Development of antimicrobial drug resistance in rectal Escherichia coli isolates from dogs hospitalized in an intensive care unit
Bibliographic record
Abstract
OBJECTIVE: To determine whether duration of hospitalization in the intensive care unit (ICU) of a veterinary teaching hospital was associated with prevalence of antimicrobial resistance among rectal Escherichia coli isolates from dogs, whether antimicrobial treatment was associated with prevalence of antimicrobial resistance, and whether there were associations among antimicrobial drugs to which isolates were resistant. DESIGN: Prospective observational study. ANIMALS: 116 dogs hospitalized in an ICU for >or= 3 days. PROCEDURES: Rectal swab specimens were obtained every 3 days and submitted for bacterial culture for E coli. Isolates were tested for susceptibility to 12 antimicrobial agents by means of disk diffusion. RESULTS: For each additional day that a dog was hospitalized in the ICU, the odds of being colonized with an E coli isolate resistant to 1 or more of the 12 antimicrobials tested increased by a factor of 1.5, independent of antimicrobial treatment. Dogs that were treated with enrofloxacin were 25.6 times as likely to be colonized by a quinolone-resistant E coli strain as were dogs that did not receive any antimicrobials. Significant correlations were found for resistance to agents in the extended-spectrum cephalosporin group and the quinolone group. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggested that the proportion of rectal E coli isolates obtained from dogs housed for >or= 3 days in a veterinary teaching hospital ICU that were resistant to antimicrobial agents increased as the duration of hospitalization in the ICU increased. Thus, ICU hospitalization time should be as short as possible to prevent development of antimicrobial resistance among rectal E coli isolates.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".