Effectiveness of Latent TB Screening and Treatment in People Initiating Dialysis in British Columbia, Canada
Bibliographic record
Abstract
Background: People undergoing chronic dialysis are at an increased risk of active tuberculosis (TB). In 2012, the Canadian province of British Columbia began systematically screening people initiating dialysis for latent TB using interferon-gamma release assay (IGRA), and treating when appropriate. Objective: The objective of this study was to compare active TB rate in people who initiated dialysis and were screened using an IGRA compared with those not screened during the same period. Design: Retrospective cohort study. Setting: British Columbia (BC), a Canadian province of 5.0 million people with an active TB incidence of 5.1 per 100 000 population. Participants: All people in BC who initiated at least 90 days of dialysis between January 2012 and May 2017 were included in the study. People were excluded if they were <18 years of age or had a prior history of active TB diagnosis or treatment for latent TB. Methods: A retrospective cohort was created of British Columbians who initiated dialysis between 2012 and 2017. Individuals were stratified into a screened and nonscreened group. Multivariable Cox regression was used to determine the association between latent TB screening and the development of active TB. The primary outcome was incident active TB, either microbiologically confirmed or clinically diagnosed. Results: Of the 3190 people included in the study, 1790 (56.1%) were screened, of which 152 (8.5%) initiated latent TB treatment postscreening. During follow-up, incident active TB was diagnosed in 6 (0.3%) of the 1790 people screened, compared with 11 (0.8%) of the 1400 people who received no screening. In multivariable analysis, latent TB screening and treatment was associated with a significant reduction in the rate of active TB (adjusted hazard ratio = 0.3, 95% confidence interval = 0.1-0.8; P < .01). Limitations: This was an observational retrospective study and the potential for unmeasured confounding should be carefully assessed. Conclusions: These findings suggest that systematically screening and treating people initiating dialysis can significantly decrease the rate of active TB in this high-risk population. Given the importance of screening high-risk groups, the results from this analysis could inform scale-up of TB screening in dialysis programs in other low incidence regions. Trial registration is not applicable as this was a retrospective cohort analysis and not a randomized trial.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".