Efficacy and safety of World Health Organization group 5 drugs for multidrug-resistant tuberculosis treatment
Bibliographic record
Abstract
The efficacy and toxicity of several drugs now used to treat multidrug-resistant tuberculosis (MDR-TB) have not been fully evaluated. We searched three databases for studies assessing efficacy in MDR-TB or safety during prolonged treatment of any mycobacterial infections, of drugs classified by the World Health Organization as having uncertain efficacy for MDR-TB (group 5). We included 83 out of 4002 studies identified. Evidence was inadequate for meropenem, imipenem and terizidone. For MDR-TB treatment, clarithromycin had no efficacy in two studies (risk difference (RD) -0.13, 95% CI -0.40-0.14) and amoxicillin-clavulanate had no efficacy in two other studies (RD 0.07, 95% CI -0.21-0.35). The largest number of studies described prolonged use for treatment of non-tuberculous mycobacteria. Azithromycin was not associated with excess serious adverse events (SAEs). Clarithromycin was not associated with excess SAEs in eight controlled trials in HIV-infected patients (RD 0.00, 95% CI -0.02-0.02), nor in six uncontrolled studies in HIV-uninfected patients, whereas six uncontrolled studies in HIV-infected patients clarithromycin caused substantial SAEs (proportion 0.20, 95% CI 0.12-0.27). For most group 5 drugs we found inadequate evidence of safety for prolonged use or for efficacy for MDR-TB, although macrolides appeared to be safe in prolonged use.
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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 | 0.024 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".