Comparison between antimicrobial-coated sutures and uncoated sutures for the prevention of surgical site infections in plastic surgery: a double blind control trial.
Bibliographic record
Abstract
OBJECTIVE: Surgical site infection (SSI) produces considerable morbidity and increases health care costs. One of its causes is microbial adherence to the surgical sutures surface. A strategy to avoid microbial colonization is the use of antimicrobial-impregnated sutures. Recently absorbable sutures treated with chlorhexidine (CHX) have been developed. Our study purpose was to compare CHX-coated and uncoated suture in elective plastic surgery. PATIENTS AND METHODS: We conducted a randomized, double-blind, single-centre controlled trial of 18 patients undergoing elective bilateral mammary surgery and 18 patients undergoing skin lesions removals. Patients were divided into 2 groups receiving antibacterial-coated (study group) and uncoated (controlled group) sutures for wound closure. Patients were evaluated for scar results and signs of SSIs were monitored over a period of 30 days (or 1 year in case of prosthetic surgery). Statistical comparison was performed using dependent t-tests for paired samples. RESULTS: For patients undergoing mammary surgery, based on Vancouver Scale, there were no significant differences between the two groups. We noticed that in 8 patients the vertical scars belonging to the control group were larger than the contralateral 8 vertical sutures belonging to the study group. For patients undergoing skin surgery, surgical wounds treated with uncoated sutures were significantly more erythematous than the ones belonging to the study group (Media: 0,8333% vs. 1,5556%, respectively; standard deviation: 9,235 vs. 0,6157; 95%; p=0.0092). CONCLUSIONS: No wounds infection was reported between the two groups. Based on our experience, we conclude that the use of CHX-coated sutures should be considered in case of inflamed lesions removal. Further studies are needed to validate our results.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".