Identifying Factors Predictive of Atlantoaxial Fusion Failure in Pediatric Patients
Bibliographic record
Abstract
STUDY DESIGN: Multicenter retrospective cohort study with multivariate analysis. OBJECTIVE: To determine factors predictive of posterior atlantoaxial fusion failure in pediatric patients. SUMMARY OF BACKGROUND DATA: Fusion rates for pediatric posterior atlantoaxial arthrodesis have been reported to be high in single-center studies; however, factors predictive of surgical non-union have not been identified by a multicenter study. METHODS: Clinical and surgical details for all patients who underwent posterior atlantoaxial fusion at seven pediatric spine centers from 1995 to 2014 were retrospectively recorded. The primary outcome was surgical failure, defined as either instrumentation failure or fusion failure seen on either plain x-ray or computed tomography scan. Multiple logistic regression analysis was undertaken to identify clinical and technical factors predictive of surgical failure. RESULTS: One hundred thirty-one patients met the inclusion criteria and were included in the analysis. Successful fusion was seen in 117 (89%) of the patients. Of the 14 (11%) patients with failed fusion, the cause was instrumentation failure in 3 patients (2%) and graft failure in 11 (8%). Multivariate analysis identified Down syndrome as the single factor predictive of fusion failure (odds ratio 14.6, 95% confidence interval [3.7-64.0]). CONCLUSION: This retrospective analysis of a multicenter cohort demonstrates that although posterior pediatric atlantoaxial fusion success rates are generally high, Down syndrome is a risk factor that significantly predicts the possibility of surgical failure. LEVEL OF EVIDENCE: 3.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".