Prevention of HIV-associated opportunistic infections and diseases in the age of highly active antiretroviral therapy
Bibliographic record
Abstract
Since the introduction of highly active antiretroviral therapy (HAART), the rates of opportunistic infections have decreased markedly as has overall morbidity and mortality from HIV infection in developed countries. However, opportunistic infections remain the most important cause of death in HIV-infected people due to both late presentation of HIV infections and failure of HAART to adequately restore cell-mediated immunity in all individuals. While prophylaxis may be discontinued in patients who have responded to HAART with sustained increases of their CD4 counts above risk thresholds, for those patients who fail HAART, those who are unable to tolerate it, or whose treatments are interrupted, opportunistic-infection prophylaxis remains essential. Some HIV-associated diseases, such as anogenital human papilloma virus-induced neoplasia and hepatitis C infection, have not decreased in frequency with the advent of HAART. For these conditions, effective screening and treatment programs will be necessary to prevent ongoing morbidity. This review will provide an update on HIV-associated opportunistic infections and their prevention in the age of HAART, as well as discuss novel presentations of opportunistic illnesses, such as immune restoration syndromes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".