Longitudinal Investigation of Methicillin‐Resistant <i>Staphylococcus aureus</i> in Piglets
Bibliographic record
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA) has emerged as an important public health concern and pigs have been implicated in human infections. Cross-sectional studies have demonstrated that MRSA can be commonly found in pigs internationally, but little is known about age-related changes in MRSA colonization. This study evaluated MRSA colonization in piglets in a longitudinal manner. Serial nasal swabs were collected from piglets born to 10 healthy sows. The prevalence of MRSA colonization on days 1, 3, 7, 14 and 21 was 1% (1/100), 6.2% (3/97), 8.5% (8/94), 4.4% (4/91) and 20% (18/91) respectively, with an overall pre-weaning prevalence of 34.5%. The prevalence on days 28, 42, 56 and 70 was 34% (31/91), 65% (57/88), 50% (44/88) and 42% (36/87) respectively, with an overall post-weaning prevalence of 85%. Eighty-four percent of piglets from negative sows and 100% of piglets from positive sows that survived at least until the time of weaning were colonized with MRSA at one or more times during the study. There was a significant association between sow and piglet colonization. The age of the piglet was significantly associated with the probability of colonization. No piglets or sows received antimicrobials during the study period. These results indicate that age must be considered when designing surveillance programmes and interpreting results of different studies on MRSA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".