James H Park1, John Bokma2, Kristina Chapple2, Jason P Caplan3. 1. Department of Neurology, Barrow Neurological Institute, Phoenix, AZ. 2. Department of Psychiatry, Creighton University School of Medicine at St. Joseph's Hospital and Medical Center, Phoenix, AZ. 3. Department of Psychiatry, Creighton University School of Medicine at St. Joseph's Hospital and Medical Center, Phoenix, AZ. Electronic address: jason.caplan@dignityhealth.org.
Abstract
BACKGROUND: Distinguishing epileptic seizures from nonepileptic seizures (NES) can be difficult, given their similar motoric manifestations and a common comorbidity. Although video electroencephalography in an epilepsy monitoring unit ideally remains the gold standard for the identification of NES, a number of "soft signs" have been proposed to indicate a greater likelihood that convulsive episodes are NES rather than epileptic in nature. Trainees at our institution have cited the presence of multiple listed allergies as indicative of a higher likelihood of NES. OBJECTIVE: The goal of this study was to provide a statistical analysis of polyallergy and its association with patients with NES admitted for video electroencephalograph monitoring. METHODS: Records of all epilepsy monitoring unit patients at St. Joseph's Hospital and Medical Center between 2006 and 2012 were reviewed for age, sex, electroencephalograph diagnosis, antiepileptic drugs previously tried, and allergy number. RESULTS: A total of 1834 patient records were used for analysis. The group classified as nonepileptic had the highest average number of allergies at 1.56, whereas the group classified as epileptic had the lowest average number of allergies at 0.70. A logistic regression model revealed that for every increase in the number of allergies greater than zero, the odds of being nonepileptic increases by 1.38 times. CONCLUSIONS: This study supports polyallergy as a predictive sign for NES. Based on a logistic regression model, we claim that each additional allergy is associated with an increase in the likelihood of a nonepileptic diagnosis by 38%.
BACKGROUND: Distinguishing epilepticseizures from nonepileptic seizures (NES) can be difficult, given their similar motoric manifestations and a common comorbidity. Although video electroencephalography in an epilepsy monitoring unit ideally remains the gold standard for the identification of NES, a number of "soft signs" have been proposed to indicate a greater likelihood that convulsive episodes are NES rather than epileptic in nature. Trainees at our institution have cited the presence of multiple listed allergies as indicative of a higher likelihood of NES. OBJECTIVE: The goal of this study was to provide a statistical analysis of polyallergy and its association with patients with NES admitted for video electroencephalograph monitoring. METHODS: Records of all epilepsy monitoring unit patients at St. Joseph's Hospital and Medical Center between 2006 and 2012 were reviewed for age, sex, electroencephalograph diagnosis, antiepileptic drugs previously tried, and allergy number. RESULTS: A total of 1834 patient records were used for analysis. The group classified as nonepileptic had the highest average number of allergies at 1.56, whereas the group classified as epileptic had the lowest average number of allergies at 0.70. A logistic regression model revealed that for every increase in the number of allergies greater than zero, the odds of being nonepileptic increases by 1.38 times. CONCLUSIONS: This study supports polyallergy as a predictive sign for NES. Based on a logistic regression model, we claim that each additional allergy is associated with an increase in the likelihood of a nonepileptic diagnosis by 38%.