Preoperative Skin Antiseptic Preparations for Preventing Surgical Site Infections: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To evaluate the clinical effectiveness of preoperative skin antiseptic preparations and application techniques for the prevention of surgical site infections (SSIs). DESIGN: Systematic review of the literature using Medline, EMBASE, and other databases, for the period January 2001 to June 2011. METHODS: Comparative studies (including randomized and nonrandomized trials) of preoperative skin antisepsis preparations and application techniques were included. Two researchers reviewed each study and extracted data using standardized tables developed before the study. Studies were reviewed for their methodological quality and clinical findings. RESULTS: Twenty studies (n = 9,520 patients) were included in the review. The results indicated that presurgical antiseptic showering is effective for reducing skin flora and may reduce SSI rates. Given the heterogeneity of the studies and the results, conclusions about which antiseptic is more effective at reducing SSIs cannot be drawn. CONCLUSIONS: The evidence suggests that preoperative antiseptic showers reduce bacterial colonization and may be effective at preventing SSIs. The antiseptic application method is inconsequential, and data are lacking to suggest which antiseptic solution is the most effective. Disinfectant products are often mixed with alcohol or water, which makes it difficult to form overall conclusions regarding an active ingredient. Large, well-conducted randomized controlled trials with consistent protocols comparing agents in the same bases are needed to provide unequivocal evidence on the effectiveness of one antiseptic preparation over another for the prevention of SSIs.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".