Detection of Methicillin-Resistant <i>Staphylococcus aureus</i> Directly from Nasal Swab Specimens by a Real-Time PCR Assay
Bibliographic record
Abstract
Screening for colonization with methicillin-resistant Staphylococcus aureus (MRSA) is a key aspect of infection control to limit the nosocomial spread of this organism. Current methods for the detection of MRSA in clinical microbiology laboratories, including molecularly based techniques, require a culture step and the isolation of pure colonies that result in a minimum of 20 to 24 h until a result is known. We describe a qualitative in vitro diagnostic test for the rapid detection of MRSA directly from nasal swab specimens (IDI-MRSA; Infectio Diagnostic, Inc., Sainte-Foy, Quebec, Canada), based upon a real-time PCR and direct detection of MRSA via amplicon hybridization with a fluorogenic target-specific molecular beacon probe. Samples from 288 patients were analyzed for the presence of MRSA with the IDI-MRSA assay, compared to detection by either direct plating or enrichment broth selective culture methods. The diagnostic values for this MRSA screening method were 91.7% sensitivity, 93.5% specificity, 82.5% positive predictive value, and 97.1% negative predictive value when compared to culture-based methods. The time from the start of processing of specimen to result was approximately 1.5 h. In our hands, the IDI-MRSA assay is a sensitive and specific test for detection of nasal colonization with MRSA and providing for same-day results, allowing more efficient and effective use of infection control resources to control MRSA in health care facilities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".