1717. <i>In Vitro</i> Activity of Aztreonam-Avibactam Against Enterobacterales Isolated from Pediatric and Adult Patients Collected During the ATLAS Global Surveillance Program, 2017-2020
Bibliographic record
Abstract
Abstract Background The rapid spread of antimicrobial resistance among clinically isolated Enterobacterales (Eba) continues to threaten public health. Aztreonam (ATM) is a monobactam stable to hydrolysis by metallo-β-lactamases (MBLs) and avibactam (AVI) inhibits class A, class C, and some class D serine β-lactamases. ATM-AVI is being developed for use against drug-resistant isolates of Eba, especially those co-producing MBLs and other β-lactamases. This study evaluated the in vitro activity of ATM-AVI and comparators against Eba collected in 2017-2020 from pediatric and adult patients as part of the ATLAS global surveillance program. Methods Non-duplicate clinical Eba isolates were collected from 239 sites in 55 countries in Europe, Latin America, Asia/Pacific (excluding mainland China and India), and Middle East/Africa. Susceptibility testing was performed by CLSI broth microdilution and interpreted using CLSI 2022 breakpoints. PCR and sequencing were used to determine the β-lactamase genes present in all isolates with meropenem MIC >1 µg/mL, and Escherichia coli, Klebsiella spp. and Proteus mirabilis with ATM or ceftazidime MIC >1 µg/mL. Results MIC90 values for ATM-AVI of 0.12 µg/ml were observed for Eba isolates collected from both pediatric and adult patients. Against all Eba isolates, ≤8 µg/ml of ATM-AVI was sufficient to inhibit 99.97% (pediatric) and 99.95% (adult), whereas ATM alone inhibited only 72.0% and 75.9% of these isolates at ≤8 µg/ml, respectively (table). Among isolates that screened positive for an MBL, MIC90 values were 0.25 µg/ml (pediatric) and 0.5 µg/ml (adult). Among MBL-positive isolates, ATM-AVI inhibited 100% (pediatric) and 99.9% (adult) at concentrations ≤8 µg/ml. In contrast, ATM alone only inhibited 19.0% (pediatric) and 25.3% (adult) of isolates carrying MBLs at ≤8 µg/ml. Conclusion Based on MIC90 values, ATM-AVI demonstrated potent in vitro activity against Eba isolated both from pediatric and adult patients. The capability of AVI to potentiate ATM against MBL-positive isolates warrants its continued development. Disclosures All Authors: No reported disclosures.
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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 | 0.001 | 0.001 |
| 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".