Treatment effects of the differential first-line antiretroviral regimens among HIV/HBV coinfected patients in southwest China: an observational study
Bibliographic record
Abstract
HIV with HBV co-infection can result in greater HIV-related immunosuppression, morbidity and mortality. Currently, there are few studies to evaluate direct treatment effects on mortality and attrition rates between first-line antiretroviral therapy (ART) based-on tenofovir (TDF) and/or lamivudine (3TC) in a real-world setting. We used Cox proportional hazard models to evaluate direct treatment effects of the first-line ART containing stavudine (d4T), azidothymidine (AZT) and TDF on death and attrition among HIV patients with HBV coinfection. A total of 3912 patients met study eligibility criteria. The overall mortality rate and attrition rate was 2.85 (95% CI: 2.55-3.16) and 8.87 (95% CI: 8.32-9.41) per 100 person-years, respectively. The ART containing TDF had a significantly lower risk of death [adjusted hazard ratio (AHR) = 0.58, 95% CI: 0.44-0.77] when compared to the ART containing d4T, but the risk of death was not significantly different when compared to the ART containing AZT (AHR = 0.91, 95% CI: 0.69-1.20). Patients with HIV/HBV coinfection receiving the ART containing TDF had significantly lower risk rates of attrition compared to those receiving the ART containing d4T (AHR = 0.72, 95% CI: 0.60-0.86) or AZT (AHR = 0.67, 95% CI: 0.58-0.77). Compared with the ART containing d4T, the ART containing AZT was significant and not significant associated with a lower risk of death and attrition, respectively. The ART containing TDF had significant effects on both of death and attrition among HIV patients with HBV coinfection.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".