Biomedicine

Abstract

Introduction and Aim: Management strategies of Alcohol Withdrawal Syndrome could be optimized if patients with greater risk are identified early and treated aggressively. Studying the pattern and predictors of alcohol withdrawal syndrome was the main objective of our study.
Materials and Methods: A total of 100 consenting male patients in the age group of 18-60 years diagnosed with alcohol dependence and uncomplicated alcohol withdrawal undergoing in-patient detoxification in tertiary care center in north India were included in the study. A semi structured proforma was used to collect socio-demographic data, Alcohol Use Disorders Identification Test (AUDIT) was used as screening tool and Clinical Institute Withdrawal Assessment for Alcohol-revised (CIWA- Ar) was used to assess severity of withdrawal.
Results: Symptoms like difficulty in orientation, seizures and hallucinations were relatively specific for severe AWS, while tremors and anxiety were common to all the patients and were non-specific for predicting severity of AWS. The severity of AWS symptoms correlated significantly with increasing age, duration of alcohol use and AUDIT score.
Conclusion: We concluded that increasing age, longer duration of alcohol use, higher AUDIT score and symptoms related to hallucinations, orientation and seizure are linked to severe alcohol withdrawal. Prior knowledge of these predictors will help to identify the patients at risk of severe alcohol withdrawal so that individual care can be enhanced.