COMBINING THE AUDIT QUESTIONNAIRE AND BIOCHEMICAL MARKERS TO ASSESS ALCOHOL USE AND RISK OF ALCOHOL WITHDRAWAL IN MEDICAL INPATIENTS

Abstract

Alcohol consumption is often under-reported in patients admitted to general hospitals with acute illness. For alcohol-dependent individuals hospital admission results in an enforced period of abstinence with potential alcohol withdrawal symptoms, and possible life threatening complications. Early detection of alcohol use is therefore beneficial to patients and health services. The purpose of this study was to investigate the performance of the alcohol use disorders identification test (AUDIT) questionnaire in the acute medical setting, and the effect of combining routine biological markers-glutamyltransferase, alanine aminotransferase, aspartate aminotransferase, and mean corpuscular volume (MCV) on its performance in the early identification of in-patients with alcohol use disorders and at risk of developing symptoms of alcohol withdrawal. Prospective study in consecutive patients admitted to an acute medical admissions ward. All patients were screened using the AUDIT questionnaire and routine blood tests. Patients were then monitored for symptoms of withdrawal using clinical institute withdrawal assessment for alcohol (CIWA-Ar). Of the 874 patients screened using the AUDIT, 98 (11%) screened positive of whom 17 (2% of the 874) experienced clinically significant alcohol withdrawal symptoms, when using serial CIWA-Ar. The AUDIT and serial CIWA-Ar detected all patients who went on to manifest acute withdrawal symptoms. There was no loss of sensitivity at an AUDIT cut-off of 13 or more compared with the lower cut-off of 8 or more. A positive predictive value of 17.3% for an AUDIT score of 8 or more in the detection of withdrawal, increased to 47.1% when found in combination with at least two abnormal biological markers whilst maintaining a sensitivity of 94.1% and specificity of 97.9%. These findings confirm that AUDIT is a useful alcohol screen in general medical settings and that its ability to correctly predict which patients will experience alcohol withdrawal is increased when used in combination with biological markers.