<i>In Vitro</i> Activity of Imipenem-Relebactam against Clinical Isolates of Gram-Negative Bacilli Isolated in Hospital Laboratories in the United States as Part of the SMART 2016 Program
Bibliographic record
Abstract
ABSTRACT Relebactam is a non-β-lactam, bicyclic diazabicyclooctane β-lactamase inhibitor of class A and class C β-lactamases, including Klebsiella pneumoniae carbapenemases (KPCs). It is in phase 3 clinical development in combination with imipenem/cilastatin. The in vitro activities of imipenem-relebactam, imipenem, and comparators were determined using the Clinical and Laboratory Standards Institute (CLSI) reference broth microdilution method for isolates of Enterobacteriaceae ( n = 3,419) and Pseudomonas aeruginosa ( n = 896) collected in 2016 by 21 U.S. hospital laboratories participating in the SMART (Study for Monitoring Antimicrobial Resistance Trends) global surveillance program. Relebactam was tested at a fixed concentration of 4 μg/ml. Imipenem-relebactam MICs were interpreted using CLSI breakpoints for imipenem. Rates of susceptibility to imipenem-relebactam and imipenem for non- Proteeae Enterobacteriaceae ( n = 3,143) and P. aeruginosa were 99.1% (3,115/3,143) and 95.9% (3,013/3,143) and were 94.4% (846/896) and 74.7% (669/896), respectively. Relebactam restored imipenem susceptibility to 78.5% (102/130) of imipenem-nonsusceptible non- Proteeae Enterobacteriaceae and to 78.0% (177/227) of imipenem-nonsusceptible P. aeruginosa isolates. Susceptibility to imipenem-relebactam was 98.2% (444/452) and 82.2% (217/264) for multidrug-resistant (MDR) non- Proteeae Enterobacteriaceae and MDR P. aeruginosa , respectively. Given the ability of relebactam to restore susceptibility to imipenem in nonsusceptible isolates of both non- Proteeae Enterobacteriaceae and P. aeruginosa and to demonstrate potent activity against current MDR isolates of both non- Proteeae Enterobacteriaceae and P. aeruginosa , further development of imipenem-relebactam appears warranted.
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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 | 0.001 |
| 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".