Physicians’ Attitudes and Practice Toward Treating Injection Drug Users Infected with Hepatitis C Virus: Results from a National Specialist Survey in Canada
Bibliographic record
Abstract
BACKGROUND: In Canada, more than 70% of new cases of hepatitis C virus (HCV) infection per year involve injection drug users (IDUs) and, currently, there is no consensus on how to offer them medical care. OBJECTIVE: To examine the characteristics of Canadian specialist physicians and their likelihood to provide treatment to HCV patients who are IDUs. METHODS: A nationwide, cross-sectional study was conducted in the specialty areas of hepatology, gastroenterology and infectious diseases to examine HCV services. The questionnaire requested information regarding basic demographics, referral pathways and opinions (yes⁄no), and examined how a physician's treatment regimen is influenced by factors such as treatment eligibility, HCV care management and barriers to providing quality service. RESULTS: Despite the fact that the majority of prevalent and incident cases of HCV are associated with injection drug use, very few specialist physicians actually provide the necessary therapy to this population. Only 19 (19.79%) comprehensive service providers were likely to provide treatment to a current IDU who uses a needle exchange on a regular basis. The majority of comprehensive service providers (n=86 [89.58%]) were likely to provide treatment to a former IDU who was stable on substitution therapy. On bivariate analysis, factors associated with the likelihood to provide treatment to current IDUs included physicians' type, ie, infectious disease specialists compared with noninfectious specialists (OR 3.27 [95% CI 1.11 to 9.63]), and the size of the community where they practice (OR 4.16 [95% CI 1.36 to 12.71] [population 500,000 or greater versus less than 500,000]). Results of the multivariate logistic regression analysis were largely consistent with the results observed in the bivariate analyses. After controlling for other confounding variables, only community size was significantly associated with providing treatment to current IDUs (OR 3.89 [95% CI 1.06 to 14.26] [population 500,000 or greater versus less than 500,000]). CONCLUSION: The present study highlighted the reluctance of specialists to provide treatment to current IDUs infected with HCV. Providing treatment services for HCV-infected substance abusers is challenging and there are many treatment barriers. However, effective delivery of treatment to this population will help to limit the spread of HCV. The present study clearly identified a need for improved HCV treatment accessibility for IDUs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".