Evaluation of Phenotypic and Genotypic Susceptibility Testing Methods for Newer β-lactam/β-lactamase Inhibitor Combinations in Multidrug Resistant <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
BACKGROUND: Ceftazidime-avibactam (CZA), ceftolozane-tazobactam (CT), and imipenem-relebactam (IMR) are newer β-lactam/β-lactamase inhibitor (BL/BLI) combinations used for treatment of multidrug resistant (MDR) Pseudomonas aeruginosa, although resistance has already emerged. Optimal use of these agents relies on timely, accurate susceptibility testing results and understanding of local resistance mechanisms. METHODS: 183 MDR P. aeruginosa clinical isolates were used to evaluate the performance of commercial Sensititre and Phoenix panels for CZA, CT, and IMR susceptibility testing compared to broth microdilution (BMD). Genomic resistance determinants were also predicted for each isolate with AMRFinderPlus. RESULTS: Categorical agreement (CA) of the Sensititre panel compared to BMD was 95.8%, 90.1%, and 95.8% for CZA, CT, and IMR, respectively. CA of the Phoenix panel was 83.0% for CZA and 85.7% for CT. The Phoenix panel was biased toward under-calling CZA resistance while error rates were acceptable for CT by the error-rate-bound method. AMRFinderPlus identified acquired β-lactamases in 4.6% of first-time patient isolates. CA of genotype with BMD was 74.9% for CZA, 91.9% for CT, and 90.7% for IMR. However, all agents had unacceptably high VME rates using genotypic testing because many phenotypically resistant isolates had no identifiable genotypic resistance determinants. CONCLUSIONS: The Sensititre panel met standard acceptance criteria while the Phoenix panel had low CA for all tested BL/BLIs compared to BMD. Acquired β-lactamases were a rare cause of BL/BLI resistance. Further understanding of resistance mechanisms is required before phenotypic BL/BLI resistance can be reliably predicted from genotype, especially in settings where prevalence of acquired β-lactamases is low.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".