• Florian Eyer, Tibor Schuster, Norbert Felgenhauer, Rudi Pfab, Tim Strubel, Bernd Saugel, and Thomas Zilker.
• Department of Toxicology, II. Medizinische Klinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. florian.eyer@mac.com
• Alcohol Alcohol. 2011 Jul 1;46(4):427-33.

AimsTo develop a prediction model for withdrawal seizures (WS) and delirium tremens (DT) during moderate to severe alcohol withdrawal syndrome (AWS) in a large cohort of inpatients treated for AWS (n = 827).MethodsRe-analysis of a cohort study population treated between 2000 and 2009. All patients received a score-guided and symptom-triggered therapy for AWS. Multivariable binary logistic regression models with stepwise variable selection procedures were conducted providing odds ratio (OR) estimates.ResultsIn the multivariable regression, significant predictors of WS during AWS therapy were a delayed climax of withdrawal severity since admission [OR/10 h: 1.23; 95% confidence interval (CI): 1.1-1.4; P < 0.001)], prevalence of structural brain lesions in the patient's history (OR 6.5; 95% CI: 3.0-14.1; P < 0.001) and WS as the cause of admittance (OR 2.6; 95% CI: 1.4-4.8; P = 0.002). Significant predictors at admission for the occurrence of DT were lower serum potassium (OR/1 mmol/l 0.33; 95% CI: 0.17-0.65; P = 0.001), a lower platelet count (OR/100.000 0.42; 95% CI: 0.26-0.69; P = 0.001) and prevalence of structural brain lesions (OR 5.8; 95% CI: 2.6-12.9; P < 0.001).ConclusionIn this large retrospective cohort, some easily determinable parameters at admission may be useful to predict a complicated course of alcohol withdrawal regarding the occurrence of WS or DT. Using the provided nomograms, clinicians can estimate the percentage likelihood of patients to develop either WS or DT during their course of withdrawal. Prevalence of structural brain lesions in the patient's history does strongly warrant a careful observation of patients.

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