Safety of prolonged treatment with bedaquiline in programmatic conditions
Bibliographic record
Abstract
Bedaquiline is now considered a first-line medicine for treatment of rifampicin-resistant tuberculosis (RR-TB). We evaluated the safety of treatment with bedaquiline for longer than 190 days in individuals with RR-TB under programmatic conditions. In a prospective cohort study enrolling pulmonary RR-TB patients, we initiated bedaquiline-based treatment at a tertiary hospital in Belarus. We defined standard bedaquiline use as <190 days and prolonged as ≥190 days. We recorded adverse events (AEs) and classified their seriousness and relation to bedaquiline. Our primary outcome in regression analyses was the incidence of serious AEs occurring within 5 months of bedaquiline cessation. We used generalised estimating equations to estimate the adjusted incidence rate ratio (aIRR) of serious AEs between the prolonged and standard bedaquiline groups. We enrolled 113 patients, 83 (73%) of whom received standard and 30 (27%) received prolonged treatment. A total of 2030 AEs occurred during treatment. Of these, 63 (3.1%) were serious AEs occurring within 5 months of bedaquiline cessation; QTcF prolongation was the most common bedaquiline-related serious AE. The incidence of serious AEs per 100 person-months was 5.4 (3.9 to 7.2) in the standard group and 4.4 (2.6 to 7.0) in the prolonged group. In adjusted analyses, serious AEs were no different (aIRR: 0.82, 95% CI 0.42-1.61) in the prolonged group. One patient in the standard bedaquiline group died of acute cardiopulmonary failure deemed possibly related to bedaquiline. Prolonged use of bedaquiline under programmatic conditions appears safe. Clinicians should carefully monitor QTcF interval since its prolongation was commonly observed.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".