AUTHOR=Dashtkoohi Mohammad , Ranji-Bourachaloo Sakineh , Pouremamali Rozhina , Dashtkoohi Mohadese , Zamani Raha , Moeinafshar Aysan , Shizarpour Arshia , Shakiba Shirin , Babaee Mohammadali , Tafakhori Abbas 

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

JOURNAL=Frontiers in Neurology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2023.1295266

DOI=10.3389/fneur.2023.1295266

ISSN=1664-2295

ABSTRACT=Purpose: Distinguishing functional seizures (FS) from epileptic seizures (ES) can pose a challenge due to their similar clinical manifestations. The creation of a clinical scoring system that assists in accurately diagnosing patients with FS would be a valuable contribution to medical practice. This score has the potential to enhance clinical decision-making and facilitate prompt diagnosis of patients with FS.
Methods: Participants who met the inclusion criteria were randomly divided into three distinct groups: training, validation, and test cohorts. Within the training group, demographic and semiological variables were thoroughly examined through various univariate analyses. Variables that exhibited a significant difference between FS and ES were then further scrutinized in two multivariate logistic regression models. This led to the development of scoring systems based on the odds ratio of the significant discriminant variables. Using the validation group, the optimal cutoff based on AUC was determined, and subsequently, the developed score was evaluated in the test cohort to comprehensively assess its performance.
Results: developed score yielded an AUC of 0.78 in the validation cohort and a cutoff point of 6 determined with a focus on maximizing sensitivity without significantly compromising specificity. Subsequently, the score was subjected to the test cohort, where it demonstrated a sensitivity of 86.96%, a specificity of 73.81%.
Conclusion: We have developed a new tool that shows promise in identifying patients suspicious of FS. With further analysis through prospective studies, this innovative simple tool can be successfully integrated into the diagnostic process of FS.