<i>In Vitro</i> Activity of Ceftolozane-Tazobactam, Imipenem-Relebactam, Ceftazidime-Avibactam, and Comparators against Pseudomonas aeruginosa Isolates Collected in United States Hospitals According to Results from the SMART Surveillance Program, 2018 to 2020
Bibliographic record
Abstract
Ceftolozane-tazobactam (C/T), imipenem-relebactam (IMR), and ceftazidime-avibactam (CZA) were tested against 2,531 P. aeruginosa strains isolated from patients in the United States from 2018 to 2020 as part of the SMART (Study for Monitoring Antimicrobial Resistance Trends) surveillance program. MICs were determined by CLSI broth microdilution and interpreted using CLSI M100 (2021) breakpoints. Imipenem-, IMR-, or C/T-nonsusceptible isolates were screened for β-lactamase genes: 96.4% of all isolates and ≥70% of multidrug-resistant (MDR), pan-β-lactam-nonsusceptible, and difficult-to-treat resistance (DTR) isolates were C/T-susceptible; 52.2% of C/T-nonsusceptible isolates remained susceptible to IMR compared to 38.9% for CZA; and 1.7% of isolates tested were nonsusceptible to both C/T and IMR versus 2.2% of isolates with a C/T-nonsusceptible and CZA-resistant phenotype (a difference of 12 isolates). C/T and IMR modal MICs for pan-β-lactam-nonsusceptible isolates remained at or below their respective susceptible MIC breakpoints from 2018 to 2020, while the modal MIC for CZA increased 2-fold from 2018 to 2019 and exceeded the CZA-susceptible MIC breakpoint in both 2019 and 2020. Only six of 802 molecularly characterized isolates carried a metallo-β-lactamase, and two isolates carried a GES carbapenemase. Most P. aeruginosa isolates were C/T-susceptible, including many with MDR, pan-β-lactam-nonsusceptible, DTR, CZA-resistant, and IMR-nonsusceptible phenotypes. While C/T was the most active antipseudomonal agent, IMR demonstrated greater activity than CZA against isolates nonsusceptible to C/T.
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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 | 0.001 |
| 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".