Comparative antibacterial effects of daptomycin, vancomycin and teicoplanin studied in an in vitro pharmacokinetic model of infection
Bibliographic record
Abstract
OBJECTIVES: To compare the antibacterial effects (ABEs) of the free (f) drugs daptomycin, vancomycin and teicoplanin against methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant S. aureus (VRSA), using high and low inocula in a pharmacokinetic in vitro model. To determine the daptomycin fAUC/MIC ratio for a static effect and 3 log reduction in viable count and relate this target to the clinical breakpoint. METHODS: Five clinical MRSA isolates held at Southmead Hospital were used (SMH 15841, SMH 40289, SMH 40275, SMH 33922 and SMH 33024) together with a VRSA isolate (SMH 19898); inocula of 10(6) and 10(8) cfu/mL were used. Daptomycin (6 mg/kg once daily), vancomycin (1 g twice daily) and teicoplanin (400 mg once daily) regimens were simulated. ABEs were measured using the 24 h area-under-the-bacterial kill curve (AUBKC) and log change in viable count at 24 h (Delta24). For daptomycin, dose escalation was used to determine the relationship between ABE and AUC/MIC. RESULTS: Daptomycin was bactericidal against the MRSA strains. Daptomycin and vancomycin were active against the VRSA strain; teicoplanin had a static effect. The higher inoculum reduced the ABEs. Analysis of variance (ANOVA) indicated that daptomycin had a superior ABE to teicoplanin and vancomycin. Daptomycin fAUC/MIC was related to AUBKC and Delta24; the fAUC/MIC ratios for a static effect and 1 log and 3 log drop were 37.2 +/- 16.5, 40.6 +/- 17.8 and 49.8 +/- 19.2, respectively. CONCLUSIONS: These data define the fAUC/MIC sizes for daptomycin for bacteriostatic and bactericidal ABEs and indicate that a 6 mg/kg dose of daptomycin is superior to vancomycin and teicoplanin against MRSA and VRSA strains.
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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 | 0.001 |
| 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".