Levofloxacin versus placebo for the treatment of latent tuberculosis among contacts of patients with multidrug-resistant tuberculosis (the VQUIN MDR trial): a protocol for a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Treatment of latent tuberculosis infection (LTBI) plays a substantial role in the prevention of drug-susceptible tuberculosis (TB). However, clinical trials to evaluate the efficacy of preventive therapy for presumed multidrug-resistant (MDR) LTBI are lacking. This trial aims to evaluate the efficacy of the antibiotic levofloxacin in preventing the development of active TB among latently infected contacts of index patients with MDR-TB. METHODS AND ANALYSIS: A double-blind placebo-controlled parallel group randomised controlled trial will be conducted in 10 provinces of Vietnam. Household contacts living with patients with bacteriologically confirmed rifampicin-resistant or MDR-TB will be eligible for recruitment if they have a positive tuberculin skin test or are known to be immunosuppressed, and do not have active TB. Participants will be randomised to receive either levofloxacin or placebo tablets once per day for 6 months. Screening for incident TB will be performed at 6 months intervals. The primary study outcome is the incidence of bacteriologically confirmed TB within 30 months after randomisation. Analysis will be by intention to treat, using Poisson regression. ETHICS: Ethical approval from the University of Sydney Human Research Ethics Committee was obtained on 29 April 2015 (2014/929), and from the Vietnam Ministry of Health Institutional Review Board on 30 September 2015 (4040/QD-BYT). DISSEMINATION: Findings of the study will be published in peer-reviewed publications and conference presentations. TRIAL REGISTRATION NUMBER: ACTRN12616000215426.
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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 | 0.051 | 0.046 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.060 | 0.010 |
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".