ArticleEuropean archives of psychiatry and clinical neuroscience2021
Classical blood biomarkers identify patients with higher risk for relapse 6 months after alcohol withdrawal treatment.
Article in European archives of psychiatry and clinical neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Differentiating Alcohol and Substance Use Disorders Using Multiclass Machine Learning Models Based on Routine Hemogram Parameters.Healthcare (Basel, Switzerland) · 2026Article
- The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment.Frontiers in psychiatry · 2026Article
- Lab tests can be used to predict phosphatidylethanol-measured high-risk alcohol use among people with HIV: a proof-of-concept using machine learning.Alcohol and alcoholism (Oxford, Oxfordshire) · 2025Article
- Repetitive transcranial magnetic stimulation combined with cognitive behavioral therapy treatment in alcohol-dependent patients: A randomized, double-blind sham-controlled multicenter clinical trial.Frontiers in psychiatry · 2022Article
- Exploration of the Role of Serine Proteinase Inhibitor A3 in Alcohol Dependence Using Gene Expression Omnibus Database.Frontiers in psychiatry · 2021Article
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Authors and funding
9 authors.
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Abstract
This naturalistic study among patients with alcohol dependence examined whether routine blood biomarkers could help to identify patients with high risk for relapse after withdrawal treatment. In a longitudinal study with 6-month follow-up among 133 patients with alcohol dependence who received inpatient alcohol withdrawal treatment, we investigated the usefulness of routine blood biomarkers and clinical and sociodemographic factors for potential outcome prediction and risk stratification. Baseline routine blood biomarkers (gamma-glutamyl transferase [GGT], alanine aminotransferase [ALT/GPT], aspartate aminotransferase [AST/GOT], mean cell volume of erythrocytes [MCV]), and clinical and sociodemographic characteristics were recorded at admission. Standardized 6 months' follow-up assessed outcome variables continuous abstinence, days of continuous abstinence, daily alcohol consumption and current abstinence. The combined threshold criterion of an AST:ALT ratio > 1.00 and MCV > 90.0 fl helped to identify high-risk patients. They had lower abstinence rates (P = 0.001), higher rates of daily alcohol consumption (P < 0.001) and shorter periods of continuous abstinence (P = 0.027) compared with low-risk patients who did not meet the threshold criterion. Regression analysis confirmed our hypothesis that the combination criterion is an individual baseline variable that significantly predicted parts of the respective outcome variances. Routinely assessed indirect alcohol biomarkers help to identify patients with high risk for relapse after alcohol withdrawal treatment. Clinical decision algorithms to identify patients with high risk for relapse after alcohol withdrawal treatment could include classical blood biomarkers in addition to clinical and sociodemographic items.
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