Algorithm Analysis of the DSM-5 Alcohol Withdrawal Symptom

DSM-5酒精戒断症状的算法分析

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Abstract

BACKGROUND: Alcohol withdrawal (AW) is an important clinical and diagnostic feature of alcohol dependence. AW has been found to predict a worsened course of illness in clinical samples, but in some community studies, AW endorsement rates are strikingly high, suggesting false-positive symptom assignments. Little research has examined the validity of the DSM-5 algorithm for AW, which requires either the presence of at least 2 of 8 subcriteria (i.e., autonomic hyperactivity, tremulousness, insomnia, nausea, hallucinations, psychomotor agitation, anxiety, and grand mal seizures), or, the use of alcohol to avoid or relieve these symptoms. METHODS: We used item and algorithm analyses of data from waves 1 and 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (current drinkers, n = 26,946 at wave 1) to study the validity of DSM-5 AW as operationalized by the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV (AUDADIS-IV). RESULTS: A substantial proportion of individuals given the AW symptom reported only modest to moderate levels of alcohol use and alcohol problems. Alternative AW algorithms were superior to DSM-5 in terms of levels of alcohol use and alcohol problem severity among those with AW, group difference effect sizes, and predictive validity at a 3-year follow-up. The superior alternative algorithms included those that excluded the nausea subcriterion; required withdrawal-related distress or impairment; increased the AW subcriteria threshold from 2 to 3 items; and required tremulousness for AW symptom assignment. CONCLUSIONS: The results indicate that the DSM-5 definition of AW, as assessed by the AUDADIS-IV, has low specificity. This shortcoming can be addressed by making the algorithm for symptom assignment more stringent.

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