Prevention of Surgical Site Infections in Spine Surgery: An International Survey of Clinical Practices Among Expert Spine Surgeons
Bibliographic record
Abstract
STUDY DESIGN: Questionnaire-based survey. OBJECTIVES: Surgical site infection (SSI) is a common complication in spine surgery but universal guidelines for SSI prevention are lacking. The objectives of this study are to depict a global status quo on implemented prevention strategies in spine surgery, common themes of practice and determine key areas for future research. METHODS: An 80-item survey was distributed among spine surgeons worldwide via email. The questionnaire was designed and approved by an International Consensus Group on spine SSI. Consensus was defined as more than 60% of participants agreeing to a specific prevention strategy. RESULTS: (SA) is not common, whereas preoperative decolonization is performed in almost half of all hospitals. Body mass index (BMI) was not important for surgery planning. In contrast, elevated HbA1c level and hypoalbuminemia were often considered as reasons to postpone surgery. Cefazoline is the common drug for antimicrobial prophylaxis. Alcohol-based chlorhexidine is mainly used for skin disinfection. Double-gloving, wound irrigation, and tissue-conserving surgical techniques are routine in the operating room (OR). Local antibiotic administration is not common. Wound closure techniques and postoperative wound dressing routines vary greatly between the participating institutions. CONCLUSIONS: With this study we provide an international overview on the heterogeneity of SSI prevention strategies in spine surgery. We demonstrated a large heterogeneity for pre-, peri- and postoperative measures to prevent SSI. Our data illustrated the need for developing universal guidelines and for testing areas of controversy in prospective clinical trials.
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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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".