Natural history of HIV-control since seroconversion
Bibliographic record
Abstract
OBJECTIVES: HIV-controllers spontaneously maintain HIV viremia at an undetectable level. We aimed to describe the delay to control from seroconversion, the duration of control, and risk factors for losing control. METHODS: HIV-controllers were identified from a pooled dataset of 24 seroconverter cohorts from Europe, Australia, and Canada (CASCADE). HIV-controllers had at least five consecutive viral loads less than 400/500 copies/ml, while antiretroviral therapy naive, for at least 5 years after seroconversion. End of control was defined as two consecutive viral loads above 2000 copies/ml. Duration of control was described using Kaplan-Meier estimates; factors associated with duration of control were identified using a Cox model. CD4⁺ cell count evolution during control was described using a mixed model. RESULTS: Of 9896 eligible seroconverters, we identified 140 (1.4%) HIV-controllers, the largest database of HIV-controllers followed from seroconversion. For 64 with viral load measured within 24 months from seroconversion, median delay to control was 16.7 (interquartile range: 7.8-37.9) months. Probability of maintaining control 20 years after seroconversion was 0.74 [95% confidence interval (CI): 0.64-0.85]. Occurrence of blips followed by return to undetectability did not increase the risk of loss of control [hazard ratio: 0.81 (95% CI: 0.10-6.70)]. However, CD4⁺ cell loss during control was significantly accelerated in individuals with blips. CONCLUSION: In most individuals, control occurred rapidly after seroconversion; however, more than 3 years were required to achieve control in 25% of HIV-controllers. Control may be sustained even when CD4⁺ cell levels are below 500 cells/μl, opening important new perspectives to understand the physiopathology underlying control.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".