Factors Associated with Reduced Antituberculous Serum Drug Concentrations in Patients with HIV-TB Coinfection
Bibliographic record
Abstract
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.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".