Background Decreases in heart rate variability have been shown to be associated with poor outcomes in severe acute brain injury. However, it is unknown whether the changes in heart rate variability precede neurological deterioration in such patients. We explored the changes in heart rate variability measured by electrocardiography in patients who had neurological deterioration following severe acute brain injury, and examined the relationship between heart rate variability and electroencephalography parameters.
Methods Retrospective analysis of 25 patients who manifested neurological deterioration after severe acute brain injury and underwent simultaneous electroencephalography plus electrocardiography monitoring.
Results Eighteen electroencephalography channels and one simultaneously recorded electrocardiography channel were segmented into epochs of 120-second duration and processed to compute 10 heart rate variability parameters and three quantitative electroencephalography parameters. Raw electroencephalography of the epochs was also assessed by standardized visual interpretation and categorized based on their background abnormalities and ictalinterictal continuum patterns. The heart rate variability and electroencephalography parameters showed consistent changes in the 2-day period before neurological deterioration commenced. Remarkably, the suppression ratio and background abnormality of the electroencephalography parameters had significant reverse correlations with all heart rate variability parameters.
Conclusions We observed a significantly progressive decline in heart rate variability from the day before the neurological deterioration events in patients with severe acute brain injury were first observed.
Citations
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Association of Depressive and Somatic Symptoms with Heart Rate Variability in Patients with Traumatic Brain Injury Seung Don Yoo, Eo Jin Park Journal of Clinical Medicine.2022; 12(1): 104. CrossRef
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Background Neurological complications are a serious concern during extracorporeal membrane oxygenation (ECMO) support in neonates and infants. However, evaluating brain injury during ECMO has limitations. Herein, we report our experience with bedside electroencephalographic monitoring during ECMO support and compared this to post-ECMO brain imaging studies and immediate neurologic outcomes.
Methods We retrospectively reviewed the data for 18 children who underwent ECMO. From these subjects, we reviewed the medical records of 10 subjects who underwent bedside EEG monitoring during ECMO support. We collected data on patient demographics, clinical details of the ECMO course, electroencephalographic monitoring, brain imaging results, and neurologic outcomes.
Results The median age was 4 months (range: 7 days-22 months), the median weight was 5 (3.6-12) kg, and the median length of ECMO therapy was 86 (27-206) hours. Eight patients (80%) were weaned successfully, and seven (70%) survived to discharge. Those with normal to mildly abnormal electroencephalographic findings had non-specific to mildly abnormal brain computed tomography findings and no neurologic impairment. Those patients with a moderately to severely abnormal electroencephalograph had markedly abnormal brain computed tomography findings and remained neurologically impaired.
Conclusions Normal electroencephalographic findings are closely related to normal or mild neurologic impairment. Our results indicate that electroencephalographic monitoring during ECMO support can be a feasible tool for evaluating brain injury although further prospective studies are needed.
Citations
Citations to this article as recorded by
Neurological monitoring in ECMO patients: current state of practice, challenges and lessons Hassan Aboul-Nour, Ammar Jumah, Hafsa Abdulla, Amreeta Sharma, Bradley Howell, Namita Jayaprakash, Jayna Gardner-Gray Acta Neurologica Belgica.2023; 123(2): 341. CrossRef
Neurological Monitoring and Complications of Pediatric Extracorporeal Membrane Oxygenation Support Ahmed S. Said, Kristin P. Guilliams, Melania M. Bembea Pediatric Neurology.2020; 108: 31. CrossRef