Detection of Methicillin Resistance in Staphylococcus aureus by Disk Diffusion and PCR Methods
Bibliographic record
Abstract
Background and Objective: Methicillin resistance in Staphylococcus aureus is an increasingly important clinical problem. A chromosomal gene, mecA, mediates resistance to penicillinase-resistant penicillins such as methicillin and oxacillin in Staphylococcus aureus. We evaluated the validity of disk diffusion test by using oxacillin, methicillin and cefoxitin disks with consideration of the presence of mecA gene as the reference method for detection of methicillin resistant Staphylococcus aureus (MRSA). Materials and Methods: The susceptibility testing of 222 S. aureus clinical isolates to oxacillin (1 µg), cefoxitin (30 µg) and methicillin (5 µg) was carried out by the disk diffusion method according to the Clinical Laboratory Standards Institute guidelines. Detection of mecA gene was performed using PCR method. Results: An amplified mecA gene of 310 bp was detected in 55% of examined strains by PCR, thus 55% strains were considered MRSA. Sensitivity of oxacillin, methicillin and cefoxitin disks were determined 100%, 99.1% and 98.3% respectively. All MRSA strains in PCR had shown resistance to penicillinase-resistant penicillins by oxacillin disk, but two and one strains were sensitive by cefoxitin and methicillin disk respectively. Thus, oxacillin was the most appropriate disk for detecting MRSA. Conclusion: The prevalence of MRSA in this study is comparable to that found in United States, Canada, Europe and Iran, but the percentage of MRSA isolates is almost twice of percentage reported from Japan.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".