Evaluation of the efficacy of disinfectant footbaths as used in veterinary hospitals
Bibliographic record
Abstract
OBJECTIVE: To evaluate efficacy of 2 disinfectants as used in footbaths in veterinary hospitals for reducing bacterial contamination of footwear. DESIGN: Prospective study. SAMPLE POPULATION: Bacteria collected from the soles of rubber boots after experimental contamination and exposure to disinfectant solutions or control conditions. PROCEDURES: Investigators contaminated boots by walking through soiled straw animal bedding. Swab samples were collected from the sole of 1 boot (right or left) without treatment. The other boot was briefly immersed in a disinfectant solution (either a quaternary ammonium compound [QAC] or a peroxygen compound) or water, and samples were collected after 7 minutes. Differences associated with the experimental treatments were analyzed statistically. Veterinary teaching hospitals (VTHs) in the United States and Canada were contacted to obtain information about the use of footbaths. RESULTS: Mean bacterial concentrations from peroxygen-treated boots were 67% to 78% lower, compared with samples taken from untreated boots. In contrast, there were no statistically detectable differences in mean bacterial concentrations in samples taken from QAC- or water-treated boots, compared with control boots. Disinfectant footbaths were reportedly used in 30 of 31 VTHs. CONCLUSIONS AND CLINICAL RELEVANCE: Disinfectant solution containing peroxygen applied in a footbath reduced bacterial concentrations on rubber boots under conditions representative of those found in VTHs. Footbaths are commonly used as a method to control infectious diseases in veterinary hospitals. Disinfectant footbaths should not be expected to sterilize footwear, but they may help in reducing the risk for nosocomial infection when used with effective disinfectants.
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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 | 0.002 | 0.005 |
| 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 | 0.000 | 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".