Increased regression and decreased incidence of human papillomavirus-related cervical lesions among HIV-infected women on HAART
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of HAART on incidence, regression, and progression of cytopathological abnormalities in HIV-infected women. DESIGN: Prospective cohort. METHODS: HIV-infected women (N=1123) from Soweto, South Africa underwent serial cervical smears that were analyzed and reported using the Bethesda System. The results of HAART and non-HAART users were compared using two statistical approaches: a survival analysis assessing risk of incident smear abnormality among women with baseline normal smear results; and analysis with marginal models assessing for an association between HAART use and likelihood of regression/progression in consecutive smears. RESULTS: After multivariate survival analysis, women using HAART with a normal baseline smear were 38% less likely to have an incident smear abnormality during follow-up than nonusers [confidence interval (CI) 0.42-0.91; P=0.01]. Multivariate marginal models analysis identified a significantly increased likelihood (odds ratio 2.61; CI 1.75-3.89; P<0.0001) of regression of cervical lesions among women on HAART. CONCLUSION: Our large prospective cohort study adds significant weight to the side of the balance of clinical research supporting the positive impact of HAART on the natural history of human papillomavirus-related cervical disease in HIV-infected women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.005 | 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 teacher head, 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".