Minimal inhibitory and mutant prevention concentrations of azithromycin, clarithromycin and erythromycin for clinical isolates of Streptococcus pneumoniae
Bibliographic record
Abstract
BACKGROUND: Previous work showed a higher prevalence of macrolide/azalide resistance in provinces of Canada where azithromycin was the major treatment for Streptococcus pneumoniae as compared with regions where clarithromycin was the dominant treatment. These data provided a way to test the mutant selection window hypothesis, which predicts that the serum drug concentration (AUC(24)) relative to the mutant prevention concentration (MPC) would be higher for clarithromycin than for azithromycin. METHODS: The MIC and MPC were determined for 191 penicillin/macrolide-susceptible clinical isolates of S. pneumoniae with azithromycin, clarithromycin and erythromycin using agar plate assays. RESULTS: The MIC(50/90) (mg/L) and MPC(50/90) (mg/L), respectively, were as follows: azithromycin 0.13/0.25 and 1/4; clarithromycin 0.031/0.063 and 0.13/0.5; erythromycin 0.063/0.13 and 0.25/2. We calculated from published pharmacokinetic values that the AUC(24)/MPC(90) for azithromycin was 0.85; for clarithromycin it was 96, and for erythromycin base and estolate it was 4 and 10, respectively. Thus the AUC(24)/MPC(90) was about 50 times higher for clarithromycin than for azithromycin. CONCLUSIONS: The elevated prevalence of azithromycin resistance may derive in part from a low value of AUC(24)/MPC(90) and/or time above MPC, since previous work indicates that the number of prescriptions per person was similar in the geographical regions examined.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".