BRIEF REPORT Immunovirologic Control 24 Months After Interruption of Antiretroviral Therapy
Bibliographic record
Abstract
Background: There is interest in whether a short course of combination antiretroviral therapy (cART) at the time of human immunodeficiency virus (HIV) seroconversion could induce long-term immunologic control after its interruption. We aimed to determine the time of virologic rebound after interruption of treatment initiated close to HIV seroconversion and to identify potential cases of posttreatment controllers (PTCs) in the CASCADE (Concerted Action on Seroconversion to AIDS and Death in Europe) Collaboration. Methods: Prospective cohort study nested within the CASCADE database of routinely collected data about patients with HIV with well-estimated date of HIV seroconversion from Europe, Canada, and Australia in the post-cART era. Participants were individuals who interrupted successful cART initiated within 3 months of HIV seroconversion. The main outcome was loss of PTC status, defined as the earlier date of virologic rebound (first of 2 consecutive measurements showing HIV RNA levels �50 copies/mL) or reinitiation of any ART after cART interruption. Results: Median time to loss of PTC status in 259 eligible individuals was 1.7 months. Eleven patients did not experience virologic rebound by 24 months after treatment interruption. Conclusion: Most patients experience virologic rebound soon after cART interruption; however, although PTCs are rare, the results of this study confirm their existence.
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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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".