Analysis of Potential β-Lactam Surrogates To Predict <i>In Vitro</i> Susceptibility and Resistance to Ceftaroline for Clinical Isolates of Enterobacteriaceae
Bibliographic record
Abstract
ABSTRACT Ceftaroline fosamil was approved by the United States Food and Drug Administration in 2010 and by the European Medicines Agency in 2012. As of April 2017, only one commercial antimicrobial susceptibility testing device offered a Gram-negative panel that included ceftaroline. This circumstance is unfortunate, as many clinical microbiology laboratories rely solely on commercial devices to generate in vitro antimicrobial susceptibility testing results for common bacterial pathogens. In lieu of device-based testing of clinical isolates of Enterobacteriaceae , laboratories wishing to test ceftaroline must either opt for disk diffusion testing or use a gradient strip; however, both alternatives interrupt laboratory workflow and require additional labor and expense. Identification of a reliable surrogate β-lactam to predict in vitro susceptibility to ceftaroline may offer another interim solution as laboratories await availability of ceftaroline for testing on their commercial devices. We tested six β-lactams (aztreonam, ceftazidime, ceftriaxone, cefotaxime, cefoxitin, and cefpodoxime) as potential surrogates for ceftaroline against a collection of 543 clinical isolates of Enterobacteriaceae selected to approximate the distribution of ceftaroline MICs observed in AWARE global surveillance studies conducted in 2013. All six potential surrogates generated very major error rates of 16.3% to 56.6%, far exceeding the accepted limit of 1.5% set by the Clinical and Laboratory Standards Institute (CLSI) and the United States Food and Drug Administration (FDA) Center for Devices and Radiological Health. Failure to identify a reliable surrogate to predict in vitro susceptibility and resistance to ceftaroline for clinical isolates of Enterobacteriaceae underscores the need for expedited addition of newer antimicrobial agents to commercial antimicrobial susceptibility testing devices.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".