Human papillomavirus intermittence, redetections, and associated risk of cytological abnormalities in the Ludwig-McGill cohort study of adult women
Bibliographic record
Abstract
Abstract Introduction We assessed the incidence of redetection with the same human papillomavirus (HPV) genotype, predictors of first HPV detections and redetections, and prevalence of cytological lesions during HPV redetections. Methods The Ludwig-McGill cohort study followed women aged 18-60 years from São Paulo, Brazil in 1993-1997 for up to 10 years. Women provided cervical samples for cytology testing and HPV DNA testing at each visit. A redetection was defined as a recurring genotype-specific HPV positive result after one or more intervening negative visits. Predictors of genotype-specific redetection were assessed using adjusted hazard ratios (aHR) with Cox regression modeling. Results 2184 women contributed 2368 incident HPV genotype-specific first detections and 308 genotype-specific redetections over a median follow-up of 6.5 years. The cumulative incidence of redetection with the same genotype was 7% at 1 year and 15% at 5 years after the loss of positivity of the first detection. Neither age (aHR 0.90, 95%CI 0.54-1.47 for ≥45y vs. <25y) nor new sexual partner acquisition (aHR 0.98, 95%CI 0.70-1.35) were statistically associated with genotype-specific redetection. High-grade squamous intraepithelial lesion prevalence was similar during first HPV detections (2.9%) and redetection (3.2%). Conclusions Our findings suggest many HPV redetections were likely reactivations of latent recurring infections.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".