Reliability of the Thoracolumbar Injury Classification and Severity Score and Comparison With the Denis Classification for Injury to the Thoracic and Lumbar Spine
Bibliographic record
Abstract
In Brief Study Design. This study is a series of thoracic and lumbar spine fracture cases to assess the reliability of thoracolumbar injury classification and severity score (TLICS) in simulated clinical scenarios. Objective. To determine the inter- and intraobserver reliability of TLICS compared with the Denis classification system, and to assess differences based on rater characteristics. Summary of Background Data. Thoracolumbar injury severity score and TLICS have been subjected to reliability testing using less robust statistical analysis. Both systems have demonstrated poor to good reliability, with particularly weak agreement on the status of the posterior ligamentous complex. Methods. Fifty-four spine fracture cases were selected from a chart review. These cases were scored on 2 occasions by 11 experts using both TLICS and the Denis classification systems. Reliability was assessed using a generalizability coefficient. The primary outcome was interobserver reliability. Secondary outcomes were intraobserver reliability, difference between orthopedic and neurosurgeons, as well as trainees and consultants, and correlation with treatment recommendations. Results. TLICS demonstrated good interobserver agreement of 0.73 to 0.74. The posterior ligamentous complex component was the least reliable. The Denis classification also demonstrated good reliability between observers, but was least reliable for flexion-distraction injuries. In addition, interobserver reliability between the Denis classification and TLICS morphology subcomponent was strong. TLICS also predicted the need for operative treatment as determined by the experts scoring the injuries. Conclusion. TLICS is a reliable system for assessing fractures of the thoracic and lumbar spine when used by experts. Similar to previous studies, the posterior ligamentous complex subcomponent score was the least reliable component. Reliability assessment using a generalizability coefficient is a robust method for validating fracture classifications. Reliability of thoracolumbar spine injury classification and severity score was assessed using generalizability analysis of 54 spine fracture cases rated by 11 experts. There was good interand intraobserver reliability, weakest for the posterior ligamentous complex component within thoracolumbar spine injury classification and severity score. There was also good agreement between the Denis classification and thoracolumbar spine injury classifi cation and severity score morphology score.
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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 | 0.020 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".