Automated differentiation between epileptic and nonepileptic convulsive seizures.
case_series · Level IV
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- Record sourced from PubMed, PMID 25545895.
- Also identified by DOI 10.1002/ana.24338.
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Abstract
Our objective was the clinical validation of an automated algorithm based on surface electromyography (EMG) for differentiation between convulsive epileptic and psychogenic nonepileptic seizures (PNESs). Forty-four consecutive episodes with convulsive events were automatically analyzed with the algorithm: 25 generalized tonic-clonic seizures (GTCSs) from 11 patients, and 19 episodes of convulsive PNES from 13 patients. The gold standard was the interpretation of the video-electroencephalographic recordings by experts blinded to the EMG results. The algorithm correctly classified 24 GTCSs (96%) and 18 PNESs (95%). The overall diagnostic accuracy was 95%. This algorithm is useful for distinguishing between epileptic and psychogenic convulsive seizures.
Medical subject headings
- Algorithms
- Electroencephalography
- Seizures
- Video Recording