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Record W1989948347 · doi:10.1177/1545109712454454

Factors Associated with Reduced Antituberculous Serum Drug Concentrations in Patients with HIV-TB Coinfection

2012· article· en· W1989948347 on OpenAlexaffabout
Rabia Ahmed, Ryan Cooper, Michelle Foisy, Evelina Der, Dennis Kunimoto

Bibliographic record

VenueJournal of the International Association of Physicians in AIDS Care · 2012
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsMedicineCoinfectionTuberculosisIsoniazidDosingBody mass indexInternal medicineHuman immunodeficiency virus (HIV)DrugGastroenterologyImmunologyPharmacologyPathology

Abstract

fetched live from OpenAlex

We describe correlates of reduced antituberculous serum drug concentrations (SDCs) in HIV-infected patients receiving treatment for active tuberculosis (TB). Cross-sectional analysis of individuals diagnosed with HIV and active TB in Northern Alberta, Canada, was performed. Of the 30 HIV-TB cases, 27 underwent measurement of SDCs. Rates of low SDCs were 9 of 26 (34%) for isoniazid (INH) and 16 of 25 (64%) for rifamycins. Increased weight and elevated body mass index (BMI) correlated with low SDCs for rifampin (P < .05) and increased weight also correlated with reduced SDCs for INH (P < .05). This suggests that conventional antituberculous dosing may be too low and consideration should be given to increase the maximum initial weight-based doses in HIV-infected patients.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations10
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the International Association of Physicians in AIDS CareSame topicTuberculosis Research and EpidemiologyFrench-language works237,207