Objective score from initial interview identifies patients with probable dissociative seizures.

Area of Science:

• Neurology
• Clinical Diagnostics

Background:

• Dissociative seizures (DS) are often misdiagnosed, leading to delayed or incorrect treatment.
• Early identification of probable DS is crucial for appropriate diagnostic workup and management.

Purpose of the Study:

• To develop and validate the Dissociative Seizures Likelihood Score (DSLS).
• To create an evidence-based tool for identifying probable DS during the initial outpatient visit.
• To facilitate early triage for comprehensive diagnostic assessment.

Main Methods:

• Analysis of clinical history data from 1616 patients with video-electroencephalography (vEEG) confirmed diagnoses.
• Comparison of five patient groups: epileptic seizures (ES), DS, physiologic nonepileptic seizure-like events (PSLE), mixed DS plus ES, and inconclusive monitoring.
• Application of data-driven methods and recursive feature elimination (RFE) to identify diagnostic features and develop the DSLS model.

Main Results:

• The DSLS accurately identified 77% of prospective patients with either ES or DS (sensitivity 74%, specificity 84%).
• DSLS accuracy was comparable to neurologists' clinical impression (84%).
• A low rate of missed DS cases (3%) was observed for both the DSLS and clinicians.

Conclusions:

• The DSLS is a reliable, evidence-based tool for identifying probable dissociative seizures using clinical history.
• The DSLS supports clinical decision-making and aids in identifying patients requiring further diagnostic evaluation.
• Combining the DSLS with clinical judgment can improve the identification of patients who warrant assessment at specialized epilepsy centers.