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Sathyanarayana A, El Atrache R, Jackson M, Cantley S, Reece L, Ufongene C, Loddenkemper T, Mandl KD, Bosl WJ. Measuring Real-Time Medication Effects From Electroencephalography. J Clin Neurophysiol 2024; 41:72-82. [PMID: 35583401 PMCID: PMC9669285 DOI: 10.1097/wnp.0000000000000946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
PURPOSE Evaluating the effects of antiseizure medication (ASM) on patients with epilepsy remains a slow and challenging process. Quantifiable noninvasive markers that are measurable in real-time and provide objective and useful information could guide clinical decision-making. We examined whether the effect of ASM on patients with epilepsy can be quantitatively measured in real-time from EEGs. METHODS This retrospective analysis was conducted on 67 patients in the long-term monitoring unit at Boston Children's Hospital. Two 30-second EEG segments were selected from each patient premedication and postmedication weaning for analysis. Nonlinear measures including entropy and recurrence quantitative analysis values were computed for each segment and compared before and after medication weaning. RESULTS Our study found that ASM effects on the brain were measurable by nonlinear recurrence quantitative analysis on EEGs. Highly significant differences ( P < 1e-11) were found in several nonlinear measures within the seizure zone in response to antiseizure medication. Moreover, the size of the medication effect correlated with a patient's seizure frequency, seizure localization, number of medications, and reported seizure frequency reduction on medication. CONCLUSIONS Our findings show the promise of digital biomarkers to measure medication effects and epileptogenicity.
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Affiliation(s)
- Aarti Sathyanarayana
- Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, U.S.A.;
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, U.S.A.;
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, U.S.A.;
| | - Rima El Atrache
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, U.S.A.; and
| | - Michele Jackson
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, U.S.A.; and
| | - Sarah Cantley
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, U.S.A.; and
| | - Latania Reece
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, U.S.A.; and
| | - Claire Ufongene
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, U.S.A.; and
| | - Tobias Loddenkemper
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, U.S.A.;
- Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, U.S.A.; and
| | - Kenneth D. Mandl
- Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, U.S.A.;
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, U.S.A.;
| | - William J. Bosl
- Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, U.S.A.;
- Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, U.S.A.;
- Department of Health Professions, University of San Francisco, San Francisco, California, U.S.A
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