<i>In vitro</i> miconazole susceptibility of meticillin‐resistant <i>Staphylococcus pseudintermedius</i> and <i>Staphylococcus aureus</i>
Bibliographic record
Abstract
BACKGROUND: The emergence and dissemination of meticillin-resistant staphylococci has created significant treatment challenges in veterinary medicine and increased interest in topical therapy for superficial infections. Concern has been expressed regarding the use of some topical antimicrobials in animals because of the potential for emergence of resistance, and additional options are required. Miconazole has limited antibacterial properties that include antistaphylococcal activity. HYPOTHESIS/OBJECTIVES: The objective of this study was to assess the in vitro susceptibility of Staphylococcus pseudintermedius and Staphylococcus aureus to miconazole. METHODS: In vitro susceptibility of 112 meticillin-resistant S. pseudintermedius (MRSP), 53 meticillin-resistant S. aureus (MRSA) and 37 meticillin-susceptible S. pseudintermedius (MSSP) to miconazole was assessed using agar dilution. RESULTS: The minimal inhibitory concentration (MIC) range, MIC(50) and MIC(90) for MRSP were 1-8, 2 and 4 μg/mL, respectively. Corresponding results for MRSA were 1-8, 2 and 6 μg/mL, and for MSSP 1-4, 2 and 2 μg/mL. The MIC for MSSP was a significantly lower MIC than that for both MRSP (P = 0.006) and MRSA (P < 0.001), while the MIC for MRSP was significantly lower than that for MRSA (P = 0.001). CONCLUSIONS AND CLINICAL IMPORTANCE: These in vitro data suggest that miconazole could be a useful therapeutic option for superficial infections caused by meticillin-susceptible and meticillin-resistant staphylococci, but proper clinical investigation is required.
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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 | 0.000 | 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) | 0.001 | 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".