Low-dose amikacin in the treatment of Multidrug-resistant Tuberculosis (MDR-TB)
Bibliographic record
Abstract
BACKGROUND: The World Health Organization recommends intravenous amikacin for the treatment of MDR-TB at a dose of 15 mg/kg. However, higher doses are associated with significant toxicity. METHODS: Patients with MDR-TB treated at our institution receive amikacin at 8-10 mg/kg, with dose adjustment based on therapeutic drug monitoring. We conducted a retrospective cohort study of patients with MDR-TB who received amikacin between 2010 and 2016. RESULTS: Forty-nine patients were included in the study. The median starting dose of amikacin was 8.9 mg/kg (IQR 8, 10), and target therapeutic drug levels were achieved at a median of 12 days (IQR 5, 26). The median duration of amikacin treatment was 7.2 months (IQR 5.7, 8), and median time to sputum culture conversion was 1 month (IQR 1,2). Six patients (12.2%) experienced hearing loss based on formal audiometry testing (95% CI 4.6-24.8%); 22.2% had subjective hearing loss (95% CI 11.2-37.1%) and 31.9% subjective tinnitus (95% CI 19.1-47.1%). Ten patients (23%) had a significant rise in serum creatinine (95% CI 11.8-38.6%), but only 5 patients had a GFR < 60 at treatment completion. 84% of patients had a successful treatment outcome (95% CI 84-99%). CONCLUSIONS: Low dose amikacin is associated with relatively low rates of aminoglycoside-related adverse events. We hypothesize that low-dose amikacin can be used as a safe and effective treatment for MDR-TB in situations where an adequate regimen cannot be constructed with Group A and B drugs, and where careful monitoring for adverse events is feasible.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".