Faropenem Susceptibility of Multidrug-resistant Contemporary Clinical Isolates from Zhejiang Province, China
Bibliographic record
Abstract
Abstract Alternative antimicrobial therapies are urgently needed for a variety of multidrug-resistant bacterial pathogens. Faropenem is an orally available β-lactam in the class of carbapenem antibiotics. Thus far, little information is available on faropenem susceptibility of multidrug-resistant clinical isolates from China. Therefore, in the current study 141 contemporary clinical isolates, including methicillin-resistant Staphylococcus aureus (MRSA: n = 18), coagulase-negative staphylococci (CNS: n = 16), Enterococcus faecalis (n = 14), Enterococcus faecium (n = 7), Pseudomonas aeruginosa (n = 25), Klebsiella pneumoniae (n = 21), Escherichia coli (n = 20), and Acinetobacter baumannii (n = 20), were collected between March 2018 and March 2019 and tested for susceptibility to faropenem and other antimicrobials using the broth microdilution method. All E. faecium, P. aeruginosa, and A. baumannii isolates were fully resistant to faropenem. However, most of the MRSA, CNS, E. faecalis, K. pneumonia, and E. coli isolates appeared to be susceptible to faropenem, with minimal inhibitory concentration90 values of 4 mg/L, 2 mg/L, 2 mg/L, 4 mg/L, and 2 mg/L, respectively. Therefore, faropenem could be considered as alternative therapy for future treatment of multidrug-resistant MRSA, CNS, E. faecalis, K. pneumonia, and E. coli infections in China.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".