Multicenter Study To Determine Disk Diffusion and Broth Microdilution Criteria for Prediction of High- and Low-Level Mupirocin Resistance in <i>Staphylococcus aureus</i>
Bibliographic record
Abstract
ABSTRACT Mupirocin susceptibility testing of Staphylococcus aureus has become more important as mupirocin is used more widely to suppress or eliminate S. aureus colonization and prevent subsequent health care- and community-associated infections. The present multicenter study evaluated two susceptibility testing screening methods to detect mupirocin high-level resistance (HLR), broth microdilution (BMD) MICs of ≥512 μg/ml, and a 6-mm zone diameter for a disk diffusion (DD) test with a 200-μg disk. Initial testing indicated that with Clinical and Laboratory Standards Institute methods for BMD and DD testing, the optimal conditions for the detection of mupirocin HLR were 24 h of incubation and reading of the DD zone diameters with transmitted light. Using the presence or absence of mupA as the “gold standard” for HLR, the sensitivity and specificity of a single-well 256 μg/ml BMD test were 97 and 99%, respectively, and those for the 200-μg disk test were 98 and 99%, respectively. Testing with two disks, 200 μg and 5 μg, was evaluated for its ability to distinguish HLR isolates (MICs ≥ 512 μg/ml), low-level-resistant (LLR) isolates (MICs = 8 to 256 μg/ml), and susceptible isolates (MICs ≤ 4 μg/ml). Using no zone with both disks as an indication of HLR and no zone with the 5-μg disk plus any zone with the 200-μg disk as LLR, only 3 of the 340 isolates were misclassified, with 3 susceptible isolates being classified as LLR. Use of standardized MIC or disk tests could enable the detection of emerging high- and low-level mupirocin resistance in S. aureus .
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".