Vancomycin Antibiotic Prophylaxis Compared to Cefazolin Increases Risk of Surgical Site Infection Following Spine Surgery
Bibliographic record
Abstract
Study Design Retrospective analysis of randomized controlled trial. Objectives Surgical site infection (SSI) after spine surgery has severe negative health and financial consequences. Surgical antibiotic prophylaxis (SAP) is a routinely used method to prevent SSIs in the spine patient population. The most commonly used antibiotic is cefazolin, with vancomycin often being substituted in the case of penicillin or cephalosporin allergy. Vancomycin as SAP has been associated with increased SSI in the joint replacement literature, but this is not yet well defined in the spinal surgery population. The purpose of this study was to determine whether vancomycin SAP compared to cefazolin SAP is associated with increased risk of SSI. Methods 535 patients, aged 16 years or older, underwent elective multi-level open posterior spinal fusion surgery at the thoracic, thoracolumbar, or lumbar levels. Demographic and operative characteristics as well as post-operative outcomes were compared between the following groups: (1) noninfected-cefazolin, (2) noninfected-vancomycin, (3) infected-cefazolin, and (4) infected-vancomycin. Primary outcomes were superficial and complicated (deep and organ/space) infections. Results The following risk factors for SSI were identified in a logistic regression analysis: vancomycin (OR 2.498, 95% CI, 1.085-5.73, P = 0.031), increasing operating time (OR 1.006, 95% CI, 1.001-1.010 P = 0.010), weight (OR 1.020, 95% CI 1.006-1.034, P = 0.005), revision procedure (OR 2.343, 95% CI 1.283-4.277, P = 0.006), and depression (OR 2.366, 95% CI 1.284-4.360, P = 0.006). Conclusions In open posterior approach spinal fusion surgery, vancomycin SAP is associated with increased risk of infection compared to cefazolin SAP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".