Ceftaroline pharmacodynamic activity versus community-associated and healthcare-associated methicillin-resistant Staphylococcus aureus, heteroresistant vancomycin-intermediate S. aureus, vancomycin-intermediate S. aureus and vancomycin-resistant S. aureus using an in vitro model
Bibliographic record
Abstract
BACKGROUND: This study assessed the pharmacodynamics of ceftaroline against methicillin-resistant Staphylococcus aureus (MRSA), heteroresistant (h) vancomycin-intermediate S. aureus (hVISA), VISA and vancomycin-resistant S. aureus (VRSA) using an in vitro model. METHODS: Two methicillin-susceptible S. aureus (MSSA), one community-associated (CA)-MRSA, one healthcare-associated (HA)-MRSA, one hVISA, three VISA and two VRSA were studied. The pharmacodynamic model was inoculated with a concentration of 1 × 10⁶ cfu/mL and ceftaroline dosed every 12 h (at 0 and 12 h) to simulate the ƒC(max) and t(½) obtained after administering 600 mg intravenously every 12 h (ƒC(max), 16 mg/L; t(½), 2.6 h). Samples were collected over 24 h to assess viable growth and changes in ceftaroline MIC over time. RESULTS: Ceftaroline ƒT(> MIC) of ≥ 92% (ceftaroline MICs, ≤ 1 mg/L) was bactericidal (≥ 3 log₁₀ killing) against MSSA, CA-MRSA, HA-MRSA, hVISA, VISA and VRSA at 12 and 24 h. No bacterial regrowth occurred over the study period and no change in ceftaroline MIC was observed. CONCLUSIONS: Ceftaroline ƒT(> MIC) of ≥ 92% (ceftaroline MICs, ≤ 1 mg/L) was bactericidal (≥ 3 log₁₀ killing) against MSSA, CA-MRSA, HA-MRSA, hVISA, VISA and VRSA at 12 and 24 h.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".