Comparison of first antiretroviral treatment duration and outcome in HIV, HIV–HBV and HIV–HCV infection
Bibliographic record
Abstract
Hepatitis C virus (HCV) and hepatitis B virus (HBV) co-infection may differentially influence HIV treatment duration and outcome. This was assessed at The Ottawa Hospital Immunodeficiency Clinic in first-time highly active antiretroviral therapy (HAART) recipients visited between January 2000 and December 2004. Of 968 patients, 526/700 (75%) HIV, 173/230 (75%) HIV-HCV and 30/38 (79%) HIV-HBV-infected patients initiated HAART. Co-infected patients stopped treatment sooner (HBV - 10 months, HCV - 9 months) than HIV mono-infected (17 months) (P<0.001). Injection drug history predicted shorter treatment duration (odds ratio [OR]1.59, P<0.001). Use of non-nucleoside-reverse-transcriptase-inhibitor-containing HAART (OR 0.76, P<0.01) and low-dose ritonavir (<400 mg twice daily)-based HAART (OR 0.83, P = 0.06) predicted longer treatment duration. HCV co-infection did not predict duration of therapy (OR 1.19, P=0.19) once controlled for by these three variables. Poor adherence was a major explanation for eventual treatment interruption in those with HIV-HCV (22% versus 5% in HIV alone; P<0.001) as was substance abuse (7% versus < 1% in HIV; P<0.001). Metabolic complications resulted in HAART interruption in HIV mono-infection (8%) but not with HBV or HCV co-infection (both <1%; P<0.001). Antiretroviral selection is critical to the longevity of initially prescribed regimens, irrespective of viral hepatitis co-infection. Attention to this and strategies targeting substance abuse and adherence in HIV-HCV are predicted to increase the duration of HAART.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".