Is patient acceptance of the diagnosis of psychogenic nonepileptic seizures linked to symptomatology?

Is patient acceptance of the diagnosis of functional (psychogenic nonepileptic) seizures linked to their clinical characteristics?

PURPOSE

We investigated the rate of acceptance of functional seizures (FS) or psychogenic nonepileptic seizures (PNES) diagnosis in a cross-sectional study in a cohort from Iran. We hypothesized that the acceptance of FS diagnosis has association with clinical characteristics of the patients.

METHODS

In this cross-sectional study, all patients with FS, who were diagnosed at Shiraz Comprehensive Epilepsy Center, Iran, from 2008 until 2018, were investigated. In a phone call interview in February 2020, we obtained the following information: whether they have accepted the diagnosis that was delivered to them; what is their seizure outcome (seizure-free during the past 12 months or not).

RESULTS

100 patients participated; at the time of the follow-up call, 74 (74%) patients expressed that they have accepted the diagnosis of FS. At the follow-up call, 48 patients (48%) were seizure-free and 52 patients (52%) were suffering from FS yet; 34 of seizure-free patients (71%) and 40 of those patients who still had seizures (77%) expressed that they have accepted the diagnosis of FS (p = .504; Fisher's exact test). Patients' characteristics and seizure semiology were not associated with the acceptance of the diagnosis of FS.

CONCLUSION

That the majority of patients with FS accept their diagnosis if it is delivered to them appropriately, and demographic and clinical characteristics of the patients do not have associations with this.

Skin conductance response and emotional response in women with psychogenic non-epileptic seizures

PURPOSE

Recent etiopathogenic models place emotional dysregulation at the core of psychogenic nonepileptic seizure (PNES). Our purpose was to assess physiological, cognitive, and behavioral emotional responses of PNES patients.

METHODS

This study compared three types of emotional responses to visual emotional stimuli between 34 female PNES group and 34 matched healthy controls: physiological response measured by skin conductance response (SCR) (rate, amplitude and latency) and heart rate deceleration; cognitive response measured by valence and arousal elicited by the images; and behavioural response measured by latency of ratings. The groups were characterized on psychiatric comorbidities, traumatic history, alexithymia, and dissociation.

RESULTS

Compared to controls, PNES group displayed lower SCR for all images (p = 0.038), shorter amplitude of heart rate deceleration (p = 0.024) and faster arousal rating for all images (p = 0.019), but no difference on cognitive rating of images. Within-groups analyses showed only in PNES subjects increased rate (+19.35%, p = 0.046) SCR for negative stimuli with strong arousal compared to negative with low arousal. PNES physiological response (SCR and heart rate deceleration) was negatively correlated to dissociation tendency (r=-0.48, p = 0.0083) and alexithymia (r=-0.44, p = 0.012)). For cognitive response, no correlation was found.

CONCLUSION

These results are in favour of a lower physiological emotional response but with an over-reactivity at behavioral level contrasting with similar cognitive assessment. For strong aversive stimuli, PNES might present a trend to overreact at physiological and behavioural levels. Our results suggest that dissociation and difficulty in describing feelings are associated with an altered physiological response in PNES women only.

Near-infrared spectroscopy in evaluating psychogenic pseudosyncope-a novel diagnostic approach

BACKGROUND

Psychogenic pseudosyncope (PPS), a conversion disorder and syncope mimic, accounts for a large proportion of 'unexplained syncope'. PPS is diagnosed by reproduction of patients' symptoms during head-up tilt (HUT). Electroencephalogram (EEG), a time consuming and resource intensive technology, is used during HUT to demonstrate absence of cerebral hypoperfusion during transient loss of consciousness (TLOC). Near-infrared spectroscopy (NIRS) is a simple, non-invasive technology for continuous monitoring of cerebral perfusion. We present a series of patients for whom PPS diagnosis was supported by NIRS during HUT.

METHODS

Eight consecutive patients with suspected PPS referred to a syncope unit underwent evaluation. During HUT, continuous beat-to-beat blood pressure (BP), heart rate (HR) and NIRS-derived tissue saturation index (TSI) were measured. BP, HR and TSI at baseline, time of first symptom, presyncope and apparent TLOC were measured. Patients were given feedback and followed for symptom recurrence.

RESULTS

Eight predominantly female patients (6/8, 75%) aged 31 years (16-54) were studied with (5/8, 63%) having comorbid psychiatric diagnoses, and (5/8, 63%) presenting with frequent episodes of prolonged TLOC with eyes closed (6/8, 75%). All patients experienced reproduction of typical events during HUT. Systolic BP (mmHg) increased from baseline (129.7 (interquartile range [IQR] 124.9-133.4)) at TLOC (153.0 (IQR 146.7-159.0)) (P-value = 0.012). HR (bpm) increased from baseline 78 (IQR 68.6-90.0) to 115.7 (IQR 93.5-127.9) (P-value = 0.012). TSI (%) remained stable throughout, 71.4 (IQR 67.5-72.9) at baseline vs. 71.0 (IQR 68.2-73.0) at TLOC (P-value = 0.484).

