Barriers to Hepatitis C Virus Treatment in a Canadian HIV-Hepatitis C Virus Coinfection Tertiary Care Clinic
Bibliographic record
Abstract
BACKGROUND: Despite demonstrated efficacy in HIV-hepatitis C virus (HCV) coinfection, not all patients initiate, complete or achieve success with HCV antiviral therapy. PATIENTS AND METHODS: All HIV-HCV coinfected patient consults received at The Ottawa Hospital Viral Hepatitis Clinic (Ottawa, Ontario) between June 2000 and September 2006 were identified using a clinical database. A descriptive analysis of primary and contributing factors accounting for why patients did not initiate HCV therapy, as well as the therapeutic outcomes of treated patients, was conducted. RESULTS: One hundred two consults were received. Sixty-seven per cent of patients did not initiate HCV therapy. The key primary reasons included: HIV therapy was more urgently needed (22%), loss to follow-up (12%), patients were deemed unlikely to progress to advanced liver disease (18%) and patient refusal (12%). Many patients had secondary factors contributing to the decision not to treat, including substance abuse (23%) and psychiatric illness (14%). Overall, 59% of untreated patients (40 of 68) were eventually lost to follow-up. Thirty-three per cent of referred patients started HCV therapy. Twenty-seven of 42 courses (64%) were interrupted prematurely for reasons such as virological nonresponse (48%), psychiatric complications (10%) and physical side effects (7%). Of all treatment recipients, 12 of 42 full courses of therapy were completed and three remained on HCV medication. Overall, eight of the 102 coinfected patients studied (8%) achieved a sustained virological response. DISCUSSION: Not all HIV-HCV coinfected patients who are deemed to be in need of HCV treatment are initiating therapy. Only a minority of patients who do receive treatment achieve success. Implementation of HIV treatment, patient retention, attention to substance abuse and mental health care should be the focus of efforts designed to increase HCV treatment uptake and success. This can be best achieved within a multidisciplinary model of health care delivery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".