Health service utilisation for anogenital warts in Ontario, Canada prior to the human papillomavirus (HPV) vaccine programme introduction: a retrospective longitudinal population-based study
Bibliographic record
Abstract
OBJECTIVE: Trends in occurrence of anogenital warts (AGWs) can provide early evidence of human papillomavirus (HPV) vaccination programme impact on preventing HPV infection and HPV-induced lesions. The objective of this study was to provide a baseline of AGW epidemiology in Ontario prior to the introduction of the publicly-funded school-based HPV vaccination programme in September 2007. SETTING AND PARTICIPANTS: As a retrospective longitudinal population-based study, we used health administrative data as a proxy to estimate incident AGWs and total health service utilisation (HSU) for AGWs for all Ontario residents 15 years and older with valid health cards between 1 April 2003 and 31 March 2007. OUTCOME MEASURES: The outcome of interest was AGW healthcare utilisation identified using the International Classification of Diseases, 10th revision (ICD-10) diagnostic code for AGWs, as well as an algorithm for identifying AGW physician office visits in a database with a unique system of diagnostic and procedural codes. An AGW case was considered incident if preceded by 12 months without HSU for AGWs. Time trends by age group and sex were analysed. RESULTS: Between fiscal years 2003 and 2006, we identified 123,247 health service visits for AGWs by 51,436 Ontario residents 15 years and older. Incident AGWs peaked in females and males in the 21-23 year age group, at 3.74 per 1000 and 2.81 per 1000, respectively. HSU for AGWs peaked in females and males within the 21-23 year age group, at 9.34 per 1000 and 7.22 per 1000, respectively. CONCLUSIONS: To the best of our knowledge, this is the first population-based study of AGW incidence and HSU in Ontario. The sex and age distribution of individuals with incident and prevalent AGWs in Ontario was similar to that of other provinces before HPV vaccine programme implementation in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".