Bacterial Genotype, Carrier Risk Factors, and an Antimicrobial Stewardship Approach Relevant To Methicillin-resistant<i>Staphylococcus Aureus</i>Prevalence in a Population of Macaques Housed in a Research Facility
Bibliographic record
Abstract
Methicillin-resistantStaphylococcus aureus(MRSA) remains a significant problem for human and animal health and can negatively affect the health status of macaques and other nonhuman primates (NHP) in research colonies. However, few publications provide guidance on the prevalence, genotype, or risk factors for macaques with MRSA and even fewer on how to effectively respond to MRSA once identified in a population. After having a clinical case of MRSA in a rhesus macaque, we sought to determine the MRSA carrier prevalence, risk factors, and genotypes of MRSA in a population of research NHPs. Over a 6-wk period in 2015, we collected nasal swabs from 298 NHPs. MRSA was isolated from 28% (n= 83). We then reviewed each macaque's medical record for a variety of variables including animal housing room, sex, age, number of antibiotic courses, number of surgical interventions, and SIV status. Analysis of these data suggests that MRSA carriage is associated with the room location, age of the animal, SIV status, and the number of antibiotic courses. We used multilocus sequence typing andspatyping on a subset of MRSA and MSSA isolates to determine whether the MRSA present in NHPs was comparable with common human strains. Two MRSA sequence types were predominant: ST188 and a novel MRSA genotype, neither of which is a common human isolate in the United States. We subsequently implemented antimicrobial stewardship practices (significantly reducing antimicrobial use) and then resampled the colony in 2018 and found that MRSA carriage had fallen to 9% (26/285). These data suggest that, as in humans, macaques may have a high carrier status of MRSA despite low clinically apparent disease. Implementing strategic antimicrobial stewardship practices resulted in a marked reduction in MRSA carriage in the NHP colony, highlighting the importance of limiting antimicrobial use when possible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".