Validation of the AO Spine Sacral Classification System: Reliability Among Surgeons Worldwide.
Bibliographic record
Abstract
OBJECTIVES: To (1) demonstrate that the AO Spine Sacral Classification System can be reliably applied by general orthopaedic surgeons and subspecialists universally around the world and (2) delineate those injury subtypes that are most difficult to classify reliably to refine the classification before evaluating clinical outcomes. DESIGN: Agreement study. SETTING: All-level trauma centers, worldwide. PARTICIPANTS: One hundred seventy-two members of the AO Trauma and AO Spine community. INTERVENTION: The AO Sacral Classification System was applied by each surgeon to 26 cases in 2 independent assessments performed 3 weeks apart. MAIN OUTCOME MEASUREMENTS: Interobserver reliability and intraobserver reproducibility. RESULTS: A total of 8097 case assessments were performed. The kappa coefficient for interobserver agreement for all cases was 0.72/0.75 (assessment 1/assessment 2), representing substantial reliability. When comparing classification grading (A/B/C) regardless of subtype, the kappa coefficient was 0.84/0.85, corresponding to excellent reliability. The kappa coefficients for interobserver reliability were 0.95/0.93 for type A fractures, 0.78/0.79 for type B fractures, and 0.80/0.83 for type C fractures. The overall kappa statistic for intraobserver reliability was 0.82 (range 0.18-1.00), representing excellent reproducibility. When only evaluating morphology type (A/B/C), the average kappa value was 0.87 (range 0.18-1.00), representing excellent reproducibility. CONCLUSION: The AO Spine Sacral Classification System is universally reliable among general orthopaedic surgeons and subspecialists worldwide, with substantial interobserver and excellent intraobserver reliability.
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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 | 0.041 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".