Alcoholic versus aqueous chlorhexidine for skin antisepsis: the AVALANCHE trial
Bibliographic record
Abstract
<h3>BACKGROUND:</h3> Preoperative skin antisepsis is routine practice. We compared alcoholic chlorhexidine with aqueous chlorhexidine for skin antisepsis to prevent surgical site infection after minor skin excisions in general practice. <h3>METHODS:</h3> We conducted this prospective, multicentre, randomized controlled trial in 4 private general practices in North Queensland, Australia, from October 2015 to August 2016. Consecutive adult patients presenting for minor skin excisions were randomly assigned to undergo preoperative skin antisepsis with 0.5% chlorhexidine in 70% ethanol (intervention) or 0.5% chlorhexidine aqueous solution (control). Our primary outcome was surgical site infection within 30 days of excision. We also measured the incidence of adverse reactions. <h3>RESULTS:</h3> A total of 916 patients were included in the study: 454 underwent antisepsis with alcoholic chlorhexidine and 462 with aqueous chlorhexidine. Of these, 909 completed follow-up. In the intention-to-treat analysis of cases available at follow-up, there was no significant difference in the incidence of surgical site infection between the alcoholic chlorhexidine arm (5.8%, 95% confidence interval [CI] 3.6% to 7.9%) and the aqueous chlorhexidine arm (6.8%, 95% CI 4.5% to 9.1%). The attributable risk reduction was 0.010 (95% CI –0.021 to 0.042), the relative risk was 0.85 (95% CI 0.51 to 1.41), and the number needed to treat to benefit was 100. Per protocol and sensitivity analyses produced similar results. The incidence of adverse reactions was low, with no difference between groups (<i>p</i> = 0.6). <h3>INTERPRETATION:</h3> There was no significant difference in efficacy between alcoholic and aqueous chlorhexidine for the prevention of surgical site infection after minor skin excisions in general practice. <b>Trial registration:</b>https://www.anzctr.org.au, no. ACTRN12615001045505
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".