Safety and Efficacy of Rifampin or Isoniazid Among People With <i>Mycobacterium tuberculosis</i> Infection and Living With Human Immunodeficiency Virus or Other Health Conditions: Post Hoc Analysis of 2 Randomized Trials
Bibliographic record
Abstract
BACKGROUND: The safety and efficacy of rifampin among people living with human immunodeficiency virus (PLHIV) or other health conditions is uncertain. We assessed completion, safety, and efficacy of 4 months of rifampin vs 9 months of isoniazid among PLHIV or other health conditions. METHODS: We conducted post hoc analysis of 2 randomized trials that included 6859 adult participants with Mycobacterium tuberculosis infection. Participants were randomized 1:1 to 10 mg/kg/d rifampin or 5 mg/kg/d isoniazid. We report completion, drug-related adverse events (AE), and active tuberculosis incidence among people living with HIV; with renal failure or receiving immunosuppressants; using drugs or with hepatitis; with diabetes mellitus; consuming >1 alcoholic drink per week or current/former smokers; and with no health condition. RESULTS: Overall, 270 (3.9%) people were living with HIV (135 receiving antiretroviral therapy), 2012 (29.3%) had another health condition, and 4577 (66.8%) had no condition. Rifampin was more often or similarly completed to isoniazid in all populations. AEs were less common with rifampin than isoniazid among PLHIV (risk difference, -2.1%; 95% confidence interval [CI], -5.9 to 1.6). This was consistent for others except people with renal failure or on immunosuppressants (2.1%; 95% CI, -7.2 to 11.3). Tuberculosis incidence was similar among people receiving rifampin or isoniazid. Among participants receiving rifampin living with HIV, incidence was comparable to those with no health condition (rate difference, 4.1 per 1000 person-years; 95% CI, -6.4 to 14.7). CONCLUSIONS: Rifampin appears to be safe and as effective as isoniazid across many populations with health conditions, including HIV. CLINICAL TRIALS REGISTRATION: NCT00170209; NCT00931736.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.019 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".