Antiretroviral-Drug Resistance among Patients Recently Infected with HIV
Bibliographic record
Abstract
BACKGROUND: Among persons in North America who are newly infected with the human immunodeficiency virus (HIV), the prevalence of transmitted resistance to antiretroviral drugs has been estimated at 1 to 11 percent. METHODS: We performed a retrospective analysis of susceptibility to antiretroviral drugs before treatment and drug-resistance mutations in HIV in plasma samples from 377 subjects with primary HIV infection who had not yet received treatment and who were identified between May 1995 and June 2000 in 10 North American cities. Responses to treatment could be evaluated in 202 subjects. RESULTS: Over the five-year period, the frequency of transmitted drug resistance increased significantly. The frequency of high-level resistance to one or more drugs (indicated by a value of more than 10 for the ratio of the 50 percent inhibitory concentration [IC50] for the subject's virus to the IC50 for a drug-sensitive reference virus) increased from 3.4 percent during the period from 1995 to 1998 to 12.4 percent during the period from 1999 to 2000 (P=0.002), and the frequency of multidrug resistance increased from 1.1 percent to 6.2 percent (P=0.01). The frequency of resistance mutations detected by sequence analysis increased from 8.0 percent to 22.7 percent (P<0.001), and the frequency of multidrug resistance detected by sequence analysis increased from 3.8 percent to 10.2 percent (P=0.05). Among subjects infected with drug-resistant virus, the time to viral suppression after the initiation of antiretroviral therapy was longer (P=0.05), and the time to virologic failure was shorter (P=0.05). CONCLUSIONS: The proportion of new HIV infections that involve drug-resistant virus is increasing in North America. Initial antiretroviral therapy is more likely to fail in patients who are infected with drug-resistant virus. Testing for resistance to drugs before therapy begins is now indicated even for recently infected patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".