Impact of major depression and antidepressant use on alcoholic and non‐alcoholic fatty liver disease: A population‐based study
Bibliographic record
Abstract
BACKGROUND AND AIMS: The effect of major depression and antidepressant use on patient survival in chronic liver disease is unknown. We evaluated the impact of major depressive disorder (MDD) and antidepressants on survival among patients with alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD). METHODS: The Health Improvement Network database, the largest medical database in the United Kingdom, was used to identify incident ALD (n = 4148) and NAFLD (n = 19 053) in patients between 1986 and 2017. Our primary outcome was development of decompensated cirrhosis or death. MDD and each class of antidepressants were assessed in multivariate Cox proportional hazards models as time-varying covariates. Models were adjusted for age, sex, socio-economic status and comorbidities. RESULTS: MDD rate was higher among patients with ALD (22.8%) compared to those with NAFLD (16.1%), P < .01. Antidepressant usage was common in patients with ALD (47.4%) and NAFLD (40.8%). After adjusting for covariates, MDD (adjusted hazard ratio [AHR]: 0.80, 95% CI: 0.63-1.02 for NAFLD; and AHR 1.01, 0.88-1.15 for ALD) was not associated with improved decompensated cirrhosis-free survival. The antidepressant mirtazapine was associated with worse decompensated cirrhosis-free survival among NAFLD (AHR 2.16, 95% CI: 1.32-3.52) and ALD (AHR 1.53, 1.09-2.15) cohorts. Similarly, mirtazapine was associated with mortality in both cohorts. CONCLUSIONS: MDD was not associated with worse outcomes for ALD or NAFLD. Mirtazapine was associated with an increased risk of decompensated cirrhosis or death, which was not observed with other antidepressants. Prospective studies are warranted to confirm these findings.
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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) | 0.000 | 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".