The impact of smoking on adherence to treatment for latent tuberculosis infection
Bibliographic record
Abstract
BACKGROUND: Studies have shown an association between smoking and tuberculosis (TB) infection, disease and TB-related mortality. We hypothesized that smokers with latent tuberculosis infection (LTBI) are less likely to comply with their LTBI treatment regimen, thus increasing their risk of developing active disease. We thus documented the impact of smoking on adherence to LTBI treatment. METHOD: Between 1998 and 2000, a convenience sample of patients undergoing treatment for LTBI completed a questionnaire on smoking status. Level of adherence to LTBI treatment was tested for associations with socio-demographic profile, and smoking status RESULTS: 320 patients were recruited, and 302 (94%) completed the questionnaire. Smoking prevalence was 21%. 72% of patients were adherent to LTBI treatment. Women (OR = 2.0; 95% CI: 1.2-3.3) and non-smokers (OR = 1.8; 95% CI: 1.0-3.3) were associated with adherence to LTBI treatment. Only gender was found as an independent predictor of adherence after adjusting for age and smoking status (OR = 1.9; 95% CI: 1.06-3.3). CONCLUSION: Males and smokers need to have extra supervision to ensure compliance with LTBI treatment.
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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) | 0.000 | 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) | 0.000 | 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".