SURGICAL SITE INFECTION AFTER SPINAL INSTRUMENTATION: REVIEW OF PATHOGENESIS, DIAGNOSIS, PREVENTION AND TREATMENT
Bibliographic record
Abstract
Objective: Despite the successful application of spinal instrumentation surgery, the development of surgical site infections (SSIs) remains inevitable even in the most experienced neurosurgery clinics.The aim of this study was to analyze potential risk factors, reassess diagnosis and treatment, and discuss outcomes in line with the literature. Materials and Methods:The records of 1564 patients who underwent spinal instrumentation surgery between 2016 and 2023 were retrospectively reviewed.Among these patients, 297 developed superficial or deep SSIs in the postoperative period.Diagnosis was based on postoperative positive wound cultures, intraoperative cultures, serum procalcitonin and C-reactive protein (CRP) levels measured in the postoperative period, and gadolinium-enhanced magnetic resonance imaging (MRI) and computed tomography scan.Demographic characteristics and preoperative risk factors of the patients were analyzed.Results: SSIs were observed in 297 (18.9%) out of 1564 patients who underwent spinal instrumentation surgery.Multiple risk factors for spinal infections following spinal instrumentation surgery, which can manifest in both the early and delayed postoperative periods, were identified.Early diagnosis and prompt initiation of appropriate treatment were associated with better prognosis in 215 patients.Among the 82 patients diagnosed late, all underwent revision surgery for spinal implant removal due to failed medical treatment, with clinical outcomes in 23 of these patients not meeting post-operative expectations.The relationship between early and delayed diagnosis and the need for reoperation were statistically significant (p<0.001).Reoperation was required in 92.7% of patients with delayed diagnosis compared with 15.3% of patients with early diagnosis, indicating an approximately 11.6-fold higher risk of reoperation in patients with delayed diagnosis.Conclusion: Intraoperative culture results are the gold standard for diagnosing SSIs after spinal instrumentation surgery and are also valuable for selecting antimicrobial agents.Monitoring procalcitonin and CRP levels, along with MRI, is highly beneficial for diagnosis.Early detection requires fewer surgical interventions and improves clinical outcomes
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".