Incidence and Outcomes of Acute Implant Extrusion Following Anterior Cervical Spine Surgery
Bibliographic record
Abstract
STUDY DESIGN: Multi-institutional retrospective case series of 8887 patients who underwent anterior cervical spine surgery. OBJECTIVE: Anterior decompression from discectomy or corpectomy is not without risk. Surgical morbidity ranges from 9% to 20% and is likely underreported. Little is known of the incidence and effects of rare complications on functional outcomes following anterior spinal surgery. In this retrospective review, we examined implant extrusions (IEs) following anterior cervical fusion. METHODS: A retrospective multicenter case series study involving 21 high-volume surgical centers from the AOSpine North America Clinical Research Network. Medical records for 17 625 patients who received cervical spine surgery (levels from C2 to C7) between January 1, 2005, and December 31, 2011, were reviewed to identify occurrence of 21 predefined treatment complications. RESULTS: Following anterior cervical fusion, the incidence of IE ranged from 0.0% to 0.8% across 21 institutions with 11 cases reported. All surgeries involved multiple levels, and 7/11 (64%) involved either multilevel corpectomies or hybrid constructs with at least one adjacent discectomy to a corpectomy. In 7/11 (64%) patients, constructs ended with reconstruction or stabilization at C7. Nine patients required surgery for repair and stabilization following IE. Average length of hospital stay after IE was 5.2 days. Only 2 (18%) had residual deficits after reoperation. CONCLUSIONS: IE is a very rare complication after anterior cervical spine surgery often requiring revision. Constructs requiring multilevel reconstruction, especially at the cervicothoracic junction, have a higher risk for failure, and surgeons should proceed with caution in using an anterior-only approach in these demanding cases. Surgeons can expect most patients to regain function after reoperation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".