Alarming Tuberculosis Rate Among People Who Inject Drugs in Vietnam
Bibliographic record
Abstract
BACKGROUND: The tuberculosis (TB) epidemic is not homogeneous in the general population but presents high-risk groups. People who inject drugs (PWID) are such a group. However, TB among PWID remains largely undocumented. Our goal was to assess the prevalence of TB and the risk factors associated with TB among PWID in Vietnam. METHODS: We implemented a cross-sectional survey among 2 community-based cohorts of human immunodeficiency virus (HIV)-positive and HIV-negative PWID in Hai Phong. Participants were screened for TB using questions on TB symptoms. Those who reported any symptom were accompanied by peers to the TB clinic for chest x-ray. If the latter was abnormal, a sputum was collected to perform an Xpert MTB/RIF test. RESULTS: A total of 885 PWID were screened for TB. For both cohorts, most PWID were male (>90.0%), with a median age of 42 years. Beside heroin injection, 52.5% of participants reported smoking methamphetamine, and 63.2% were on methadone. Among HIV-positive PWID (N = 451), 90.4% were on antiretroviral therapy and 81.6% had a viral load <1000 copies/mL. Using a complete-case analysis, the estimated TB prevalence was 2.3% (95% confidence interval [CI], 1.0-4.5) and 2.1% (95% CI, 0.8-4.2) among HIV-positive and HIV-negative people, respectively. Living as a couple, arrest over the past 6 months, homelessness, and smoking methamphetamine were independently associated with TB but not HIV infection. CONCLUSIONS: In the context of very large antiretroviral therapy coverage, this extremely high rate of TB among PWID requires urgent actions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".