A Preliminary Guideline for the Assignment of Methicillin‐Resistant <i>Staphylococcus aureus</i> to a Canadian Pulsed‐Field Gel Electrophoresis Epidemic Type Using <i>spa</i> Typing
Bibliographic record
Abstract
BACKGROUND: Increasing rates of methicillin-resistant Staphylococcus aureus (MRSA) infections on a global scale is a major health concern. In Canada, there are 10 known epidemic types of MRSA as determined by pulsed-field gel electrophoresis (PFGE). Despite the excellent discriminatory power of PFGE, there are several disadvantages of using this technique, such as high degree of labour intensity and the inability to easily develop an MRSA typing database due to the subjective interpretation of results. OBJECTIVES: The purpose of the present study was to determine whether spa typing, an established DNA sequence-based typing method, could be used as an alternative to PFGE for the typing of Canadian MRSA (CMRSA) epidemic isolates. RESULTS: spa types were determined for 1488 CMRSA isolates, and the method was analyzed for its ability to identify and cluster CMRSA1-10 strains. Minimal spanning tree analysis of 1452 spa types revealed individual clonal clusters for PFGE epidemic types CMRSA1, 2, 7 and 8, but spa typing could not distinguish CMRSA5 from CMRSA9 and CMRSA10, and CMRSA3 from CMRSA4 and CMRSA6. However, specific spa types were generally associated with only one PFGE epidemic type. Based on these results, a spa typing guideline for CMRSA isolates was developed and tested using the first 300 MRSA isolates received in 2007 through the Canadian Nosocomial Infection Surveillance Program. CONCLUSIONS: The high concordance of spa types with PFGE epidemic types using this guideline demonstrated the feasibility of spa typing as a more rapid and less technically demanding alternative typing method for MRSA in Canada.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.007 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".