Objective: To investigate the use of quantitative EEG (qEEG) in patients with acute encephalopathies (AEs) and EEG background abnormalities.
Method: Patients were divided into favorable outcome (group A, 43 patients) and an unfavorable outcome (group B, 5 patients). EEGLAB software was used for the qEEG analysis. A graphic of the spectral power from all channels was generated for each participant. Statistical comparisons between the groups were performed.
Results: In group A, spectral analysis revealed spectral peaks (theta and alpha frequency bands) in 84% (38/45) of the patients. In group B, a spectral peak in the delta frequency range was detected in one patient. The remainder of the patients in both groups did not present spectral peaks. Statistical analysis showed lower frequencies recorded from the posterior electrodes in group B patients.
Conclusion: qEEG may be useful in the evaluations of patients with AEs by assisting with the prognostic determination.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1590/0004-282X20130204 | DOI Listing |
Int J Surg
January 2025
Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Nanjing, Jiangsu, China.
Background: Type A aortic dissection (TAAD) remains a significant challenge in cardiac surgery, presenting high risks of adverse outcomes such as permanent neurological dysfunction and mortality despite advances in medical technology and surgical techniques. This study investigates the use of quantitative electroencephalography (QEEG) to monitor and predict neurological outcomes during the perioperative period in TAAD patients.
Methods: This prospective observational study was conducted at the hospital, involving patients undergoing TAAD surgery from February 2022 to January 2023.
Life (Basel)
January 2025
Department of Neurosciences, Iuliu Hațieganu University of Medicine and Pharmacy, No. 8 Victor Babeș Street, 400012 Cluj-Napoca, Romania.
Acute ischemic stroke (AIS) is frequently associated with long-term post-stroke cognitive impairment (PSCI) and dementia. While the mechanisms behind PSCI are not fully understood, the brain and cognitive reserve concepts are topics of ongoing research exploring the ability of individuals to maintain intact cognitive performance despite ischemic injuries. Brain reserve refers to the brain's structural capacity to compensate for damage, with markers like hippocampal atrophy and white matter lesions indicating reduced reserve.
View Article and Find Full Text PDFNeurotherapeutics
January 2025
Department of Neurology, Massachusetts General Hospital, Boston MA, USA. Electronic address:
Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Characteristic EEG changes have been identified in diverse neurologic conditions including stroke, trauma, and anoxia, and the increased utilization of continuous EEG (cEEG) has identified potentially harmful activity even in patients without overt clinical signs or neurologic diagnoses. Manual annotation by expert neurophysiologists is a major resource limitation in investigating the prognostic and therapeutic implications of these EEG patterns and in expanding EEG use to a broader set of patients who are likely to benefit.
View Article and Find Full Text PDFBrain Sci
December 2024
Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb, 10000 Zagreb, Croatia.
Background/objectives: Cognitive training paradigms rely on the idea that consistent practice can drive neural plasticity, improving not only connectivity within critical brain networks, but also ultimately result in overall enhancement of trained cognitive functions, irrespective of the specific task. Here we opted to investigate the temporal dynamics of neural activity and cognitive performance during a structured cognitive training program.
Methods: A group of 20 middle-aged participants completed 20 training sessions over 10 weeks.
Eur Stroke J
January 2025
Department of Neurology, Massachusetts General Hospital (MGH), Boston, MA, USA.
Purpose: Population level tracking of post-stroke functional outcomes is critical to guide interventions that reduce the burden of stroke-related disability. However, functional outcomes are often missing or documented in unstructured notes. We developed a natural language processing (NLP) model that reads electronic health records (EHR) notes to automatically determine the modified Rankin Scale (mRS).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!