Comparison of Agar Dilution and E-test for antimicrobial susceptibility testing of Campylobacter coli isolates recovered from 80 Ontario swine farms
Bibliographic record
Abstract
The primary aim of this study was to evaluate the level of agreement of the E-test for in vitro antimicrobial susceptibility testing of Campylobacter coli using the agar dilution technique, which is the approved method. A convenience sample of 80 Ontario swine farms was chosen for this study; each farm was visited from January to June 2004. A total of 233 isolates of C. coli were tested for susceptibility to 10 antimicrobials by agar dilution and the E-test. Performance of the tests was evaluated using 7 quality control strains: Escherichia coli ATCC 25922, Staphylococcus aureus ATCC 29213, Campylobacter jejuni ATCC 33560, and Campylobacter coli ATCC 33559 for the E-test and E. coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, and C. jejuni ATCC 33560 for the agar dilution test. Weighted Cohen’s kappa and prevalence-adjusted bias-adjusted kappa (PABAK) tests were used for statistical analysis. The E-test and agar dilution test results had a strong agreement when resistance to streptomycin and tetracycline were evaluated (weighted kappa: 0.68 and 0.66, respectively). However, marked disagreement was detected when testing susceptibility to nalidixic acid and ampicillin (0.15 and 0.22, respectively). Almost perfect agreement was detected by PABAK when testing susceptibility to gentamicin (0.99). Agreement was found to be moderate for ciprofloxacin, azithromycin, clindamycin, erythromycin, and chloramphenicol. Although the level of agreement between the E-test and agar dilution depended on the antimicrobial being tested, the E-test always detected a lower proportion of resistant isolates compared to agar dilution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".