Mechanisms of Reduced Susceptibility to Ciprofloxacin in <i>Escherichia coli</i> Isolates from Canadian Hospitals
Bibliographic record
Abstract
OBJECTIVE: To determine whether plasmid-mediated quinolone resistance (PMQR) determinants play a role in the increasing resistance to fluoroquinolones among Escherichia coli isolates in Canadian hospitals, and to determine the mechanisms of reduced susceptibility to ciprofloxacin in a recent collection of 190 clinical E coli isolates. METHODS: E coli isolates (n=1702) were collected as part of the 2007 Canadian Hospital Ward Antibiotic Resistance Surveillance (CANWARD) study. Antimicrobial susceptibility testing was performed by Clinical and Laboratory Standards Institute (CLSI) broth microdilution. Using a representative subset of isolates (n=190), the mechanisms of reduced susceptibility to ciprofloxacin were detected by polymerase chain reaction and sequencing of the quinolone resistance-determining regions (QRDR) of chromosomal gyrA and parC genes, and by polymerase chain reaction for the PMQR genes: qnr, aac(6') Ib-cr and qepA. RESULTS: 2.1% and 1.1% of E coli harboured aac(6')Ib-cr and qnrB, respectively. Single amino acid substitutions in the QRDR of gyrA were observed among isolates with ciprofloxacin minimum inhibitory concentrations as low as 0.12 μg/mL. As the ciprofloxacin minimum inhibitory concentration increased to 1 μg/mL (which is still considered to be susceptible by the CLSI), the vast majority of isolates demonstrated both gyrA and parC mutations. CONCLUSION: PMQR determinants and QRDR mutants among clinical E coli isolates with reduced susceptibility to ciprofloxacin demonstrates the need for increased surveillance and the need to re-evaluate the current CLSI breakpoints to prevent further development of fluoroquinolone resistance.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".