CD4+ and viral load outcomes of antiretroviral therapy switch strategies after virologic failure of combination antiretroviral therapy in perinatally HIV-infected youth in the United States
Bibliographic record
Abstract
OBJECTIVE: This study compared 12-month CD4 and viral load outcomes in HIV-infected children and adolescents with virological failure, managed with four treatment switch strategies. DESIGN: This observational study included perinatally HIV-infected (PHIV) children in the Pediatric HIV/AIDS Cohort Study (PHACS) and Pediatric AIDS Clinical Trials (PACTG) Protocol 219C. METHODS: Treatment strategies among children with virologic failure were compared: continue failing combination antiretroviral therapy (cART); switch to new cART; switch to drug-sparing regimen; and discontinue all ART. Mean changes in CD4% and viral load from baseline (time of virologic failure) to 12 months follow-up in each group were evaluated using weighted linear regression models. RESULTS: Virologic failure occurred in 939 out of 2373 (40%) children. At 12 months, children switching to new cART (16%) had a nonsignificant increase in CD4% from baseline, 0.59 percentage points [95% confidence interval (95% CI) -1.01 to 2.19], not different than those who continued failing cART (71%) (-0.64 percentage points, P = 0.15) or switched to a drug-sparing regimen (5%) (1.40 percentage points, P = 0.64). Children discontinuing all ART (7%) experienced significant CD4% decline -3.18 percentage points (95% CI -5.25 to -1.11) compared with those initiating new cART (P = 0.04). All treatment strategies except discontinuing ART yielded significant mean decreases in log10VL by 12 months, the new cART group having the largest drop (-1.15 log10VL). CONCLUSION: In PHIV children with virologic failure, switching to new cART was associated with the best virological response, while stopping all ART resulted in the worst immunologic and virologic outcomes and should be avoided. Drug-sparing regimens and continuing failing regimens may be considered with careful monitoring.
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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 | 0.003 |
| 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 | 0.001 |
| 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 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".