Type-specific concurrent anogenital HPV detection among young women and MSM attending Dutch sexual health clinics
Bibliographic record
Abstract
OBJECTIVES: This study aimed to investigate type-specific concurrent anogenital human papillomavirus (HPV) detection and examine associations with concurrent detection. METHODS: Data from a Dutch repeated cross-sectional study among young sexual health clinic visitors (Papillomavirus Surveillance among STI clinic Youngsters in the Netherlands) between 2009 and 2019 were used. Cohen's kappa was used to assess the degree of type-specific concordance of HPV detection between anal and genital sites for 25 HPV genotypes for women and men who have sex with men (MSM) separately. Associations with type-specific concurrent HPV were identified. Receptive anal intercourse (RAI) was forced into the model to investigate its influence. RESULTS: Among women (n=1492), type-specific concurrent anogenital detection was common; kappa was above 0.4 for 20 genotypes. Among MSM (n=614), kappa was <0.4 for all genotypes. The only significant association with type-specific concurrent anogenital detection among women was genital chlamydia (adjusted OR 1.5, 95% CI 1.1 to 2.2). RAI was not associated. CONCLUSIONS: Type-specific concurrent anogenital HPV detection was common among young women, and uncommon among MSM. For women, concurrent HPV detection was associated with genital chlamydia. Our results are suggestive of autoinoculation of HPV among women.
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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 | 0.005 |
| 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 | 0.000 | 0.001 |
| 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".