Psychiatric treatment considerations with direct acting antivirals in hepatitis C
Bibliographic record
Abstract
BACKGROUND: Despite recent advances in hepatitis C (HCV) treatment, specifically the addition of direct acting antivirals (DAAs), pegylated interferon-alpha remains the backbone of HCV therapy. Therefore, the impact of DAAs on the management of co-morbid psychiatric illness and neuropsychiatric sequalae remains an ongoing concern during HCV therapy. This paper provides a review of the neuropsychiatric adverse effects of DAAs and drug-drug interactions (DDIs) between DAAs and psychiatric medications. METHODS: We conducted a Pubmed search using relevant search terms and hand searched reference lists of related review articles. In addition, we searched abstracts for major hepatology conferences and contacted respective pharmaceutical companies for additional studies. RESULTS: Limited data is available on the neuropsychiatric adverse effects of DAAs; however, data from major clinical trials suggest that DAAs have minimal neuropsychiatric risk. DAAs can potentially interact with a variety of psychotropic agents via cytochrome P450 and p-glycoprotein interactions. Triazolam, oral midazolam, St. John's Wort, carbamazepine and pimozide, are contraindicated with DAAs. DDIs between DAAs and antidepressants, anxiolytics, hypnotics, mood stabilizers, antipsychotics and treatments for opioid dependence are summarized. CONCLUSIONS: Although DAAs do not add significant neuropsychiatric risk, the potential for DDIs is high. Consideration of DDIs is paramount to improving medication adherence and mitigating adverse effects during HCV therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".