BCG vaccination and the prevalence of latent tuberculosis infection in an aboriginal population.
Bibliographic record
Abstract
SETTING: Estimations of prevalence of latent tuberculous infection (LTBI) are confounded by factors known to influence the results of the tuberculin skin test (TST) such as age, contact history and bacille Calmette-Guerin (BCG) vaccination. Appropriate interpretation of TST results is necessary to ensure LTBI treatment for those at greatest risk. OBJECTIVE: To document the prevalence of LTBI in Aboriginal people living on a reserve in British Columbia (BC) and to determine the influence of BCG. DESIGN: A population-based, retrospective descriptive analysis of all epidemiological data collected for the on-reserve Aboriginal programme in BC (1951-1996). RESULTS: Of 17615 persons who received a TST during the study period, 42% had received BCG. During the study period, an average of 2517 TSTs were completed per year (SD = 1228) among persons with an average age of 26 years (SD = 16). Among all subjects, the average prevalence of LTBI was 25% (95 %CI 24-25). The presence of BCG (OR = 3.1, 95%CI 2.8-3.4) and multiple BCGs (OR = 10.2, 95%CI 7.7-13.6) were both associated with a positive TST. A positive TST was also associated with a shorter duration in years between the most recent BCG and the TST. CONCLUSION: The average prevalence of LTBI in a sequential sample of Aboriginal people living on a reserve in BC was estimated at 25%. BCG, especially in multiple doses, increased the likelihood of a positive TST.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".