Alcohol-based antisepsis without the use of chlorhexidine for arthroscopy in horses
Bibliographic record
Abstract
• Immediate bacterial reduction between tested protocols was not different. • Sustained bacterial reduction between tested protocols was not different. • Sole alcohol-based antisepsis demonstrated efficacy for equine hock arthroscopy. Alcohol-based antisepsis has shown experimentally to be as effective as 4 % chlorhexidine gluconate (CHG) at reducing bacterial counts (colony forming units; CFU) on equine skin. Our objectives were to determine the immediate and post-surgical reduction in CFU/mL on equine skin prepared with CHG-based or 70 % isopropyl alcohol (IPA)-based (without CHG) protocols in a clinical setting with arthroscopic surgery. Our hypotheses were that the log 10 CFU/mL reduction would not significantly differ between protocols immediately after preparation or at the end of surgery. Six horses underwent a 40 min bilateral tarsocrural joint arthroscopy with each limb randomly assigned to Group A or B. Group A tarsocrural joints underwent a rough scrub using 4 % CHG and a 5 min sterile scrub using 2 % CHG. Group B underwent a rough scrub with neutral soap followed by a 90 s sterile scrub with IPA. Samples were collected before rough scrub (T0), immediately after sterile scrub (T1), and end of surgery (T2). CFU/mL were determined in duplicate and were log-transformed and averaged. ANOVA models compared the immediate reduction (T0-T1) and sustained reduction (T0-T2) between treatment groups. The immediate and sustained log10CFU/mL reduction between groups was not different ( P = 0.46, P = 0.42). Both groups achieved at least a 2-log immediate and sustained reduction. Limitations include small population size, short surgical duration, length of follow-up, and researchers were not blinded to treatment during sampling. This study demonstrates efficacy of IPA-based antisepsis, without the need for CHG, and supports further investigation in clinical surgery as an acceptable method of surgical site preparation.
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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 | 0.001 |
| 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) | 0.002 | 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".