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Validation of a predictive calculator to distinguish between patients presenting with dissociative versus epileptic seizures.

ABSTRACT: Dissociative seizures (also known as psychogenic nonepileptic seizures) are a common functional neurological disorder that can be difficult to distinguish from epileptic seizures. Patients with dissociative seizures provide diagnostic challenges, leading to delays in care, inappropriate care, and significant healthcare utilization and associated costs. The dissociative seizure likelihood score (DSLS) was developed by Kerr and colleagues at UCLA to distinguish between patients with epileptic seizures and dissociative seizures based on clinical and medication history as well as features of seizure semiology. We validated this calculator at the University of Colorado, which is a Level 4 National Association of Epilepsy Center. The DSLS accurately predicted the diagnosis in 81% of patients, despite local variability in the factors associated with epileptic versus dissociative seizures between the two populations. The DSLS can be a useful tool to assist with history taking and may have important utility for clinical decision making with these difficult to distinguish patient populations.

SUBMITTER: Lenio S

PROVIDER: S-EPMC7951947 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Validation of a predictive calculator to distinguish between patients presenting with dissociative versus epileptic seizures.

Lenio Steven S Kerr Wesley T WT Watson Meagan M Baker Sarah S Bush Chad C Rajic Alex A Strom Laura L

Epilepsy & behavior : E&B 20210202

Dissociative seizures (also known as psychogenic nonepileptic seizures) are a common functional neurological disorder that can be difficult to distinguish from epileptic seizures. Patients with dissociative seizures provide diagnostic challenges, leading to delays in care, inappropriate care, and significant healthcare utilization and associated costs. The dissociative seizure likelihood score (DSLS) was developed by Kerr and colleagues at UCLA to distinguish between patients with epileptic seiz ...[more]

PMID: 33545649

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Project description:ImportanceMisdiagnosis of epilepsy is common. Video electroencephalogram provides a definitive diagnosis but is impractical for many patients referred for evaluation of epilepsy.ObjectiveTo evaluate the accuracy of outpatient smartphone videos in epilepsy.Design, setting, and participantsThis prospective, masked, diagnostic accuracy study (the OSmartViE study) took place between August 31, 2015, and August 31, 2018, at 8 academic epilepsy centers in the United States and included a convenience sample of 44 nonconsecutive outpatients who volunteered a smartphone video during evaluation and subsequently underwent video electroencephalogram monitoring. Three epileptologists uploaded videos for physicians from the 8 epilepsy centers to review.Main outcomes and measuresMeasures of performance (accuracy, sensitivity, specificity, positive predictive value, and negative predictive value) for smartphone video-based diagnosis by experts and trainees (the index test) were compared with those for history and physical examination and video electroencephalogram monitoring (the reference standard).ResultsForty-four eligible epilepsy clinic outpatients (31 women [70.5%]; mean [range] age, 45.1 [20-82] years) submitted smartphone videos (530 total physician reviews). Final video electroencephalogram diagnoses included 11 epileptic seizures, 30 psychogenic nonepileptic attacks, and 3 physiologic nonepileptic events. Expert interpretation of a smartphone video was accurate in predicting a video electroencephalogram monitoring diagnosis of epileptic seizures 89.1% (95% CI, 84.2%-92.9%) of the time, with a specificity of 93.3% (95% CI, 88.3%-96.6%). Resident responses were less accurate for all metrics involving epileptic seizures and psychogenic nonepileptic attacks, despite greater confidence. Motor signs during events increased accuracy. One-fourth of the smartphone videos were correctly diagnosed by 100% of the reviewing physicians, composed solely of psychogenic attacks. When histories and physical examination results were combined with smartphone videos, correct diagnoses rose from 78.6% to 95.2%. The odds of receiving a correct diagnosis were 5.45 times greater using smartphone video alongside patient history and physical examination results than with history and physical examination alone (95% CI, 1.01-54.3; P = .02).Conclusions and relevanceOutpatient smartphone video review by experts has predictive and additive value for diagnosing epileptic seizures. Smartphone videos may reliably aid psychogenic nonepileptic attacks diagnosis for some people.

Project description:BackgroundThe evidence base for the effectiveness of psychological interventions for patients with dissociative non-epileptic seizures (DS) is currently extremely limited, although data from two small pilot randomised controlled trials (RCTs), including from our group, suggest that Cognitive Behavioural Therapy (CBT) may be effective in reducing DS occurrence and may improve aspects of psychological status and psychosocial functioning.Methods/designThe study is a multicentre, pragmatic parallel group RCT to evaluate the clinical and cost-effectiveness of specifically-tailored CBT plus standardised medical care (SMC) vs SMC alone in reducing DS frequency and improving psychological and health-related outcomes. In the initial screening phase, patients with DS will receive their diagnosis from a neurologist/epilepsy specialist. If patients are eligible and interested following the provision of study information and a booklet about DS, they will consent to provide demographic information and fortnightly data about their seizures, and agree to see a psychiatrist three months later. We aim to recruit ~500 patients to this screening stage. After a review three months later by a psychiatrist, those patients who have continued to have DS in the previous eight weeks and who meet further eligibility criteria will be told about the trial comparing CBT + SMC vs SMC alone. If they are interested in participating, they will be given a further booklet on DS and study information. A research worker will see them to obtain their informed consent to take part in the RCT. We aim to randomise 298 people (149 to each arm). In addition to a baseline assessment, data will be collected at 6 and 12 months post randomisation. Our primary outcome is monthly seizure frequency in the preceding month. Secondary outcomes include seizure severity, measures of seizure freedom and reduction, psychological distress and psychosocial functioning, quality of life, health service use, cost effectiveness and adverse events. We will include a nested qualitative study to evaluate participants' views of the intervention and factors that acted as facilitators and barriers to participation.DiscussionThis study will be the first adequately powered evaluation of CBT for this patient group and offers the potential to provide an evidence base for treating this patient group.Trial registrationCurrent Controlled Trials ISRCTN05681227 ClinicalTrials.gov NCT02325544.

Dataset Information

Validation of a predictive calculator to distinguish between patients presenting with dissociative versus epileptic seizures.

Publications

Validation of a predictive calculator to distinguish between patients presenting with dissociative versus epileptic seizures.

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