Infecting HIV-1 Subtype Predicts Disease Progression in Women of Sub-Saharan Africa
Bibliographic record
Abstract
INTRODUCTION: Long-term natural history cohorts of HIV-1 in the absence of treatment provide the best measure of virulence by different viral subtypes. METHODS: Newly HIV infected Ugandan and Zimbabwean women (N=303) were recruited and monitored for clinical, social, behavioral, immunological and viral parameters for 3 to 9.5years. RESULTS: Ugandan and Zimbabwean women infected with HIV-1 subtype C had 2.5-fold slower rates of CD4 T-cell declines and higher frequencies of long-term non-progression than those infected with subtype A or D (GEE model, P<0.001), a difference not associated with any other clinical parameters. Relative replicative fitness and entry efficiency of HIV-1 variants directly correlated with virulence in the patients, subtype D>A>C (P<0.001, ANOVA). DISCUSSION: HIV-1 subtype C was less virulent than either A or D in humans; the latter being the most virulent. Longer periods of asymptomatic HIV-1 subtype C could explain the continued expansion and dominance of subtype C in the global epidemic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".