In vitro activity of imipenem/relebactam against Enterobacteriaceae and Pseudomonas aeruginosa isolated from intraabdominal and urinary tract infection samples: SMART Surveillance United States 2015–2017
Bibliographic record
Abstract
OBJECTIVES: Antimicrobial resistance, including multidrug-resistance (MDR), is increasing, especially among Gram-negative bacilli. New agents are needed to treat infections caused by these pathogens. This report assessed the activity of imipenem/relebactam against Gram-negative bacilli from intraabdominal infections (IAIs) and urinary tract infections (UTIs) submitted to the SMART (Study for Monitoring Antimicrobial Resistance Trends) global surveillance programme in the United States from 2015 to 2017. METHODS: Broth microdilution MICs for imipenem/relebactam and comparators were determined by a central laboratory against isolates of non-Proteeae Enterobacteriaceae (NPE) and Pseudomonas aeruginosa (P. aeruginosa). Imipenem/relebactam MICs were interpreted using United States Food and Drug Administration (FDA) breakpoints. RESULTS: 99.5% of NPE isolates collected from patients with IAIs (n=3633) and UTIs (n=3038) were susceptible to imipenem/relebactam, as were 77.9% of imipenem-nonsusceptible, 96.3% of Klebsiella pneumoniae carbapenemase (KPC)-positive, and 98.7% of MDR isolates from IAIs and UTIs combined. A total of 96.7% of IAI isolates (n=486) and 96.4% of UTI isolates (n=360) of P. aeruginosa were susceptible to imipenem/relebactam, as were 85.0% of imipenem-nonsusceptible and 87.3% of MDR isolates from IAIs and UTIs combined. Percent susceptibility to imipenem/relebactam for cefepime-, ceftazidime-, and piperacillin-tazobactam-nonsusceptible isolates was 98.3-98.8% for NPE and 87.3-90.0% for P. aeruginosa. CONCLUSIONS: Imipenem/relebactam demonstrated potent in vitro activity against NPE and P. aeruginosa isolates from IAIs and UTIs, including against resistant subsets, and will provide important coverage for IAIs and UTIs caused by β-lactam-resistant, MDR, and KPC-positive Gram-negative bacilli.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".