Antiretroviral Resistance among HIV‐Infected Persons Who Have Died in British Columbia, in the Era of Modern Antiretroviral Therapy
Bibliographic record
Abstract
BACKGROUND: The prevalence of antiretroviral resistance among persons enrolled in the centralized HIV/AIDS Drug Treatment Program in British Columbia, Canada, who had died between July 1997 and December 2001, was investigated, to determine the degree to which antiretroviral resistance contributed to mortality. METHODS: During this period, 637 deaths had occurred. The last plasma sample obtained during therapy was genotyped retrospectively for treated individuals who had died of a nonaccidental cause. Samples with plasma human immunodeficiency virus (HIV) loads <500 copies/mL were not genotyped. Drug resistance among 1220 living HIV-infected persons who had experienced virologic therapy failure during the study period also was examined. RESULTS: Of 554 individuals who had died of nonaccidental causes, 58 (10.4%) were antiretroviral naive, and 99 (17.9%) had very brief exposure to antiretroviral therapy (median, 2 months). The majority of isolates from the remaining 397 individuals harbored either no major resistance mutations or represented samples with plasma HIV suppression of <500 copies/mL. Resistance to >/=1, >/=2, or 3 drug classes was observed in 76%, 42%, and 11% of individuals, respectively, in the group of 1220 living individuals experiencing virologic therapy failure, compared with only 44%, 23%, and 5% of individuals, respectively, who had died (P<.001). CONCLUSION: Only a relatively low prevalence of multidrug resistance was observed in this cohort, indicating that the exhaustion of treatment options because of drug resistance was not a significant contributor to mortality.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".