AO Spine upper cervical injury classification system: a description and reliability study
Bibliographic record
Abstract
BACKGROUND CONTEXT: Prior upper cervical spine injury classification systems have focused on injuries to the craniocervical junction (CCJ), atlas, and dens independently. However, no previous system has classified upper cervical spine injuries using a comprehensive system incorporating all injuries from the occiput to the C2-3 joint. PURPOSE: To (1) determine the accuracy of experts at correctly classifying upper cervical spine injuries based on the recently proposed AO Spine Upper Cervical Injury Classification System (2) to determine their interobserver reliability and (3) identify the intraobserver reproducibility of the experts. STUDY DESIGN/SETTING: International Multi-Center Survey. PATIENT SAMPLE: A survey of international spine surgeons on 29 unique upper cervical spine injuries. OUTCOME MEASURES: Classification accuracy, interobserver reliability, intraobserver reproducibility. METHODS: Thirteen international AO Spine Knowledge Forum Trauma members participated in two live webinar-based classifications of 29 upper cervical spine injuries presented in random order, four weeks apart. Percent agreement with the gold-standard and kappa coefficients (ƙ) were calculated to determine the interobserver reliability and intraobserver reproducibility. RESULTS: Raters demonstrated 80.8% and 82.7% accuracy with identification of the injury classification (combined location and type) on the first and second assessment, respectively. Injury classification intraobserver reproducibility was excellent (mean, [range] ƙ=0.82 [0.58-1.00]). Excellent interobserver reliability was found for injury location (ƙ = 0.922 and ƙ=0.912) on both assessments, while injury type was substantial (ƙ=0.689 and 0.699) on both assessments. This correlated to a substantial overall interobserver reliability (ƙ=0.729 and 0.732). CONCLUSIONS: Early phase validation demonstrated classification of upper cervical spine injuries using the AO Spine Upper Cervical Injury Classification System to be accurate, reliable, and reproducible. Greater than 80% accuracy was detected for injury classification. The intraobserver reproducibility was excellent, while the interobserver reliability was substantial.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".