Influence of clipping on bacterial contamination of canine arthrocentesis sites before and after skin preparation
Bibliographic record
Abstract
OBJECTIVE: To determine the influence of hair removal as part of the aseptic skin preparation of canine arthrocentesis sites and to characterize the bacterial flora remaining after aseptic skin preparation. STUDY DESIGN: Randomized controlled trial. STUDY POPULATION: Thirteen shorthaired beagle-cross dogs. METHODS: A coin toss was used to randomly determine to have one carpus, elbow, tarsus, and stifle clipped. The contralateral side was left unclipped. Aseptic skin preparation was performed on all sites with 4% chlorhexidine followed by 70% isopropyl alcohol. The skin of each site was sampled for aerobic and anaerobic bacterial cultures before and after aseptic skin preparation. Bacterial cultures were submitted for laboratory testing to determine the colony-forming units (CFU) of bacteria and bacterial species isolated for each site. RESULTS: Each group (clipped and unclipped) included 52 sites. Aseptic skin preparation reduced bacterial CFU in both groups. There was no association between values for CFU per milliliter after skin preparation of dogs and side (P = .07), joint (P = .71), pre-aseptic skin preparation CFU (P = .94), or clipping (P = .42). Staphylococcus spp were the most common of the bacterial species cultured. CONCLUSION: In clean shorthaired dogs without visible evidence of dermatological disease, leaving arthrocentesis sites unclipped rather than performing traditional surgical clipping did not result in increased bacterial skin counts after aseptic skin preparation. CLINICAL SIGNIFICANCE: In this study we did not find evidence to support that clipping of canine arthrocentesis sites is required for effective aseptic skin preparation. A prospective clinical trial is required to determine whether a change in practice would be associated with increased morbidity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".