Antimicrobial susceptibility of porcine Pasteurella multocida, Streptococcus suis, and Actinobacillus pleuropneumoniae from the United States and Canada, 2001 to 2010
Bibliographic record
Abstract
Objective: To provide data on the in vitro antimicrobial susceptibility of three bacterial respiratory disease pathogens isolated from swine across the United States and Canada over the period 2001 to 2010. Materials and methods: A total of 1097 Actinobacillus pleuropneumoniae, 2389 Pasteurella multocida, and 2617 Streptococcus suis isolates recovered from diseased or dead swine from North America over a 10-year period were tested for in vitro susceptibility to antimicrobial agents approved for treatment of swine respiratory disease (SRD). Clinical and Laboratory Standards Institute standardized methods were used to determine the minimum inhibitory concentrations (MICs) of ceftiofur, enrofloxacin, florfenicol, penicillin, tetracycline, tilmicosin, and tulathromycin. Results: Over the years 2001to 2010, A pleuropneumoniae and P multocida remained susceptible to ceftiofur, enrofloxacin, florfenicol, tilmicosin, and tulathromycin, and S suis remained susceptible to ceftiofur, enrofloxacin, and florfenicol. Low penicillin MIC values for P multocida and S suis and higher MIC values for A pleuropneumoniae were also seen. Most isolates of all three organisms were resistant to tetracycline over the 10 years of the survey. Implications: Monitoring antimicrobial susceptibility among swine pathogens over time provides valuable information about changes which may be occurring in the antimicrobial susceptibility of these organisms and is an important tool in effective antimicrobial therapy. Surveillance of the in vitro susceptibility of these SRD pathogens continues to be an important component in antimicrobial stewardship.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".