AUC0-t/MIC is a continuous index of fluoroquinolone exposure and predictive of antibacterial response for Streptococcus pneumoniae in an in vitro infection model
Bibliographic record
Abstract
OBJECTIVE: To conduct a comprehensive pharmacodynamic analysis of moxifloxacin and levofloxacin against Streptococcus pneumoniae in an in vitro infection model. METHODS: In dose escalation studies, single doses with peak concentrations equivalent to 1 x, 2 x, 4 x, 8 x, 16 x and 32 x MIC against two isolates of S. pneumoniae were studied over 24 h. Traditional pharmacodynamic indices, including peak concentration divided by MIC (peak/MIC), time of concentration above MIC (T > MIC) and AUC24/MIC, were estimated for all regimens. As a continuous index of fluoroquinolone exposure, AUC0-t/MIC was also calculated, as AUC from time 0 to 1, 2 and 6 h divided by MIC. Correlations between pharmacodynamic indices and antibacterial effects were examined using linear and non-linear methods. In validation experiments, the pharmacodynamic model was used to predict bacterial kill curves, produced by simulated clinical doses of moxifloxacin and levofloxacin against two other S. pneumoniae isolates. RESULTS: Peak/MIC was most predictive of early bacterial kill, whereas T > MIC was significantly associated with final bacterial counts at 24 h. Antibacterial effects were bacteriostatic when T > MIC was 48% and bactericidal when values exceeded 55%. AUC0-t/MIC was strongly associated with bacterial kill throughout the dosing interval. Bactericidal activity and bacterial eradication were associated with AUC0-t/MICs of 28 and 135, respectively. AUC0-t/MIC was also highly predictive of bacterial kill curves produced by simulated clinical doses of moxifloxacin and levofloxacin (precision 0.36 log10 cfu/mL, bias 0.02 log10 cfu/mL). CONCLUSION: This study demonstrated the novel application of AUC0-t/MIC as a continuous index of antibiotic activity, and provided extensive characterization of fluoroquinolone pharmacodynamics against S. pneumoniae.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".