Virologic and Immunologic Impact and Durability of Enfuvirtide-Based Antiretroviral Therapy in HIV-Infected Treatment-Experienced Patients in a Clinical Setting
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness and safety of enfuvirtide-based therapy in treatment-experienced patients in a clinical setting. METHOD: Retrospective study of treatment-experienced patients receiving enfuvirtide-based therapy for a minimum of 2 months. Endpoints included virologic suppression, virologic rebound, immunologic response, and adverse events. RESULTS: Sixty-four patients were eligible for inclusion in the analysis. Median baseline viral load and CD4+ count were 4.7 log10 copies/mL (interquartile range [IQR], 4.0-5.2) and 150 cells/mm3 (IQR, 60-250), respectively. At month 12, viral load declined by a median of 2.53 log10 copies/mL (IQR, 0.97-3.12). The unadjusted median time to virologic suppression was 7.7 months (95% CI 4.1-10.4 months). Baseline viral load and number of protease inhibitors in the current regimen were significantly associated with virologic suppression following multivariate analysis (hazard ratio [HR] 0.45, 95% CI 0.31-0.63, p < .0001, and HR 0.51, 95% CI 0.27-0.94, p = .03, respectively). Among the 42 patients who attained sustained virologic suppression, 10 experienced virologic rebound during a median follow-up of 13.3 months (IQR, 7.0-19.1). Injection site reactions were reported in 33 (52%) patients, resulting in treatment discontinuation in nine patients. CONCLUSION: Enfuvirtide-based therapy provides durable antiretroviral activity for treatment-experienced patients in a clinical setting.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".