The prevalence of human papillomavirus and its impact on cervical dysplasia in Northern Canada
Bibliographic record
Abstract
INTRODUCTION: Certain types of the Human Papillomavirus (HPV) are sexually transmitted and highly associated with development of cervical dysplasia and cervical cancer but the distribution of HPV infection in the North, particularly amongst First Nations, Metis, and Inuit peoples, is little known. The purposes of the study are to identify the prevalence of type-specific HPV infections and the association of different HPV types with cervical dysplasia among women in Northern Canada. METHODS: This was a cross-sectional study with attendants of the routine or scheduled Pap testing program in the Northwest Territories (NWT), Nunavut, Labrador and Yukon, Canada. Approximately half of each sample was used for Pap test and the remaining was used for HPV genotyping using a Luminex-based method. Pap test results, HPV types, and demographic information were linked for analyses. RESULTS: Results from 14,598 specimens showed that HPV infection was approximately 50% higher among the Aboriginal than the non-Aboriginal population (27.6% vs. 18.5%). Although the most common HPV type detected was HPV 16 across region, the prevalence of other high risk HPV types was different. The age-specific HPV prevalence among Aboriginal showed a 'U' shape which contrasted to non-Aboriginal. The association of HPV infection with cervical dysplasia was similar in both Aboriginal and non-Aboriginal populations. CONCLUSIONS: The HPV prevalence was higher in Northern Canada than in other Areas in Canada. The prevalence showed a higher rate of other high risk HPV infections but no difference of HPV 16/18 infections among Aboriginal in comparison with non-Aboriginal women. This study provides baseline information on HPV prevalence that may assist in surveillance and evaluation systems to track and assess HPV vaccine programs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".