The Use of Antibiotics-Impregnated Bone Cement in Reducing Surgical Site Infections in Spine Surgery: A Systematic Review
Bibliographic record
Abstract
Abstract Spine surgeries are one of the most widely performed operations in orthopaedic surgery and neurosurgery. However, one of the most common complications of spine surgeries is surgical site infection (SSI), which is associated with various postoperative morbidities. The use of antibiotics-impregnated bone cement (AIBC) is common in orthopaedic surgeries. Therefore, we aim to provide a comprehensive review of AIBC use in spine surgeries. Data were gathered from PubMed, Europe PMC, and ScienceDirect using keywords associated with AIBC and spine surgeries. We included all publications associated with AIBC and spine surgeries. Studies without full papers, non-English publications, review articles, and animal or cadaveric studies were excluded. The quality of each included studies were assessed using the Newcastle Ottawa Scale and the Joanna Briggs Institute Critical Appraisal for case reports, case series, and quasi-experimental studies. Fifteen studies of 322 patients using AIBC in spine surgery were included. Ten of 15 studies reported 100% infection-free events with AIBC administration with or without given systemic antibiotics. Two studies did not report 100% infection-free events due to methicillin-resistant Staphylococcus aureus (MRSA) infections and technical causes. Three studies reported the use of AIBC without disclosing outcomes. Various types of bacteria ranging from methicillin-sensitive Staphylococcus aureus to MRSA have been discovered, with polymethylmethacrylate and vancomycin being the most frequently used AIBCs. AIBC can be used to prevent postoperative infections due to its high effectiveness, easy administration, and no side effects. Further studies are needed to determine the most appropriate antibiotics, dose, and type of cement.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".