Attempted eradication of methicillin‐resistant <i>Staphylococcus aureus</i> colonisation in horses on two farms
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: Methicillin-resistant Staphylococcus aureus (MRSA) is an emerging equine and zoonotic pathogen. Infection control protocols can be used to control MRSA in human hospitals, but measures to eradicate MRSA on horse farms have not been evaluated. OBJECTIVES: To describe an MRSA eradication programme that was used to attempt to eliminate MRSA colonisation among horses and horse personnel on 2 equine farms. METHODS: Active surveillance cultures and infection control protocols were implemented on 2 farms with endemic MRSA. RESULTS: Active screening and strict implementation of infection control protocols resulted in a rapid decrease in number of colonised horses on both farms. The majority of horses eliminated MRSA without antimicrobial treatment. On one farm colonisation was eradicated, while only 2 (3%) colonised horses remained on the other farm at the end of the study. CONCLUSIONS: Although at this stage the benefit of eradication of MRSA from populations of horses and cost-benefit studies have not been established, this study illustrates that short-term eradication can be achieved with a policy of segregation, enhanced infection control precautions and repeated testing of groups of animals. POTENTIAL RELEVANCE: Infection control practices should form the basis of MRSA control. Antimicrobial therapy does not appear to be required for eradication of MRSA colonisation in horses and control of MRSA on farms. In appropriate circumstances, these methods may be useful for controlling the spread of this potentially serious pathogen.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".