Reproductive and genital health and risk of cervical human papillomavirus infection: results from the Ludwig-McGill cohort study
Bibliographic record
Abstract
BACKGROUND: There are inconsistencies in the literature on reproductive and genital health determinants of human papillomavirus (HPV) infection, the primary cause of cervical cancer. We examined these factors in the Ludwig-McGill Cohort Study, a longitudinal, repeated-measurements investigation on the natural history of HPV infection. METHODS: We analyzed a cohort subset of 1867 women with one complete year of follow-up. We calculated odds ratios (OR) and 95% confidence intervals (CI) for reproductive and genital health characteristics from questionnaire and laboratory data in relation to 1-year period prevalence of HPV infection. Two outcomes were measured; the first based on phylogenetic grouping of HPV types based on tissue tropism and oncogenicity (Alphapapillomavirus Subgenus 1: species 1, 8, 10 and 13; Subgenus 2: species 5, 6, 7, 9, 11; Subgenus 3: species 3, 4 and 14) and the second based on transient or persistent HPV infections. RESULTS: Lifetime (Subgenus 3 OR = 2.00, CI: 1.23-3.24) and current (Subgenus 3 OR =2.00, CI: 1.15-3.47) condom use and use of contraceptive injections (Subgenus 1 OR = 1.96, CI: 1.22-3.16, Subgenus 2 OR = 1.34, CI: 1.00-1.79) were associated with increased risk of HPV infection. Intrauterine device use was protective (Subgenus 1 OR = 0.48, CI: 0.30-0.75, Subgenus 2 OR = 0.78, CI: 0.62-0.98). These factors were not associated with persistence of HPV infection. Tampon use, previous gynecologic infections and cervical inflammation were associated with an overall increased risk of HPV infection. CONCLUSIONS: Cervical HPV infection was associated with reproductive and genital health factors. Further studies are necessary to confirm the low to moderate associations observed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".