The natural history and epidemiology of cervical human papillomavirus infections in Montreal university students
Bibliographic record
Abstract
Introduction. Only a small proportion of women with oncogenic HPV infections will eventually progress to high-grade squamous intraepithelial lesions (HSIL) or invasive cervical cancer (ICC), although the reasons why are not well understood. Additional knowledge about viral transmission and persistence is still needed, since some studies have shown that certain environmental co-factors, such as previous STDs or alcohol use may facilitate the sexual transmission of HPV or the persistence of an established HPV infection. The objectives of this study were to: 1) Describe the incidence and clearance rates of type-specific HPV infections; 2) Identify determinants of high- (HR) and lowrisk (LR) HPV acquisition and clearance, and; 3) Identify viral determinants of low-grade squamous intraepithelial lesions (LSIL). Methodology. In a prospective cohort of 621 Montreal university students, cervical specimens were collected for cytology and HPV DNA detection. Information on potential risk factors was obtained by interview at baseline, and at return visits. Follow-up visits were scheduled every 6 months over 2 years, for a total of 5 visits. Results. The two-year cumulative incidence of any HPV infection was 36% and the mean duration of an episode with a type-specific HR- or LR-HPV infection was 16.3 and 13.4 months, respectively. After adjusting for age and sexual activity, co-factors for HPV acquisition included a recent Chlamydia infection, oral contraceptive use, alcohol use and washing after sex. Some determinants of HPV clearance included tobacco and alcohol use, in addition to use of tampons, daily vegetable consumption and condom use. Slightly different sets of the aforementioned co-factors or predictors were observed for HR- and LR-HPV infections. Non-European HPV 16 or -18 variants appear to be strongly associated with incident low-grade squamous intraepithelial lesion (LSIL). Conclusion. HPV infections occurred frequently in this cohort, and 24% or 12% of the women remained positive after 24 months with an incident type-specific HR- or LR-HPV infection. Some modifiable co-factors, independent of sexual activity, may facilitate transmission or persistence of certain HPV infections. These results may have implications for public health education and cervical cancer screening programmes.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".