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Use of biomarkers for alcohol use disorders in clinical practice
Author(s) -
Neumann Tim,
Spies Claudia
Publication year - 2003
Publication title -
addiction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.424
H-Index - 193
eISSN - 1360-0443
pISSN - 0965-2140
DOI - 10.1046/j.1359-6357.2003.00587.x
Subject(s) - carbohydrate deficient transferrin , context (archaeology) , medicine , alcohol abuse , comorbidity , alcohol use disorder , clinical practice , alcohol , psychiatry , intensive care medicine , alcohol consumption , physical therapy , paleontology , biochemistry , chemistry , biology
Background Biomedical markers may provide additive objective information in screening and confirmation of acute or recent consumption, intoxication, relapse, heavy drinking, hazardous/harmful use/abuse and dependence and alcohol use related organ dysfunction (alcohol use‐related disorders: AUDs). Aims To review the use of biomarkers in clinical practice to detect AUDs. Findings About one‐fifth of the patients seen in clinical practice have AUDs, which offer a variety of treatment options if diagnosed. The diagnosis of AUDs relies on clinical and alcohol‐related history, physical examination, questionnaires and laboratory values. No clinical available laboratory test [e.g. for acute abuse: alcohol in blood or breath; for chronic alcohol abuse: γ‐glutamyl transferase (GGT), mean corpuscular volume (MCV), carbohydrate‐deficient transferrin (CDT)] is reliable enough on its own to support a diagnosis of alcohol dependence, harmful use or abuse. Sensitivities, specificities and the predictive values may vary considerably according to patient and control group characteristics (e.g. gender, age or related comorbidity). In patient groups with limited cooperation markers may be helpful when considering treatment options. Conclusions More research is needed to determine the value of markers (single or combined, with questionnaires) in the context of clinical decision‐making algorithms in defined settings and with defined dichotomous outcome variables.