The Level of Alcohol Consumption in the Prior Year Does Not Impact Clinical Outcomes in Patients With Alcohol‐Associated Hepatitis
Bibliographic record
Abstract
The 10-item Alcohol Use Disorders Identification Test (AUDIT-10) and its shorter form, AUDIT-Consumption (AUDIT-C), are questionnaires used to characterize severity of drinking. We hypothesized that liver injury and short-term outcomes of alcohol-associated hepatitis (AH) would correlate with a patient's recent alcohol consumption as determined by AUDIT-10 and AUDIT-C. We analyzed a prospective international database of patients with AH diagnosed based on the National Institute on Alcohol Abuse and Alcoholism (NIAAA) standard definitions. All patients were interviewed using AUDIT-10. Primary outcomes included the discriminatory ability of the AUDIT-10 and AUDIT-C scores for predicting survival status at 28 and 90 days and severity of liver injury, as measured by Model for End-Stage Liver Disease-sodium (MELD-Na). The relationship between AUDIT scores and survival status was quantified by calculating the area under the curve of the receiver operating characteristic analysis. The relationship between AUDIT scores and MELD-Na was examined using correlation coefficients. In 245 patients (age range 25-75 years; 35% female), we found no correlation between AUDIT-10 or AUDIT-C scores and either 28- or 90-day mortality. Similarly, there was no correlation between AUDIT-10 and AUDIT-C and MELD-Na scores. There was a strong positive correlation between MELD-Na and 28- and 90-day mortality. Additional measures of severity of alcohol use (average grams of alcohol consumed per day, years of drinking, convictions for driving under the influence, and rehabilitation attempts) and psychosocial factors (marriage, paid employment, and level of social support) had no influence on MELD-Na. In patients presenting with AH, AUDIT-10 and AUDIT-C were predictors of neither clinical severity of liver disease nor short-term mortality, suggesting that level of alcohol consumption in the prior year is not key to the presenting features or outcome of AH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".