Development of a rating scale to predict the severity of alcohol withdrawal syndrome

Tilman Wetterling*, Bernhard Weber, Markus Depfenhart, Barbara Schneider, Klaus Junghanns

*Korrespondierende/r Autor/-in für diese Arbeit
20 Zitate (Scopus)


Aim: Various factors that may influence the severity of the alcohol withdrawal syndrome (AWS) have been identified. We tested the predictive value of these factors compiled in a newly developed scale, LARS (Luebeck alcohol withdrawal risk scale). Method: A total of 100 individuals (81 males, 19 females, mean age: 47.6 ± 9.9 years) consecutively transferred to inpatient detoxification were included in this prospective study. All fulfilled the ICD-10 criteria for alcohol dependence. The LARS was applied at the time of admission. The course of the AWS was assessed by AWS-scale at least every 4 h. The maximum AWS-score was taken as indicator of the severity of AWS. Results: The mean AWS-score max was 6.5 ± 3.3. In all 20% of the patients developed a severe AWS (AWS-scoremax ≥10). The maximum score usually occurred within 36 h after the last drink. A short version, the LARS11, was developed by statistically grounded item reduction. The optimal cut-off of the LARS11 was calculated as 10. The positive predictive value for severe AWS was 76%, while the negative predictive value was 98.7%. The sensitivity and specificity were high (95 or 92.5%, respectively). Conclusion: LARS11 assessed immediately be fore detoxification appears to provide a useful estimate of mild/moderate versus severe AWS, and is now ready to be validated in an independent sample.

ZeitschriftAlcohol and Alcoholism
Seiten (von - bis)611-615
PublikationsstatusVeröffentlicht - 11.2006

Strategische Forschungsbereiche und Zentren

  • Forschungsschwerpunkt: Gehirn, Hormone, Verhalten - Center for Brain, Behavior and Metabolism (CBBM)


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