Advances in Human Immunodeficiency Virus Therapeutics
Bibliographic record
Abstract
OBJECTIVE: To review recent advances in the management of persons infected with HIV. DATA SOURCES: A MEDLINE search (March 2003-February 2006) was done to identify recent articles on antiretroviral therapy research, adverse effects, and investigational products. Abstracts and programs of major HIV conferences, held from January 2003 to June 2005, were also reviewed for relevant material. STUDY SELECTION AND DATA EXTRACTION: Studies and observations conducted with either recently approved or investigational products were selected for inclusion, with conference abstracts primarily used. Excluded were topics covered in recent publications in The Annals. DATA SYNTHESIS: New modalities for treating HIV, including the CXCR4 and CCR5 receptor inhibitors, have so far shown promise in trial. Tipranavir, a recently approved protease inhibitor, has been shown to be effective in highly resistant patients, but may be unable to be combined with other protease inhibitors. Once-daily emtricitabine and tenofovir have shown superiority compared with lamivudine and zidovudine as backbone nucleoside analogs for combination antiretroviral therapy. Pharmacokinetic considerations for age, gender, race, and which agents are being discontinued have emerged. CONCLUSIONS: Much progress has been made in the treatment of HIV infection. Tolerability and adherence remain major obstacles to optimizing regimen longevity.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".