The 3 HP regimen for tuberculosis preventive treatment: safety, dosage and related concerns during its large-scale implementation in countries like India
Bibliographic record
Abstract
The 3-month once-weekly isoniazid-rifapentine (3 HP) regimen for tuberculosis preventive treatment recommended by WHO is being rolled in countries including India. It has higher completion rates and lower risk of hepatotoxicity than isoniazid preventive treatment, but trials also showed higher frequency of systemic drug reactions (SDRs) including flu-like syndromes and dizziness, and also uncommon Grade 3 or 4 adverse events like hypotension, syncope, bronchospasm. Low BMI is a risk factor for SDRs. Available data on safety of 3 HP in the Asian region is limited, heterogeneous, but points to a higher frequency of SDRs suggesting a need for caution in its large-scale implementation. 19% (118/614) of household contacts initiated on 3 HP in Delhi reported dizziness. Multiple lines of evidence including pharmacokinetic data suggest that the SDRs may be related to isoniazid and its plasma concentration. WHO and national guidelines for the 3 HP regimen currently recommend a fixed dose of once-weekly 900 mg isoniazid in adults regardless of body weight that poses a risk of SDRs for lower weight adults, amplified by the acetylator status and the lack of co-administration of pyridoxine. Weight based dosing, co-administration of pyridoxine and pharmacovigilance studies should accompany the roll out of 3 HP to ensure its safe and successful implementation.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".