Factors Associated With Tuberculosis Infection Among Household Contacts of Patients With Multidrug-Resistant Tuberculosis in 10 Provinces of Vietnam: A Cross-Sectional Study
Bibliographic record
Abstract
Abstract Background: In 2021, an estimated 450 000 incident people developed Rifampicin-resistant (RR) or multidrug-resistant (MDR)-TB (defined as resistance to both rifampicin and isoniazid) worldwide. Given that the commonly used rapid molecular diagnostic test, GeneXpert, only detect resistance, programmatic reporting groups MDR/RR-TB together. Household contacts (HHCs) of a patient with active MDR/RR-TB are at high risk for a TB infection (TBI) and disease, as they have a prolonged exposure to the index cases. This study aimed to establish the prevalence of TBI and factors associated with TB infection among HHCs. Methods: A cross-sectional survey was conducted among close contacts of patients with MDR/RR-TB, who participated in screening for TB infection, as a part of the VQUIN multidrug-resistant tuberculosis (MDR-TB) trial. TBI status was defined based upon a tuberculin skin test result (TST) of at least 10mm. Logistic regression was used to evaluate the relationship between the characteristics of HHCs or the index case, and HHCs with positive TST. The primary outcome was the prevalence of TBI amongst the HHCs, and the risk factors associated with TBI in this population. Results: 3823 HHCs of 1758 MDR/RR-TB index cases participated in screening. The prevalence of TB infection at baseline was 71.2%, comprising 2438 (63.8%) individuals with baseline positivity, and an additional 283 (7.4%) demonstrating TST conversion after 8-12 weeks. Factors associated with a positive TST in the multivariable model included, HHCs with older age groups had a higher prevalence of infection. Other factors associated with an increased prevalence of infection included: normal BMI (aOR = 1.33, 95% CI: 1.06-1.66), smoking history (aOR = 1.76, 95% CI: 1.39-2.23), a prior history of TB (aOR = 4.56, 95% CI: 2.49-8.35), the presence of a BCG scar (aOR = 1.23, 95% CI: 1.02-1.50 ), and more than eight hours spent each day on average over the previous three months with the index patient (aOR = 1.52, 95% CI: 1.28-1.81). Conclusion: This study identified that HHCs amongst the MDR/RR-TB patients had a high TBI prevalence and identified a number of risk factors of contracting TBI. Evidence for the effectiveness of preventive therapy to treat TB infection in MDR/RR-TB contacts is urgently needed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".