Carotid Artery Injury in Anterior Cervical Spine Surgery: Multicenter Cohort Study and Literature Review
Bibliographic record
Abstract
STUDY DESIGN: Retrospective study and literature review. OBJECTIVE: To provide more comprehensive data about carotid artery injury (CAI) or cerebrovascular accident (CVA) related to anterior cervical spine surgery. METHODS: We conducted a retrospective, multicenter, case series study involving 21 high-volume surgical centers from the AOSpine North America Clinical Research Network. Medical records of 17 625 patients who went through cervical spine surgery (levels from C2 to C7) between January 1, 2005, and December 31, 2011, were analyzed. Also, we performed a literature review using Medline and PubMed databases. The following terms were used alone, and in combination, to search for relevant articles: cervical, spine, surgery, complication, iatrogenic, carotid artery, injury, cerebrovascular accident, CVA, and carotid stenosis. RESULTS: Among 17 625 patients that were analyzed, no cases were reported to experienced CAI or CVA after cervical spine surgery. Nevertheless, in our PubMed search we found 157 articles, but only 5 articles matched our study objective criteria; 2 cases were reported to present CAI and 3 cases presented CVA. CONCLUSIONS: CAI and CVA related to anterior cervical spine surgeries are extremely rare. We were not able to find neither in our retrospective study nor in our literature research a correlation between the type or length of anterior cervical spine procedure with CVA or CAI complications. However, surgeons should be aware of the possibility of vascular complications and minimize intraoperative direct vascular manipulations or retraction. Preoperative screening for underlying vascular pathology and risk factors is also important.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".