The prevalence of human papillomavirus in pediatric tonsils: A systematic review of the literature
Bibliographic record
Abstract
BACKGROUND: HPV-related head and neck cancer rates have been increasing in recent years, with the tonsils being the most commonly affected site. However, the current rate of HPV infection in the pediatric population remains poorly defined. The objective of this study was to systematically review and evaluate the prevalence and distribution of HPV in the tonsils of pediatric patients undergoing routine tonsillectomy. METHODS AND RESULTS: The literature was searched using PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, and ProQuest Dissertations & Theses Global databases (inception to December 2017) by two independent review authors. Inclusion criteria included articles which evaluated the prevalence of HPV in a pediatric cohort without known warts or recurrent respiratory papillomatosis, those which used tonsil biopsy specimens for analysis, and those with six or more subjects and clear outcomes reported. Eleven studies met the inclusion criteria. Using the Oxford Clinical Evidence-based Medicine (OCEBM) guidelines, two reviewers appraised the level of evidence of each study, extracted data, and resolved discrepancies by consensus. The systematic review identified 11 articles (n = 2520). Seven studies detected HPV in the subject population, with prevalence values ranging from 0 to 21%. The level of evidence for all included studies was OCEBM Level 3. CONCLUSIONS: HPV may be present in pediatric tonsillectomy specimens; however, the largest included study demonstrated a prevalence of 0%. Future testing should be performed using methods with high sensitivities and specificities, such as reverse transcript real-time PCR or digital droplet PCR.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".