Grassroots Partnership to See and Treat Cervical Cancer in Rural Uganda
Bibliographic record
Abstract
Abstract 9 Background: In Uganda, cervical cancer is the leading cause of cancer death, affecting 45 in every 100,000 women annually and killing 25 in every 100,000 annually. To effect change, two Canadian registered charities partnered with a Ugandan nongovernmental organization, a university, and the Ministry of Health to develop a novel screening, treatment, and educational training program. The two major goals of our program were to develop a training program for health care providers in southwestern Uganda for visual inspection of the cervix with acetic acid (VIA) and a cryotherapy see and treat model; and to implement the first cervical cancer screening program of its kind in the Kabale region of southwestern Uganda. Methods: Our program was developed in partnership with Mbarara University of Science and Technology, a grass-roots Ugandan community development organization (Kigezi Healthcare Foundation [KIHEFO]), a Canadian charity that is focused on providing medical and dental care and educational training and infrastructure development (Bridge to Health Medical and Dental), and a Canadian charity that is focused on treatment for advanced cervical cancer (Road to Care). Results: Requisite supplies were obtained by Bridge to Health Medical and Dental and left behind with KIHEFO. A partnership was formed between academia, government, and civil society across Canada and Uganda. Over 5 days, 15 Ugandan health care workers were trained in VIA and cryotherapy, and 96 patients were screened for cervical cancer. Six patients were successfully treated for precancerous lesions. One biopsy was sent for pathology review and analysis. Conclusion: Since the pilot program, KIHEFO has conducted two additional cervical cancer screening programs using VIA and the see and treat approach. A new cervical cancer screening and treatment campaign, along with a quality control and educational training refresher, for the original 15 health care providers is planned for February 2017. Funding: Bridge to Health Medical and Dental and Kigezi Healthcare Foundation in partnership with the Ugandan Ministry of Health. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST No COIs from the authors.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".