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Brain Analysis With a Complex Network Approach in Stroke Patients Based on Electroencephalography: A Systematic Review and Meta-Analysis Publisher



Asadi B1 ; Cuencazaldivar JN2, 3, 4 ; Nakhostin Ansari N5, 6 ; Ibanez J7, 8 ; Herrero P1 ; Calvo S1
Authors
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Authors Affiliations
  1. 1. Department of Physiatry and Nursing, Faculty of Health Sciences, IIS Aragon, University of Zaragoza, C/Domingo Miral s/n, Zaragoza, 50009, Spain
  2. 2. Grupo de Investigacion en Fisioterapia y Dolor, Departamento de Enfermeria y Fisioterapia, Facultad de Medicina y Ciencias de la Salud, Universidad de Alcala, Alcala de Henares, 28801, Spain
  3. 3. Physical Therapy Unit, Primary Health Care Center “El Abajon�, Las Rozas de Madrid, 28231, Spain
  4. 4. Research Group in Nursing and Health Care, Puerta de Hierro Health Research Institute—Segovia de Arana (IDIPHISA), Majadahonda, 28222, Spain
  5. 5. Research Center for War-Affected People, Tehran University of Medical Sciences, P.O. Box 14155-6559, Tehran, Iran
  6. 6. Department of Physiotherapy, School of Rehabilitation, Tehran University of Medical Sciences, P.O. Box 14155-6559, Tehran, Iran
  7. 7. BSICoS Group, IIS Aragon, Universidad de Zaragoza, Zaragoza, 50018, Spain
  8. 8. Department of Bioengineering, Imperial College, London, SW7 2AZ, United Kingdom

Source: Healthcare (Switzerland) Published:2023


Abstract

Background and purpose: Brain function can be networked, and these networks typically present drastic changes after having suffered a stroke. The objective of this systematic review was to compare EEG-related outcomes in adults with stroke and healthy individuals with a complex network approach. Methods: The literature search was performed in the electronic databases PubMed, Cochrane and ScienceDirect from their inception until October 2021. Results: Ten studies were selected, nine of which were cohort studies. Five of them were of good quality, whereas four were of fair quality. Six studies showed a low risk of bias, whereas the other three studies presented a moderate risk of bias. In the network analysis, different parameters such as the path length, cluster coefficient, small-world index, cohesion and functional connection were used. The effect size was small and not significant in favor of the group of healthy subjects (Hedges’g = 0.189 [−0.714, 1.093], Z = 0.582, p = 0.592). Conclusions: The systematic review found that there are structural differences between the brain network of post-stroke patients and healthy individuals as well as similarities. However, there was no specific distribution network to allows us to differentiate them and, therefore, more specialized and integrated studies are needed. © 2023 by the authors.
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