Incidence and duration of human papillomavirus infections in young women: insights from a bimonthly follow-up cohort
Bibliographic record
Abstract
BACKGROUND: We studied the duration of HPV detection and risk of (re-) detection for 25 HPV genotypes in a cohort of 132 women followed every eight weeks for up to two years between 2016 and 2020. Participants were between 18 and 25 years old at inclusion and half of them were vaccinated against HPV. They were recruited near the University and the STI detection centre in Montpellier, France. METHODS: We used genotype-specific longitudinal data to characterise the dynamics of HPV-detected episodes. We investigated the contribution of viral and host factors to the variations in the duration of HPV detection, and the time before (re-)detection of the same genotype using multivariate Cox regression models with frailty at the patient level. FINDINGS: We detected at least one HPV episode in 74% of the participants and re-detected the same genotype in 47% of them. Covariates related to socio-economic difficulties were associated with a lower risk of detectability loss (hazard ratio 0.45 with a 95% confidence interval, CI, from 0.21 to 0.97). The number of lifetime sexual partners was strongly associated with an increased risk of new positive detection (hazard ratio 2.40 with a 95%CI from 1.07 to 5.39). In contrast, vaccination was associated with a lower risk of displaying incident infections (hazard ratio of 0.64 with a 95%CI from 0.43 to 0.96). CONCLUSION: In the short term, vaccination shows clear signs of protection against new HPV detections, including for some genotypes not targeted by the vaccine, such as HPV31 and HPV51.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".