Safety of Triple-Dose Rifampin in Tuberculosis Treatment: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Recent studies suggest that triple-dose rifampin (TDR; ≥30 mg/kg/d) may be unsafe. We updated a systematic review to investigate the safety and efficacy of TDR. METHODS: We searched Embase, MEDLINE, Cochrane CENTRAL, Cochrane Database for Systematic Reviews, and clinicaltrials.gov for randomized, controlled trials from 1 January 1965 to 10 February 2024 that compared standard-dose rifampin (SDR) with TDR and/or double-dose rifampin (DDR) in human tuberculosis treatment. The primary outcome was pooled incidence rate ratio (IRR) of severe adverse events (SevAEs) between participants who received TDR and those who received SDR. Pooled relative risk (RR) of death was a key secondary outcome. Meta-analysis was performed using the inverse variance method. Heterogeneity was assessed using I2, and bias was assessed using Cochrane Risk of Bias 2. The protocol was prospectively registered (osf.io/kfn5a). RESULTS: Of the 11 315 articles identified, 17 met inclusion criteria, enrolling 2313 SDR participants (17 studies), 2238 receiving DDR (12 studies), and 1199 receiving TDR (11 studies). Six studies had a high risk of bias. There was an increase in pooled SevAEs among participants who received TDR compared with those who received SDR (IRR, 1.48; 95% confidence interval [CI], 1.12-1.96; I2, 23%), driven by hepatic events (IRR, 1.96; 95% CI, 1.21-3.18). Death did not differ between participants who received TDR and SDR (RR, 1.19; 95% CI, .71-1.99). One limitation is that only 2 included studies were blinded. CONCLUSIONS: Regimens that used TDR were associated with an increase in SevAEs, raising concerns regarding safety of TDR regimens.
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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 | 0.022 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.044 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".