Comparison of the Vitek Gram-Positive Susceptibility 106 Card, the MRSA-Screen Latex Agglutination Test, and <i>mecA</i> Analysis for Detecting Oxacillin Resistance in a Geographically Diverse Collection of Clinical Isolates of Coagulase-Negative Staphylococci
Bibliographic record
Abstract
The Vitek automated susceptibility testing system with a modified gram-positive susceptibility (GPS) 106 card (bioMerieux Vitek, Inc., Hazelwood. Mo.) and a rapid slide latex agglutination test (MRSA-Screen test; Denka Seiken Co., Ltd., Tokyo, Japan) were evaluated for their abilities to detect oxacillin resistance in coagulase-negative staphylococci (CoNS). The reference broth microdilution method and the detection of the mecA gene by PCR ("gold standard" reference result) were used to compare the results obtained with the commercial products. A total of 123 clinical isolates consisting of eight species were selected from U.S. surveillance collections. Among the mecA-positive isolates (95 strains), 30 isolates were initially negative on the MRSA-Screen test read at 3 min. When the agglutination reaction was extended for 10 min, 26 of the 30 isolates became positive. For a different four isolates, the oxacillin MIC was < or =0.25 microg/ml on the Vitek GPS 106 card. Among the mecA-negative isolates (28 strains), for two Staphylococcus warneri, two S. lugdunensis, and two S. saprophyticus strains MICs were > or =0.5 microg/ml by the reference broth microdilution method. Four of these isolates were also categorized as resistant with the Vitek GPS 106 card and two isolates were positive by the MRSA-Screen test. Overall, the MRSA-Screen test, GPS 106 card, and reference broth microdilution method had sensitivities of 95.7 (result at 10 min), 95.7, and 100%, respectively, and specificities of 92.8, 85.7, and 78.5%, respectively. Although the MRSA-Screen test required a slight procedural modification, both commercial methods achieved a sensitivity and specificity at detecting oxacillin resistance in CoNS at a level that was acceptable for clinical laboratory use.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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".