CONCLUSIONS

NIRS provides a non-invasive surrogate of cerebral perfusion during HUT. We propose HUT incorporating NIRS monitoring in the diagnostic algorithm for patients with suspected PPS.

A test of the adaptive network explanation of functional disorders using a machine learning analysis of symptoms

The classification and etiology of functional disorders is controversial. Evidence supports both psychological and biological (disease) models that show, respectively, that functional disorders should be classified as one (bodily distress syndrome) and many (e.g., irritable bowel syndrome (IBS), fibromyalgia syndrome (FMS), and chronic fatigue syndrome (CFS)). Two network models (symptom network and adaptive network) can explain the specificity and covariation of symptomatology, but only the adaptive network model can explain the covariation of the somatic symptoms of functional disorders. The adaptive network model is based on the premise that a network of biological mechanisms has emergent properties and can exhibit adaptation. The purpose of this study was to test the predictions that symptom similarity increases with pathology and that network connection strengths vary with pathology, as this would be consistent with the notion that functional disorder pathology arises from network adaptation. We conducted a symptom internet survey followed by machine learning analysis. Participants were 1751 people reporting IBS, FMS or CFS diagnosis who completed a 61-item symptom questionnaire. Eleven symptom clusters were identified. Differences in symptom clusters between IBS, FMS and CFS groups decreased as overall symptom frequency increased. The strength of outgoing connections between clusters varied as a function of symptom frequency and single versus multiple diagnoses. The findings suggest that the pathology of functional disorders involves an increase in the activity and causal connections between several symptom causing mechanisms. The data provide support for the proposal that the body is capable of complex adaptation and that functional disorders result when rules that normally improve adaptation create maladaptive change.

Clinical Approaches to Psychogenic Nonepileptic Seizures

Psychogenic nonepileptic seizures (PNES) are a subtype of conversion disorder (also called functional neurological symptom disorder in DSM-5). Patients with PNES are high utilizers of health care and can have disability levels similar to those of patients with epilepsy. PNES is a common, complex neuropsychiatric somatoform disorder at the interface of neurology and psychiatry disciplines and is largely overlooked and avoided by mental health providers. Despite advances in establishing accurate diagnosis and evidence-based treatments, recent knowledge about PNES has not been well translated into clinical practice. Long diagnostic delays have been associated with poor prognosis. Recent advances in possible neurophysiological biomarkers include functional MRI studies that show abnormalities in emotional, cognitive, executive, and sensorimotor neurocircuits. Although the gold standard for diagnosis is video electroencephalograph, this test is underused by psychiatrists. The International League Against Epilepsy proposed a staged approach to PNES diagnosis using history, semiologic features, and EEG. Thorough psychiatric assessment can identify relevant biopsychosocial and predisposing, precipitating, and perpetuating factors, as well as assess the comorbid psychiatric disorders, which can inform a treatment plan. Clear and thoughtful delivery of diagnosis is the first step in treatment. Regular follow-up with the patient's neurologist, in addition to treatment by mental health professionals familiar with somatic symptom disorders, is recommended. Psychotherapy is the mainstay of treatment, and randomized clinical trials using cognitive-behavioral therapies reveal significant reduction in seizures and other psychiatric symptoms. After centuries, mental health providers now have access to the tools to diagnose and effectively treat PNES and other conversion disorders.

Explaining unexplained pain to fibromyalgia patients: finding a narrative that is acceptable to patients and provides a rationale for evidence based interventions

As the cause of fibromyalgia is controversial, communicating with patients can be challenging, particularly if the patient adopts the narrative 'I am damaged and so I need a more powerful pain killer'. Research shows that providing patients with alternative narratives can be helpful, but it remains unclear what particular narratives are most acceptable to patients and at the same time provide a rationale for evidence based psychological and exercise interventions. This article described the development of a new narrative and the written comments made about the narrative by fibromyalgia patients. The narrative derives from a complexity theory model and provides an alternative to biogenic and psychogenic models. The model was presented to 15 patients whose comments about comprehensibility led to the final format of the narrative. In the final form, the body is presented as 'a very, very clever computer' where fibromyalgia is caused by a software rather than a hardware problem. The software problem is caused by the body adapting when people have to 'keep going' despite 'stop signals', such as pain and fatigue. The narrative provides a rationale for engaging in psychological and exercise interventions as a way of correcting the body's software. This way of explaining fibromyalgia was evaluated by a further 25 patients attending a 7-week 'body reprogramming' intervention, where the therapy was presented as correcting the body's software, and included both exercise and psychological components. Attendance at the course was 85%. Thematic analysis of written patient feedback collected after each session showed that patients found the model believable and informative, it provided hope and was empowering. Patients also indicated that they had started to implement lifestyle change with perceived benefit. Fibromyalgia patients appear to respond positively to a technology-derived narrative based on the analogy of the body as a computer.