Clinical Functional Seizure Score (CFSS): a simple algorithm for clinicians to suspect functional seizures

Area of Science:

• Neurology
• Clinical Diagnostics

Background:

• Distinguishing functional seizures (FS) from epileptic seizures (ES) is clinically challenging due to overlapping symptoms.
• Accurate differentiation is crucial for appropriate patient management and treatment.

Purpose of the Study:

• To develop and validate a clinical scoring system to aid in the diagnosis of functional seizures (FS).
• To improve clinical decision-making and expedite the diagnostic process for patients with FS.

Main Methods:

• A clinical scoring system (CFSS) was developed using demographic and semiological variables from training and validation cohorts.
• Multivariate logistic regression identified discriminating variables between FS and ES.
• The optimal cutoff value was determined using AUC in the validation cohort and the CFSS was evaluated in a test cohort.

Main Results:

• The CFSS demonstrated an AUC of 0.78 in the validation cohort.
• A cutoff score of 6 was established, balancing sensitivity and specificity.
• In the test cohort, the CFSS achieved 86.96% sensitivity and 73.81% specificity.

Conclusions:

• A novel, simple tool (CFSS) has been developed with promising results for identifying patients with suspected functional seizures (FS).
• Further prospective studies are warranted to integrate this tool into routine diagnostic workflows for FS.