New Recommendations of a Height-Based Dosing Regimen of Tobramycin for Cystic Fibrosis in Adults: A Population Pharmacokinetic Analysis
Bibliographic record
Abstract
BACKGROUND: Acute pulmonary exacerbations (APEs) in patients with adult cystic fibrosis (CF) are treated with a beta-lactam and an aminoglycoside for activity against Pseudomonas aeruginosa (PA). Emerging drug resistance and changing pharmacokinetic profile in an aging population involve a reevaluation of tobramycin dosing recommendations. The objective of this study was to develop a population pharmacokinetic model and establish optimal dosing recommendations for tobramycin using Monte Carlo simulations. METHODS: This retrospective clinical study and data collection were performed at the CF center of the McGill University Health Center (MUHC), Canada. Model development and simulations were performed using a nonlinear mixed-effect modeling approach (NONMEM, version 7.4.2). The ratios of maximal concentration (C max ) to the minimal inhibitory concentration (MIC) (C max /MIC ≥8 and ≥10) and area under the curve (AUC) to the MIC (AUC/MIC ≥70 and ≥100) were evaluated. RESULTS: Adult patients with CF (n = 51) treated with tobramycin were included in the study. Plasma concentrations of tobramycin were obtained for 699 samples from the MUHC database. The two-compartmental model best described the pharmacokinetics of tobramycin. The association of patient height with the central volume of distribution significantly improved this model. Height, rather than weight, induced the best reduction in objective function. According to simulations, doses between 3.4 mg/cm and 4.4 mg/cm were necessary to achieve C max /MIC values of ≥8 and ≥10, respectively. However, higher doses were required to achieve the AUC/MIC targets. CONCLUSIONS: This study demonstrated that height of the patients seems to be more suitable than their weight for dosing adjustments in adult patients with CF. According to this model, initial doses of tobramycin between 3.4 and 4.4 mg/cm should be recommended for patients with a median height of 164 cm and weight of 55 kg to achieve the target plasma concentrations.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".