Determinants of Low-Risk and High-Risk Cervical Human Papillomavirus Infections in Montreal University Students
Bibliographic record
Abstract
BACKGROUND: Previous studies have been inconsistent about the degree of sexual transmissibility of cervical human papillomavirus (HPV) infection. The authors hypothesize that risk factors for HPV infection vary according to HPV type. GOAL: To estimate the prevalence of HPV infection in asymptomatic women and to identify risk factors for overall HPV infection and HPV infection by oncogenic and nononcogenic type. STUDY DESIGN: A cross-sectional survey was conducted at the McGill University clinic in Montreal. Cervical specimens were collected from 489 female students presenting at the clinic for a routine Papanicolaou test. Data on potential risk factors was obtained by questionnaire. Human papillomavirus DNA was detected by the polymerase chain reaction using consensus primers (MY09/11) followed by hybridization with generic and type-specific probes using Southern blot and dot blot techniques. RESULTS: The overall HPV prevalence was 21.8%. A low-risk HPV infection was found in 6.2% of the women, 11.8% had a high-risk HPV infection (types 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58), 7.1% had an unknown HPV type, and 2.7% had a multiple type infection. Two profiles emerged for sexual activity and risk of HPV infection according to oncogenic risk after multivariate analysis. Lifetime frequency of sexual intercourse and lifetime number of oral sex partners was associated with high-oncogenic-risk HPV infections; however, HPV infection with low-oncogenic-risk types was invariant with respect to markers of sexual activity. CONCLUSION: These results suggest that there are differences in epidemiologic correlates of transmission between low-risk and high-oncogenic-risk HPV types based on oncogenicity. This finding has important implications for primary prevention of HPV infection and cervical cancer precursors.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".