A systematic study of stereotypy in epileptic seizures versus psychogenic seizure-like events

Vogrig, Alberto; Hsiang, Jen Chun; Ng, Jacqueline K.; Rolnick, Joshua; Cheng, Jessica; Parvizi, Josef

doi:10.1016/j.yebeh.2018.11.030

Cited by 15 publications

(16 citation statements)

References 26 publications

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“…Absent postictal deep, heavy breathing (stertor) and ictal eye closure, however, are both highly specific and relatively sensitive findings [ 22 – 26 , 28 ]. A fluctuating course is both specific and sensitive for PNES [ 11 , 21 , 23 ], as confirmed in this study, with comparable value to ictal eye closure and absent postictal stertor. It is a sign relatively easy to appreciate in a video even with suboptimal resolution.…”

Section: Discussionsupporting

confidence: 79%

“…Logistic regression correctly classified 85.18% of patients based on this finding alone. Fluctuating or discontinuous ictal motor manifestations have been previously demonstrated to have high specificity for PNES; there is also a relatively high sensitivity in comparison to other semiological features [ 11 , 23 , 26 ], particularly where there are two or more pauses during an event (Table 3 ) [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

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Predictive semiology of psychogenic non-epileptic seizures in an epilepsy monitoring unit

et al. 2021

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Introduction The diagnosis of psychogenic nonepileptic seizures (PNES) is a common clinical dilemma. We sought to assess the diagnostic value of four ictal signs commonly used in differentiating PNES from epileptic seizures (ES). Methods We retrospectively reviewed consecutive adult video-electroencephalogram (VEM) studies conducted at a single tertiary epilepsy center between May 2009 and August 2016. Each event was assessed by a blinded rater for the presence of four signs: fluctuating course, head shaking, hip thrusting, and back arching. The final diagnosis of PNES or ES was established for each event based on clinical and VEM characteristics. All ES were pooled regardless of focal or generalized onset. We analyzed the odds ratio of each sign in PNES in comparison to ES with adjustment for repeated measures using logistic regression. Additionally, we calculated the sensitivity, specificity, predictive values, and likelihood ratios of each sign to diagnose PNES. Results A total of 742 events from 140 VEM studies were assessed. Fluctuating course (odds ratio (OR) 37.37, 95% confidence interval (CI) 13.56–102.96, P < 0.0001), head shaking (OR 2.95, 95% CI 1.26–6.79, P = 0.012), and hip thrusting (OR 4.28, 95% CI 1.21–15.18, P = 0.02) were each significantly predictive of PNES. Fluctuating course had the highest sensitivity (76.16%). Back arching (OR 1.06, 95% CI 0.35–3.20, P = 0.92) was not significantly associated with PNES. Conclusion Fluctuating course, head shaking, and hip thrusting are semiological features significantly more common in PNES than ES. Fluctuating course is the most reliable sign. Back arching does not appear to differentiate PNES from ES.

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Section: Discussionsupporting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Predictive semiology of psychogenic non-epileptic seizures in an epilepsy monitoring unit

et al. 2021

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“…Likewise, patients with visual auras are thought to have occipital seizures affecting the visual network, and those with emotional auras are thought to have seizures involving limbic regions. Interestingly, seizure behavior or subjective reports respect a high degree of stereotypy in a given patient or across patients with similar epilepsies (26).…”

Section: Significancementioning

confidence: 99%

Altered sense of self during seizures in the posteromedial cortex

Parvizi

Braga

Kucyi

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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The posteromedial cortex (PMC) is known to be a core node of the default mode network. Given its anatomical location and blood supply pattern, the effects of targeted disruption of this part of the brain are largely unknown. Here, we report a rare case of a patient (S19_137) with confirmed seizures originating within the PMC. Intracranial recordings confirmed the onset of seizures in the right dorsal posterior cingulate cortex, adjacent to the marginal sulcus, likely corresponding to Brodmann area 31. Upon the onset of seizures, the patient reported a reproducible sense of self-dissociation—a condition he described as a distorted awareness of the position of his body in space and feeling as if he had temporarily become an outside observer to his own thoughts, his “me” having become a separate entity that was listening to different parts of his brain speak to each other. Importantly, 50-Hz electrical stimulation of the seizure zone and a homotopical region within the contralateral PMC induced a subjectively similar state, reproducibly. We supplement our clinical findings with the definition of the patient’s network anatomy at sites of interest using cortico-cortical–evoked potentials, experimental and resting-state electrophysiological connectivity, and individual-level functional imaging. This rare case of patient S19_137 highlights the potential causal importance of the PMC for integrating self-referential information and provides clues for future mechanistic studies of self-dissociation in neuropsychiatric populations.

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“…Eye closure during the ictal episode has been shown to be highly sensitive and specific for PNES (96.2 and 98.1% respectively) (7,8). PNES are generally significantly longer then epileptic events (9), and a seizure length of over 5 min makes an event 24 times more likely to be PNES (10). Fully controlled falling and resistance to eye opening are also suggestive of PNES (11).…”

Section: Semiologic Extrapolation In Dsmentioning

confidence: 99%

Digital Semiology: A Prototype for Standardized, Computer-Based Semiologic Encoding of Seizures

et al. 2021

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Video-EEG monitoring (VEM) is imperative in seizure classification and presurgical assessment of epilepsy patients. Analysis of VEM is currently performed in most institutions using a freeform report, a time-consuming process resulting in a non-standardized report, limiting the use of this essential diagnostic tool. Herein we present a pilot feasibility study of our experience with “Digital Semiology” (DS), a novel seizure encoding software. It allows semiautomated annotation of the videos of suspected events from a predetermined, hierarchal set of options, with highly detailed semiologic descriptions, somatic localization, and timing. In addition, the software's semiologic extrapolation functions identify characteristics of focal seizures and PNES, sequences compatible with a Jacksonian march, and risk factors for SUDEP. Sixty episodes from a mixed adult and pediatric cohort from one level 4 epilepsy center VEM archives were analyzed using DS and the reports were compared with the standard freeform ones, written by the same epileptologists. The behavioral characteristics appearing in the DS and freeform reports overlapped by 78–80%. Encoding of one episode using DS required an average of 18 min 13 s (standard deviation: 14 min and 16 s). The focality function identified 19 out of 43 focal episodes, with a sensitivity of 45.45% (CI 30.39–61.15%) and specificity of 87.50% (CI 61.65–98.45%). The PNES function identified 6 of 12 PNES episodes, with a sensitivity of 50% (95% CI 21.09–78.91%) and specificity of 97.2 (95% CI 88.93–99.95%). Eleven events of GTCS triggered the SUDEP risk alert. Overall, these results show that video recordings of suspected seizures can be encoded using the DS software in a precise manner, offering the added benefit of semiologic alerts. The present study represents an important step toward the formation of an annotated video archive, to be used for machine learning purposes. This will further the goal of automated VEM analysis, ultimately contributing to wider utilization of VEM and therefore to the reduction of the treatment gap in epilepsy.

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A systematic study of stereotypy in epileptic seizures versus psychogenic seizure-like events

Cited by 15 publications

References 26 publications

Predictive semiology of psychogenic non-epileptic seizures in an epilepsy monitoring unit

Predictive semiology of psychogenic non-epileptic seizures in an epilepsy monitoring unit

Altered sense of self during seizures in the posteromedial cortex

Digital Semiology: A Prototype for Standardized, Computer-Based Semiologic Encoding of Seizures

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