Stereotypy of psychogenic nonepileptic seizures

Functional seizures: Are they consistent over time?

BACKGROUND

Our previous study showed that functional seizures (FS) are consistent in the same patient during a single video EEG monitoring (VEEG). This study aimed to check whether FS remains consistent across VEEG sessions even after several years.

METHODS

The study evaluated the consistency of FS across different VEEG sessions using five criteria: FS type, the main anatomical region involved (specifically, the body part most affected during the seizure), other involved anatomical regions, frequency of movements, and duration of FS. Consistency levels were categorized as low (one consistent axis), moderate (two consistent axes), and high (three or more consistent axes).

RESULTS

Fourteen patients were included in the final analysis. The mean time between monitoring was 3.8 ± 2.5 years (0.5-8 year). In 13 of 14 patients, the first and second monitoring events were classified into the same FS category. There was consistency in the main anatomical region involved in 9 out of 12 patients with motor FS. In 9 out of 12 patients with motor FS, the other anatomical regions involved were consistent in both sessions. The mean duration of the FS between sessions was inconsistent in most of the patients. Ten patients were classified with high consistency, one patient with moderate consistency, two patients with low consistency, and in one patient, the events were classified as inconsistent.

CONCLUSIONS

Our results show that FS tends to remain consistent in a single patient even after several years, and there is probably no correlation between the degree of consistency and the time between VEEG sessions. These findings have implications for supporting the concept of FS as a consistent phenomenon. Additionally, they may suggest potential avenues for future research to elucidate the origins of FS. Subsequent studies are essential to validate and expand upon these preliminary observations.

Psychogenic nonepileptic seizures: Are they a freeze reaction?

Psychogenic nonepileptic seizures (PNES) clinically resemble epileptic seizures (ES) but lack epileptic activity at the time of the seizure and are also not due to any other pathophysiological disorder. The integrative cognitive model (ICM) suggests that PNES is an automatic reaction generated from distorted memory and is perceived as uncontrollable and unwanted. Furthermore, the ICM model implies that a PNES event occurs due to an external or internal cue. Intrigued by this assumption, we wanted to examine why a PNES event occurs at a particular moment by investigating the pre-ictal behavior. This study is a retrospective study. We included all patients diagnosed with PNES or ES admitted to our long-term video-EEG monitoring unit (LTVEM) between 01/01/2018 and 30/08/2020. Using thorough video analysis, we checked the patient's state at the onset of the event and looked back to see what the patient was doing before the event onset. We defined 4 types of pre-ictal behavior A. Inactivity. B. Environment arrangement c. Other. D. No apparent pre-ictal behavior. Thirty patients with PNES and 30 patients with ES were included in the study. In total, 46 PNES events and 56 ES events were recorded and analyzed. In 33 /46 PNES seizures (72%), a type A, A + B or C pre-ictal behavior was observed compared to 1/56 ES (1.78%) with type A pre-ictal behavior. All other pre-ictal behavior in the ES group were of type D. Patients with PNES have a unique pre-ictal behavior before most PNES events with motor manifestations. Since the pre-ictal behavior consists mainly of inactivity, we believe it may imply that PNES represents a freeze reaction or a reconstruction of a freeze reaction.

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

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.

Classification and comparative analysis of psychogenic nonepileptic seizures (PNES) semiology based on video-electroencephalography (VEEG)

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.

Differential Semiology Based on Video Electroencephalography Monitoring Between Psychogenic Nonepileptic Seizures and Temporal Lobe Epileptic Seizures

BACKGROUND

Psychogenic nonepileptic seizures (PNESs) are disruptive changes in behavior without ictal correlate of epileptic activity and high prevalence of psychiatric morbidity. Differential diagnosis is difficult particularly with temporal lobe epilepsy (TLE), which is also associated with high prevalence of psychiatric comorbidity. Although video electroencephalography is the gold standard for differential diagnosis, clinical semiology analysis may help the clinician in general medical practice.

OBJECTIVE

In this study, the differential semiology, based on video electroencephalography, between PNESs and TLE seizures was analyzed.

METHODS

The video electroencephalography of patients with diagnosis of PNES and TLE were reviewed and compared between groups. Clinical semiology of all episodes recorded by video electroencephalography in each patient was analyzed and classified in accordance with the presence of behavioral arrest, motor hyperkinetic activity, impaired awareness, aura, and automatisms. Chi square test and binary logistic regression were determined.

RESULTS

Thirty-two patients with PNES (32 ± 11 y) and 34 with TLE (32 ± 12 y) were included. Female patients were predominant in the PNES group (P < 0.05). Mean time duration of episodes was 6.8 ± 10 minutes in PNES and 1.6 ± 0.8 minutes in TLE (P < 0.05). Impaired awareness (odds ratio = 24.4; 95% confidence interval = 3.79 -157.3, P < 0.01), automatisms (odds ratio = 13.9; 95% confidence interval = 2.1- 90.5, P < 0.01), and shorter duration of the events (odds ratio = 2.261, 95% confidence interval = 1.149 - 4.449, P = 0.018) were found as independent factors for detecting TLE seizures comparing PNESs.

