Binge drinking at time of bariatric surgery is associated with liver disease, suicides, and increases long-term mortality
Bibliographic record
Abstract
BACKGROUND AND AIMS: Alcohol use disorder has been reported in patients undergoing bariatric procedures, but the pattern of alcohol consumption has not been evaluated. We investigated the prevalence, risk factors, and impact of binge drinking (BD) at the time of surgery and during follow-up. METHODS: A prospective, longitudinal study of subjects undergoing bariatric surgery was included in the LABS-2 registry between 2006 and 2009. Participants with AUDIT questionnaire at the time of surgery and a minimum of 12 months follow-up were included. BD was defined as consuming ≥5 drinks on at least 1 occasion in the previous month. Liver biopsies were obtained during bariatric procedures in not all cases. Survival analysis was performed with the adjusted Cox regression model and competing risk. RESULTS: A total of 2257 subjects were included, with a median follow-up of 79 months. The prevalence of BD at time of surgery was 12%, and it raised up to 23% during follow-up. Patients with BD predominantly had a binge eating disorder (OR=1.35 [95% CI: 1.04-1.76]), regularly consumed fast food [OR=1.4 (95% CI: 1.07-1.85)] and used other drugs (OR=2.65 [95% CI: 1.74-4.04]). Within liver biopsies evaluation, BD showed higher hepatic iron deposits (OR=3.00 [95% CI: 1.25-7.21]). BD at the time of surgery was associated with a higher risk of BD during follow-up (OR=10.49 [95% CI: 7.86-14.00]) and long-term mortality (HR: 3.21 [95% CI: 1.67-6.18]). Specific causes of death in these patients with BD were liver disease (p=0.020), suicide (p=0.015), neoplasms (p=0.034), and respiratory (p=0.025). CONCLUSIONS: The prevalence of BD in patients undergoing bariatric surgery is high and increases the risk of postoperative liver disease, suicides, and long-term mortality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".