Aztreonam/avibactam effect on pharmacodynamic indices for mutant selection of<i>Escherichia coli and Klebsiella pneumoniae</i>harbouring serine- and New Delhi metallo-β-lactamases
Bibliographic record
Abstract
OBJECTIVES: Ceftazidime/avibactam is not active against MBL-producing bacteria. Combining ceftazidime/avibactam or avibactam with aztreonam can counter the resistance of MBL-producing Enterobacterales. The aim of this study was to evaluate whether the addition of avibactam could reduce or close the mutant selection window (MSW) of aztreonam in Escherichia coli and Klebsiella pneumoniae harbouring MBLs; MSW is a pharmacodynamic (PD) parameter for the selection of emergent resistant mutants. METHODS: In vitro susceptibility of 19 clinical isolates to ceftazidime/avibactam, aztreonam alone, and in co-administration (aztreonam/ceftazidime/avibactam and aztreonam/avibactam) was determined, as well as the mutant prevention concentration (MPC). The fraction of time within 24 h that the free drug concentration was within the MSW (fTMSW) and the fraction of time that the free drug concentration was above the MPC (fT>MPC) in both plasma and epithelial lining fluid (ELF) were determined from simulations of 10 000 profiles. The joint PTA was used to derive a joint cumulative fraction of response (CFR). RESULTS: All isolates were resistant to ceftazidime/avibactam or aztreonam. Combining aztreonam and avibactam or ceftazidime/avibactam resulted in synergistic bactericidal activities against all isolates. Synergism was primarily due to the aztreonam/avibactam combination. For aztreonam/avibactam dosing regimens evaluated in clinical trials, fT>MPC values were >90% and >80%, whereas fTMSW measures were <10% and <20% in plasma and ELF, respectively. The CFR was 100% for aztreonam/avibactam against the collection of clinical isolates. CONCLUSIONS: Effective antimicrobial combination optimized the PD parameters measuring selection for emergent mutants by increasing fT>MPC and reducing fTMSW.
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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) | 0.000 | 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".