Nicholas J Janocko1, Jin Jing2, Ziwei Fan2, Diane L Teagarden1, Hannah K Villarreal1, Matthew L Morton1, Olivia Groover1, David W Loring1, Daniel L Drane3, M Brandon Westover2, Ioannis Karakis4. 1. Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA. 2. Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. 3. Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA; Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Department of Neurology, University of Washington, Seattle, WA, USA. 4. Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA. Electronic address: ioannis.karakis@emory.edu.
Abstract
OBJECTIVE: Functional seizures (FS) are often misclassified as epileptic seizures (ES). This study aimed to create an easy to use but comprehensive screening tool to guide further evaluation of patients presenting with this diagnostic dilemma. MATERIALS AND METHODS: Demographic, clinical and diagnostic data were collected on patients admitted for video-EEG monitoring for clarification of their diagnosis. Upon discharge, patients were classified as having ES vs FS. Using the collected characteristics and video-EEG diagnosis, we created a multivariable logistic regression model to identify predictors of ES. Then, we trained an integer-coefficient model with the most frequently selected predictors, creating a pointing system coined DDESVSFS, with scores ranging from -17 to +8 points. RESULTS: 43 patients with FS and 165 patients with ES were recruited. In the final integer-coefficient model, 8 predictors were identified as significant in differentiating ES from FS: normal electroencephalogram (-3 points), predisposing factors for FS (-3 points), increased number of comorbidities (-3 points), semiology suggestive of FS (-4 points), increased seizure frequency (-4 points), longer disease duration (+3 points), antiepileptic polypharmacy (+2 points) and compliance with antiepileptic drugs (+3 points). Cumulative scores of ≤ -9 points carried <5% predictive value for ES, while cumulative scores of ≥ -1 points carried >95% predictive value. The model performed well (AUC: 0.923, sensitivity: 0.945, specificity: 0.698). CONCLUSIONS: We propose DDESVSFS as a simple, rapid and comprehensive prediction score for the Differential Diagnosis of Epileptic Seizures VS Functional Seizures. Large prospective studies are needed to evaluate its utility in clinical practice.
OBJECTIVE: Functional seizures (FS) are often misclassified as epileptic seizures (ES). This study aimed to create an easy to use but comprehensive screening tool to guide further evaluation of patients presenting with this diagnostic dilemma. MATERIALS AND METHODS: Demographic, clinical and diagnostic data were collected on patients admitted for video-EEG monitoring for clarification of their diagnosis. Upon discharge, patients were classified as having ES vs FS. Using the collected characteristics and video-EEG diagnosis, we created a multivariable logistic regression model to identify predictors of ES. Then, we trained an integer-coefficient model with the most frequently selected predictors, creating a pointing system coined DDESVSFS, with scores ranging from -17 to +8 points. RESULTS: 43 patients with FS and 165 patients with ES were recruited. In the final integer-coefficient model, 8 predictors were identified as significant in differentiating ES from FS: normal electroencephalogram (-3 points), predisposing factors for FS (-3 points), increased number of comorbidities (-3 points), semiology suggestive of FS (-4 points), increased seizure frequency (-4 points), longer disease duration (+3 points), antiepileptic polypharmacy (+2 points) and compliance with antiepileptic drugs (+3 points). Cumulative scores of ≤ -9 points carried <5% predictive value for ES, while cumulative scores of ≥ -1 points carried >95% predictive value. The model performed well (AUC: 0.923, sensitivity: 0.945, specificity: 0.698). CONCLUSIONS: We propose DDESVSFS as a simple, rapid and comprehensive prediction score for the Differential Diagnosis of Epileptic Seizures VS Functional Seizures. Large prospective studies are needed to evaluate its utility in clinical practice.
Authors: Janice L Smolowitz; Sarah C Hopkins; Tracey Perrine; Karen E Eck; Lawrence J Hirsch; Mary O'Neil Mundinger Journal: Am J Med Qual Date: 2007 Mar-Apr Impact factor: 1.852
Authors: Wesley T Kerr; Emily A Janio; Chelsea T Braesch; Justine M Le; Jessica M Hori; Akash B Patel; Norma L Gallardo; Janar Bauirjan; Andrea M Chau; Eric S Hwang; Emily C Davis; Albert Buchard; David Torres-Barba; Shannon D'Ambrosio; Mona Al Banna; Andrew Y Cho; Jerome Engel; Mark S Cohen; John M Stern Journal: Epilepsy Behav Date: 2018-02-02 Impact factor: 2.937
Authors: Ioannis Karakis; Andrew J Cole; Georgia D Montouris; Marta San Luciano; Kimford J Meador; Charitomeni Piperidou Journal: Epilepsy Res Treat Date: 2014-04-08