Intraoperative Adverse Events and Related Postoperative Complications in Spine Surgery: Implications for Enhancing Patient Safety Founded on Evidence-Based Protocols
Bibliographic record
Abstract
STUDY DESIGN: Prospective observational study. OBJECTIVE: To assess the incidence and clinical consequence of intraoperative adverse events from a wide variety of spinal surgical procedures. SUMMARY OF BACKGROUND DATA: In this study, adverse events were defined as any unexpected or undesirable event(s) occurring as a result of spinal surgery. A complication was defined as a disease or disorder, which, as a consequence of a surgical procedure, will negatively affect the outcome of the patient. We hypothesized that most adverse events would not result in complications that would be normally flagged through traditional practice audit approaches. By defining the incidence and types of adverse events seen in a spine surgical practice, we hope to develop preventative approaches to enhance patient safety. METHODS: All postoperative clinical sequelae (i.e., complications) were prospectively identified, classified as to type, and graded (0 [none] to IV [death]) in 700 consecutive patients who underwent spine surgery (excluding > 300-day surgery microdiscectomies) at a university center from January 2002 to June 2003. To confirm data accuracy and assess the clinical sequelae of any adverse events, the medical records of these 700 patients were reviewed. RESULTS: The overall incidence of intraoperative adverse events was 14% (98/700). A total of 23 adverse events led to postoperative clinical sequelae for an overall intraoperative complication incidence of 3.2% (23/700). Specific adverse events included dural tears (n = 58), spinal instrumentation-related events (n = 12), blood loss exceeding 5000 mL (n = 10), anesthesia/medical (n = 4), suspected or actual vertebral artery injury (n = 3), approach-related events (n = 3), esophageal/pharyngeal injury (n = 2), and miscellaneous (n = 6). CONCLUSIONS: Adverse events can frequently occur (14%) during spinal surgery, however, the majority (76.5%) are not associated with complications. Improved patient safety can only be maximized by independent practice audit and the development of prospective methods to record adverse event data so that enhanced, evidence-based, clinical protocols can be developed.
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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 | 0.425 | 0.495 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".