Cervical cancer screening uptake among HIV-positive women in Ontario, Canada: A population-based retrospective cohort study
Bibliographic record
Abstract
Cervical cancer caused by oncogenic types of the human papillomavirus (HPV) is of concern among HIV-positive women due to impairment of immune responses required to control HPV infection. Our objectives were to describe patterns of cervical cancer screening using Pap cytology testing among HIV-positive women in Ontario, Canada from 2008 to 2013 and to identify factors associated with adequate screening. We conducted a retrospective, population-based cohort study among screen-eligible HIV-positive women using provincial administrative health data. We estimated annual proportions tested and reported these with 95% confidence intervals (CI). Next, using person-years as the unit of analysis, we identified factors associated with annual Pap testing using log-binomial regression. A total of 2271 women were followed over 10,697 person-years. In 2008, 34.0% (95%CI 31.1-37.0%) had a Pap test. By 2013, the proportion of HIV-positive women tested was 25.9% (95%CI 23.6-28.2%). Women who were most likely to undergo testing were younger, were immigrants from countries with generalized HIV epidemics, lived in the highest income neighbourhoods, had a female primary care physician, had two or more encounters per year with an infectious disease or internal medicine specialist, and had greater comorbidity. Nearly three in four HIV-positive women were under-screened despite all having universal insurance for medically-necessary services. Annual Pap testing decreased following the 2011-2013 release of new guidelines for a lengthened screen interval for average risk women and a billing disincentive. Clinic-based intervention such as physician alerts or reminders may be needed to improve screening coverage among HIV-positive women.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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 teacher head, 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".