Dataset Information

The Personality Assessment Inventory as a tool for diagnosing psychogenic nonepileptic seizures.

ABSTRACT: Using 184 subjects with valid personality assessment interview (PAI) profiles and video-electroencephalography (VEEG)-confirmed diagnoses of epileptic seizures (ES; n = 109) or psychogenic nonepileptic seizures (PNES; n = 75), we present the diagnostic test performance of the PAI PNES Indicator and other PAI scales when used to differentiate PNES from ES. Subjects with PNES reported significantly higher somatic, conversion, depressed, anxious, and suicidal symptoms. As a diagnostic tool, the PNES Indicator does not add additional accuracy beyond the conversion subscale (SOM-C). The somatization (SOM-S) and physiological depression (DEP-P) subscales perform as well as the SOM-C subscale. The SOM-C scale (cut point > or =70) was 58.7% sensitive and 83.5% specific at diagnosing PNES. Assuming a 30% prevalence of PNES, the SOM-C scale has a positive predictive value (PPV) of 60.4% and negative predictive value (NPV) of 82.5%. Overall, the PAI SOM-C subscale does not appear more accurate than other psychometric tests used to differentiate PNES from ES.

SUBMITTER: Thompson AW

PROVIDER: S-EPMC2844915 | biostudies-other | 2010 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

The Personality Assessment Inventory as a tool for diagnosing psychogenic nonepileptic seizures.

Thompson Alexander W AW Hantke Nathan N Phatak Vaishali V Chaytor Naomi N

Epilepsia 20090601 1

Using 184 subjects with valid personality assessment interview (PAI) profiles and video-electroencephalography (VEEG)-confirmed diagnoses of epileptic seizures (ES; n = 109) or psychogenic nonepileptic seizures (PNES; n = 75), we present the diagnostic test performance of the PAI PNES Indicator and other PAI scales when used to differentiate PNES from ES. Subjects with PNES reported significantly higher somatic, conversion, depressed, anxious, and suicidal symptoms. As a diagnostic tool, the PNE ...[more]

PMID: 19490032

Similar Datasets

Project description:ObjectiveLow-cost evidence-based tools are needed to facilitate the early identification of patients with possible psychogenic nonepileptic seizures (PNES). Prior to accurate diagnosis, patients with PNES do not receive interventions that address the cause of their seizures and therefore incur high medical costs and disability due to an uncontrolled seizure disorder. Both seizures and comorbidities may contribute to this high cost.MethodsBased on data from 1,365 adult patients with video-electroencephalography-confirmed diagnoses from a single center, we used logistic and Poisson regression to compare the total number of comorbidities, number of medications, and presence of specific comorbidities in five mutually exclusive groups of diagnoses: epileptic seizures (ES) only, PNES only, mixed PNES and ES, physiologic nonepileptic seizurelike events, and inconclusive monitoring. To determine the diagnostic utility of comorbid diagnoses and medication history to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and age, trained using a retrospective database and validated using a prospective database.ResultsOur model differentiated PNES only from ES only with a prospective accuracy of 78% (95% confidence interval =72-84%) and area under the curve of 79%. With a few exceptions, the number of comorbidities and medications was more predictive than a specific comorbidity. Comorbidities associated with PNES were asthma, chronic pain, and migraines (p < 0.01). Comorbidities associated with ES were diabetes mellitus and nonmetastatic neoplasm (p < 0.01). The population-level analysis suggested that patients with mixed PNES and ES may be a population distinct from patients with either condition alone.SignificanceAn accurate patient-reported medical history and medication history can be useful when screening for possible PNES. Our prospectively validated and objective score may assist in the interpretation of the medication and medical history in the context of the seizure description and history.

Project description:ObjectiveEarly and accurate diagnosis of patients with psychogenic nonepileptic seizures (PNES) leads to appropriate treatment and improves long-term seizure prognosis. However, this is complicated by the need to record seizures to make a definitive diagnosis. Suspicion for PNES can be raised through knowledge that patients with PNES have increased somatic sensitivity and report more positive complaints on review-of-systems questionnaires (RoSQs) than patients with epileptic seizures. If the responses on the RoSQ can differentiate PNES from other seizure types, then these forms could be an early screening tool.MethodsOur dataset included all patients admitted from January 2006 to June 2016 for video-electroencephalography at UCLA. RoSQs prior to May 2015 were acquired through retrospective chart review (n=405), whereas RoSQs from subsequent patients were acquired prospectively (n=190). Controlling for sex and number of comorbidities, we used binomial regression to compare the total number of symptoms and the frequency of specific symptoms between five mutually exclusive groups of patients: epileptic seizures (ES), PNES, physiologic nonepileptic seizure-like events (PSLE), mixed PNES plus ES, and inconclusive monitoring. To determine the diagnostic utility of RoSQs to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and the number of medical comorbidities.ResultsOn average, patients with PNES or mixed PNES and ES reported more than twice as many symptoms than patients with isolated ES or PSLE (p<0.001). The prospective accuracy to differentiate PNES from ES was not significantly higher than naïve assumption that all patients had ES (76% vs 70%, p>0.1).DiscussionThis analysis of RoSQs confirms that patients with PNES with and without comorbid ES report more symptoms on a population level than patients with epilepsy or PSLE. While these differences help describe the population of patients with PNES, the consistency of RoSQ responses was neither accurate nor specific enough to be used solely as an early screening tool for PNES. Our results suggest that the RoSQ may help differentiate PNES from ES only when, based on other information, the pre-test probability of PNES is at least 50%.

Dataset Information

The Personality Assessment Inventory as a tool for diagnosing psychogenic nonepileptic seizures.

Publications

The Personality Assessment Inventory as a tool for diagnosing psychogenic nonepileptic seizures.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets