Comparison of three phenotypic techniques for detection of methicillin resistance in Staphylococcus spp. reveals a species-dependent performance
Bibliographic record
Abstract
OBJECTIVES: To evaluate the usefulness of the cefoxitin screen in Vitek 2 Gram-positive panels for recognizing methicillin-resistant strains of staphylococci. METHODS: Seven hundred and ninety-nine non-duplicate isolates of Staphylococcus aureus and coagulase-negative strains were included in the study. Methicillin resistance was measured using PCR for the mecA gene, the CLSI cefoxitin disc diffusion method, the Vitek 2 cefoxitin screen and the Vitek 2 oxacillin susceptibility test. RESULTS: Compared with the molecular detection of methicillin resistance the overall sensitivities and specificities of the phenotypic tests for cefoxitin disc diffusion were 94.9% and 97.0%, for Vitek 2 cefoxitin screen were 94.6% and 93.5% and for Vitek 2 oxacillin susceptibility test were 93.8% and 77.9%. The cephamycin tests (cefoxitin disc diffusion and Vitek 2 screen) were not able to identify mecA-positive strains of Staphylococcus simulans. In addition, the performance of the Vitek 2 system was poor against Staphylococcus cohnii subspecies, Staphylococcus hominis hominis and Staphylococcus saprophyticus. CONCLUSIONS: Overall, the performance of the Vitek 2 system for differentiating mecA-positive staphylococci was comparable to PCR and the CLSI disc diffusion method; however, performance was species-dependent. Thus, before accepting the results produced by Vitek 2, species identification may be required.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".