Introduction of short course treatment for latent tuberculosis infection at a primary care facility for refugees in Winnipeg, Canada: A mixed methods evaluation
Bibliographic record
Abstract
Background: The World Health Organization (WHO) End TB strategy document 'Toward tuberculosis elimination: an action framework for low incidence countries'-like Canada- identifies screening and treatment of latent tuberculosis infection (LTBI) for groups at increased risk for TB disease as a priority, including newcomers from endemic countries. In 2015, the clients-centered model offered at a primary care facility for refugees, BridgeCare Clinic, Winnipeg, Canada was evaluated. The model included LTBI screening, assessment, and treatment, and originally offered 9-months of isoniazid as treatment. This mixed methods evaluation investigates LTBI program outcomes since the introduction of two short-course treatment regimens: 4-months of rifampin, and 3-months of isoniazid and rifapentine. Methods: This study combined a retrospective analysis of program administrative data with structured interviews of clinic staff. We included LTBI treatment eligibility, the treatment regimen offered, treatment initiation, and completed treatment from January 1, 2015 to August 6, 2020. Results: Seven hundred and one people were screened, and infection rates varied from 34.1% in 2015 to 53.3% in 2020. Most people living with LTBI came from high TB burden countries in Africa and South-East Asia WHO regions and were younger than 45 years old. Treatment eligibility increased 9% (75% in 2015 to 86% in 2016-2020) and most people diagnosed with LTBI took the short course treatments offered. There was an increase of 14.5% in treatment initiation (75.6 vs. 90.1%), and an increase of 8% in treatment completion (82.4 vs. 90.4%) after short-course regimens were introduced. The final model showed that the treatment regimen tends to affect the frequency of treatment completion, but there are other factors that influence this outcome, in this population. With the new treatments, BridgeCare Clinic achieved the 90% of treatment coverage, and the 90% treatment completion rate targets recommended in the End TB Strategy. Qualitative interviews with clinic staff further affirm the higher acceptability of the new treatments. Conclusion: While these results are limited to government-sponsored refugees in Winnipeg, they highlight the acceptability and value of short-course LTBI treatment as a possibility for reaching End TB targets in primary care settings.
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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 | 0.027 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".