Human Papillomavirus Persistence, Recurrence, and Incidence in Early Childhood
Bibliographic record
Abstract
BACKGROUND: Little is known on the vertical transmission of human papillomavirus (HPV) and on the dynamics of HPV among children. Our objective was to determine the risk of HPV recurrence, persistence, and incidence over 2 years of age among children born to HPV-positive mothers. METHODS: We conducted the HERITAGE study among pregnant women recruited between 2010 and 2016 in Canada. HPV DNA testing was done on vaginal samples collected during the first and third trimesters of pregnancy, and on conjunctival, oral, pharyngeal, and genital samples collected in children from birth and at every 3-6 months up to 2 years. We estimated the probability of HPV vertical transmission, and of HPV recurrence, persistence, and incidence among children during follow-up. Time to clear HPV among children was estimated using Kaplan-Meier technique. RESULTS: Among the 422 women with HPV during pregnancy, 390 carried pregnancy to term, and 395 children were born alive including twins/triplets. HPV vertical transmission was estimated at 7.3% (95% confidence interval [CI], 5.0%-10.4%) with a genotype concordance of 85.2%. During the entire follow-up, we observed 91 HPV detections (among 51 children) including 2 recurrent and 1 persistent. Incident genotypes occurred in 26 of the 270 (9.6%) children with valid HPV testing during follow-up. Most HPV infections detected in children cleared with a mean time of 3.9 months (95% CI, 3.6-4.2 months). CONCLUSIONS: HPV vertical transmission and incident HPV occasionally occur during infancy, but the risk of persistence or recurrence is overall very low.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".