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Record W4396861435 · doi:10.1016/j.lansea.2024.100422

The 3 HP regimen for tuberculosis preventive treatment: safety, dosage and related concerns during its large-scale implementation in countries like India

2024· review· en· W4396861435 on OpenAlexaff
Anurag Bhargava

Bibliographic record

VenueThe Lancet Regional Health - Southeast Asia · 2024
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineIsoniazidRifapentineRegimenAdverse effectPharmacovigilanceDosingTuberculosisPediatricsInternal medicineLatent tuberculosisPharmacologyMycobacterium tuberculosisPathology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.886
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.068
GPT teacher head0.437
Teacher spread0.370 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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