title: A prediction model for identifying alcohol withdrawal seizures.
abstract: A retrospective review of alcohol withdrawal seizures was performed at a private chemical-dependence treatment facility to help identify patients who were at high risk for having a seizure. Patients were identified by two means: controlled substance records were reviewed to determine patients having received intramuscular phenobarbital, and patient charts were reviewed for all patients with a discharge diagnosis of a seizure disorder. Two thousand and one patient records were reviewed; alcohol withdrawal seizure patients were identified. Twenty-eight randomly selected nonseizure patient records served as controls. The statistical test consisted of a discriminant function analysis. The data yielded a statistically significant predictive model for alcohol withdrawal seizures based on six interdependent patient variables which will be helpful in treating future patients undergoing alcohol withdrawal.
authors.affiliation: Department of Hospital Pharmacy Practice and Administration, Medical University of South Carolina, Charleston 29425.
authors.forename: W A
authors.initials: WA
authors.lastname: Morton
authors.forename: L K
authors.initials: LK
authors.lastname: Laird
authors.forename: D F
authors.initials: DF
authors.lastname: Crane
authors.forename: N
authors.initials: N
authors.lastname: Partovi
authors.forename: L H
authors.initials: LH
authors.lastname: Frye
mesh_terms: D000328:Adult; D000430:Alcohol Withdrawal Delirium / Q000175:diagnosis*; D000437:Alcoholism / Q000534:rehabilitation*; D004569:Electroencephalography / Q000187:drug effects; D000431:Ethanol / Q000009:adverse effects; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009460:Neurologic Examination / Q000187:drug effects; D012189:Retrospective Studies; D012307:Risk Factors; D012640:Seizures / Q000175:diagnosis*; D016320:Substance Abuse Treatment Centers
chemical_list: D000431:Ethanol