Prevalence of HIV-1 resistant to antiretroviral drugs in 81 individuals newly infected by sexual contact or injecting drug use
Bibliographic record
Abstract
OBJECTIVE: Prolonged treatment with antiretroviral drugs results in the selection of HIV-1 variants with mutations conferring resistance to nucleoside and non-nucleoside reverse transcriptase inhibitors (NRTI and NNRTI) or to protease inhibitors (PI). There is serious concern about transmission of resistant viruses to newly infected persons. This study monitored the prevalence of resistant viruses in individuals undergoing primary HIV infection. DESIGN: Resistance testing was performed on 81 individuals infected between 1997 and 1999 by injecting drug use (n =21), sexual (n = 56), or unknown (n = 4) transmission. METHODS: Automated sequencing was used to genotype the reverse transcriptase (RT) and protease regions of virus isolated from patients' plasma. The phenotypic susceptibility of stimulated peripheral blood mononuclear cells to antiretroviral drugs was assayed. Line probe assays detected quasispecies variations in wild-type and mutated RT codons. RESULTS: A high prevalence of PI and RT genotypic variants, associated with high-level resistance to antiretroviral drugs, was observed in individuals newly infected by injecting drug use (PI = 24%, RT = 24%) or sexual transmission (PI = 12%, RT = 22%). The PI mutations, L101, V82A, and L90M, were found in 10.5, 3 and 4% of cases, respectively; whereas for RT, primary mutations at positions T215Y (zidovudine), M184V (lamivudine), T69D/A (zalcitabine), and K103N (multi-NNRTI) were present in 8, 5, 4, and 4% of subjects, respectively. Resistance to NRTI was demonstrated by phenotypic, genotypic, and line probe analyses. Transmission of multidrug (NRTI/NNRTI/PI) resistance in eight subjects (9.9%) was confirmed by showing that source partners possessed viruses of similar genotype. CONCLUSIONS: The transmission of drug-resistant HIV is a serious problem that merits further attention by public health officials as well as virologists and clinicians.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".