting the conditions (eyes open, eyes closed), and several cognitive tasks. Results: We observed two significant associations between the DTABR values and the HADS-D scores of post-stroke depressed patients for each of the two visits (V1 and V2) of the N-Pep 12 trial. We recorded the relationships in the Global (V1 = 30 to 120 days after stroke) and Frontal Extended (V2 = 90 days after stroke) regions during cognitive tasks that trained attention and working memory. For the second visit, the association between the analyzed variables was negative. Conclusions: As both our relationships were described during the cognitive condition, we can state that the neural networks involved in processing attention and working memory might go through a reorganization process one to four months after the stroke onset. After a period longer than six months, the process could localize itself at the level of frontal regions, highlighting a possible divergence between the local frontal dynamics and the subjective well-being of stroke survivors. QEEG parameters linked to stroke progression evolution (like DAR or DTABR) can facilitate the identification of the most common neuropsychiatric complication in stroke survivors. MDPI 2022-12-23 /pmc/articles/PMC9818970/ /pubmed/36611341 http://dx.doi.org/10.3390/diagnostics13010049 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Livinț Popa, Livia
Chira, Diana
Dăbală, Victor
Hapca, Elian
Popescu, Bogdan Ovidiu
Dina, Constantin
Cherecheș, Răzvan
Strilciuc, Ștefan
Mureșanu, Dafin F.
Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression
title Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression
title_full Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression
title_fullStr Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression
title_full_unstemmed Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression
title_short Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression
title_sort quantitative eeg as a biomarker in evaluating post-stroke depression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9818970/
https://www.ncbi.nlm.nih.gov/pubmed/36611341
http://dx.doi.org/10.3390/diagnostics13010049
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