Impact of an antimicrobial dressing in reducing surgical site infections in cardiac surgery patients.
Bibliographic record
Abstract
UNLABELLED: xBxxaxcxkground. In addition to prevention guidelines already in place, the effectiveness of an antimicrobial dressing on the occurrence of surgical site infections (SSIs) among adult patients undergoing cardiac surgery was evaluated. METHODS: A house-wide replacement of the plain postoperative gauze dressing with a sterile dressing impregnated with 0.2% polyhexamethylene biguanide directly on the incision after closure in the operation room was performed. From May 2005 to March 2007, 1658 patients were enrolled in this study. Surgical site infections were identified using the Centers for Disease Control and Prevention standard criteria. RESULTS: Of the 1658 patients enrolled, 1399 patients were included in the analysis, 692 with the plain dressing and 707 with antimicrobial dressing. The overall and leg site infection rate was significantly higher in the plain dressing group compared to the antimicrobial group but similar in the sternal site. Overall, the antimicrobial dressings significantly reduced infection (OR 0.58 [0.38-0.89]). Obesity was also a strong independent predictor of SSI regardless of the site of surgery. Increasing age at surgery and left ventricular ejection fraction of 30%-49% were also independent predictors of infection. CONCLUSION: The antimicrobial dressing had a positive effect by reducing the infection rate, especially for leg incisions using conventional open techniques, and could be a worthwhile addition in conjunction with a strategic program. .
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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 | 0.002 |
| 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".