CONCLUSION

Clinical semiology analysis may orientate the differential diagnosis in general medical practice, between PNESs and TLE seizures. Further studies comparing PNES semiology with other subtypes of epilepsies may complete these preliminary findings.

Reliability of reported peri-ictal behavior to identify psychogenic nonepileptic seizures

PURPOSE

Differentiating psychogenic non-epileptic seizures (PNES) from epileptic seizures (ES) can be difficult, even when expert clinicians have video recordings of seizures. Moreover, witnesses who are not trained observers may provide descriptions that differ from the expert clinicians', which often raises concern about whether the patient has both ES and PNES. As such, quantitative, evidence-based tools to help differentiate ES from PNES based on patients' and witnesses' descriptions of seizures may assist in the early, accurate diagnosis of patients.

METHODS

Based on patient- and observer-reported data from 1372 patients with diagnoses documented by video-elect roencephalography (vEEG), we used logistic regression (LR) to compare specific peri-ictal behaviors and seizure triggers in five mutually exclusive groups: ES, PNES, physiologic non-epileptic seizure-like events, mixed PNES plus ES, and inconclusive monitoring. To differentiate PNES-only from ES-only, we retrospectively trained multivariate LR and a forest of decision trees (DF) to predict the documented diagnoses of 246 prospective patients.

RESULTS

The areas under the receiver operating characteristic curve (AUCs) of the DF and LR were 75% and 74%, respectively (empiric 95% CI of chance 37-62%). The overall accuracy was not significantly higher than the naïve assumption that all patients have ES (accuracy DF 71%, LR 70%, naïve 68%, p > 0.05).

CONCLUSIONS

Quantitative analysis of patient- and observer-reported peri-ictal behaviors objectively changed the likelihood that a patient's seizures were psychogenic, but these reports were not reliable enough to be diagnostic in isolation. Instead, our scores may identify patients with "probable" PNES that, in the right clinical context, may warrant further diagnostic assessment.

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

OBJECTIVE

The objective of this study was to quantify the features of stereotypy in epileptic seizures and compare it with that of stereotypy in psychogenic nonepileptic seizure-like events (PNES) confirmed by video-electroencephalography (VEEG) monitoring.

METHODS

Video-electroencephalography monitoring records of 20 patients with temporal lobe seizures (TLS) and 20 with PNES were retrospectively reviewed (n = 138 seizures, 48 TLS and 90 PNES). We analyzed the semiology of 59 behaviors of interest for their presence, duration, sequence, and continuity using quantified measures that were entered into statistical analysis.

RESULTS

We identified discontinuity as the parameter that was clearly distinct between PNES and epileptic TLS events: there were significantly more frequent pauses of behavior (i.e., "on-off" pattern) in PNES compared with TLS (P = 0.012). The frequency of pauses during an event was diagnostic of PNES events. For instance, the presence of 2 "pauses" during an episode determines a 69% probability of the seizure being nonepileptic. Moreover, PNES events had significantly greater duration (143 s) than TLS events (68 s) (excluding outliers, P = 0.002) and greater duration variability from one event to another in the same subject (P = 0.005).

SIGNIFICANCE

Our work provides the first quantified measure of behavioral semiology during epileptic and nonepileptic seizures and offers novel behavioral measures to differentiate them from each other.

Semiological characteristics of patients with psychogenic nonepileptic seizures: Gender-related differences

Psychogenic nonepileptic seizures (PNES) are more prevalent among women, and diagnosis may sometimes be delayed by as much as seven years. Understanding the effect of gender on the presentation of a PNES may assist with diagnosis based on semiological details in the clinical setting. Although video-EEG monitoring (VEM) is the gold standard for diagnosing PNES, determining gender-related seizure semiology through careful history may prevent diagnostic delay while waiting for VEM. The aim of this study was to investigate gender-related differences in the semiology of PNES. Patients, all aged at least 16 years, diagnosed with PNES following VEM between December 2005 and November 2016 were included in this study. All patients' medical records and video-EEG-documented PNES were reviewed, and the presence or absence of semiological signs was recorded for each documented attack. Demographic features and semiological signs of PNES were compared between female and male patients. Forty-one patients (31 females, 10 males) aged 27.2 ± 12.2 years (range: 16-65) were included in the study. Mean age at onset of PNES was higher for female patients than males, at 24.3 ± 11.5 versus 17.5 ± 3.2 years (p = 0.005). The median duration of PNES was longer for female patients than males, at 10 min (range: 5 s-120 min) versus 2 min (range: 10 s-60 min) (p = 0.016). The most common symptom was forced eye closure in both genders. No significant gender-specific differences were observed in terms of the type or semiology of PNES. Although there are no major gender-related differences in PNES semiology, our findings highlight the importance of greater caution, especially in male patients, when diagnosing PNES, remembering that onset may also occur at young ages and that a short seizure duration does not exclude PNES.