Prospective, randomised clinical trial of four different presurgical hand antiseptic techniques in equine surgery
Bibliographic record
Abstract
BACKGROUND: Currently, the World Health Organization recommends the use of alcohol-based hand rubs (ABR) for surgical hand preparation in human surgery. When disinfecting soaps are used, a rubbing technique causes less skin irritation than brush scrubbing. Based on a recent survey, most equine surgeons still use disinfecting soap. The efficacy of scrubbing vs. rubbing and the use of sole ABR compared with chlorhexidine (CHx)- based products has not been evaluated in the equine surgical setting. OBJECTIVES: To compare four surgical hand antisepsis techniques in equine surgery for reduction of aerobic bacterial counts from pre- to post-preparation (immediate efficacy) and at the end of surgery (sustained efficacy). STUDY DESIGN: Randomised, prospective clinical trial. METHODS: A 4% CHx-based product applied with either a scrub or rub technique, one sole ABR (ET; 80% ethanol) and one CHx/alcohol-combination (CHx/ET; 1% CHx and 61% ethanol) product both applied with a rub technique were evaluated. Samples were collected by glove juice technique and cultured on 3M™ Petrifilm plates and counted using a 3M™ Petrifilm plate reader. RESULTS: colony forming unit (CFU) reduction was 2.4 for CHx-scrub, 2.8 for CHx-rub, 3.1 for CHx/ET and 2.1 for ET. CHx/ET resulted in significantly lower bacterial counts than CHx-scrub (P<0.005) and ET (P<0.001) while CHx-rub resulted in significantly lower counts than ET (P<0.001). At the end of surgery bacterial counts were the lowest for CHx-rub, significantly lower than CHx/ET (P<0.001) and ET (P<0.001). There was no difference between CHx-rub and -scrub techniques (P = 0.7). MAIN LIMITATIONS: Bacterial counts were used as the outcome measure rather than prevalence of surgical site infection, and the effect of hand preparation on skin health was not assessed. CONCLUSIONS: CFU counts more effectively than CHx products. When using CHx soaps in the equine setting, hand-rub is as effective as a hand-scrub-technique.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".