Impact of depression and antidepressant use on clinical outcomes of hepatitis B and C: a population-based study
Bibliographic record
Abstract
BACKGROUND: Depression is common in patients with chronic viral hepatitis. We evaluated the impact of major depressive disorder (MDD) and antidepressant use on survival among patients with HBV and HCV. METHODS: We used The Health Improvement Network database, the largest medical database in the UK, to identify incident HBV (n=1401) and HCV (n=1635) in patients between 1986 and 2017. Our primary composite outcome was the development of decompensated cirrhosis or death. MDD and each class of antidepressants were assessed in multivariate Cox proportional hazards models. Models were adjusted for age, sex, and clinical comorbidities. RESULTS: The prevalence of MDD among HCV patients was higher compared with HBV patients (23.5% vs. 9.0%, p<0.001, respectively). Similarly, HCV patients were more likely to use antidepressants (59.6%) compared with HBV patients (27.1%), p>0.001. MDD was not an independent predictor for decompensated cirrhosis-free survival or mortality. However, the use of tricyclic and tetracyclic antidepressants (TCAs) was associated with poor decompensated cirrhosis-free survival in HBV and HCV cohorts (adjusted HR: 1.80, 95% CI, 1.00-3.26 and 1.56, 95% CI, 1.13-2.14, respectively). Both TCAs in the HBV cohort and selective serotonin reuptake inhibitors among the HCV cohort were associated with poor overall survival (adjusted HR: 2.18, 95% CI, 1.16-4.10; 1.48, 95% CI, 1.02-2.16, respectively). CONCLUSIONS: Although prevalent among viral hepatitis patients, MDD did not affect disease progression or survival in either HBV or HCV cohorts. TCA use was associated with poor decompensated cirrhosis-free survival. Therefore, its use should be further studied among viral hepatitis patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".