Management of paediatric HIV-1 resistance
Bibliographic record
Abstract
PURPOSE OF REVIEW: Children have higher rates of virological failure than adults, often associated with more extensive resistance and limited second-line options. In order to maintain clinical benefits of highly active antiretroviral therapy (HAART) into adulthood, particularly for children starting at a young age, strategies are needed to limit the emergence of resistance and to offer highly effective subsequent lines of therapy. Similarly, well resourced settings face challenges regarding extensive resistance accumulated over the past decade or more, particularly resulting from suboptimal therapies. RECENT FINDINGS: Rates of resistance at failure of nonnucleoside reverse-transcriptase inhibitor based HAART are higher in developing countries than in well resourced settings. In the latter, second-generation protease inhibitors tipranavir and darunavir are promising, with tipranavir now licensed for those above 2 years and darunavir showing good trial results in children above 6 years. However, combination with new classes such as integrase inhibitors (currently in phase I trials) and CCR5 antagonists (no paediatric data yet) will probably be necessary to gain maximal long-term benefits. SUMMARY: Common goals in paediatric HIV for both resource-rich and resource-limited settings are to limit vertical transmission, minimize emergence of resistant viruses in both mother and child where prevention of mother-to-child transmission fails, and limit resistance in children starting HAART. Optimal sequencing of regimens in the absence of resistance testing is a priority research area. Paediatric studies using newer classes of agents are of paramount importance, as well as expanding access to existing antiretrovirals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.005 | 0.002 |
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".