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Classification and comparative analysis of psychogenic nonepileptic seizures (PNES) semiology based on
Divyani Garg1, Ayush Agarwal2, Varun Malhotra1
1Department of Neurology, All India Institute of Medical Sciences, New Delhi, India.
Background:
Multiple classification systems for psychogenic nonepileptic seizures (PNES) based on semiological features have been described. We sought to compare the efficiency of four PNES classification systems.
Methods:
We retrospectively analyzed medical and video-electroencephalography (VEEG) records of patients with PNES with at least one typical event recorded on VEEG. Semiology of PNES events was stringently classified using Hubsch, Dhiman, Wadwekar, and Asadi-Pooya's classification systems.
Results:
We studied 248 patients with PNES (78% females, mean age 23.1 ± 10.3 years) and reviewed 498 PNES events. Using Hubsch's scheme, we classified events into: dystonic attacks with primitive gestural activity (5.2%), paucikinetic attacks with preserved responsiveness (9.7%), pseudosyncope (59.8%), hyperkinetic prolonged attacks (16.2%) and axial dystonic prolonged attacks (1.6%), and unclassified (7.5%). Using Dhiman's classification, events were: abnormal motor (hypermotor [10.4%]/ partial motor [12.7%]), dialeptic type (58.6%), mixed patterns (17.3%), and unclassified (1%). Using Wadwekar's classification: dystonic attacks with primitive gestural activity (5.2%), paucikinetic attacks with preserved responsiveness (9.6%), pseudosyncope with/without hyperventilation (65.1%), hyperkinetic prolonged attacks involving limbs ± trunk (18.5%), and axial dystonic prolonged attacks (1.6%). Using Asadi-Pooya's classification, events were: hypermotor (30.1%), non-motor (62.9%), and mixed (7.0%). All events could be classified via Wadwekar and Asadi-Pooya systems.
Conclusion:
In our study, pseudosyncope/dialeptic/non-motor semiology emerged as most frequent. Most of our patients with PNES had stereotyped semiology. All events could be classified using the schemes by Asadi-Pooya and Wadweker et al. Dhiman et al. scheme could classify 99% and 7.5% remained unclassified using Hubsch et al. scheme.
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