The Influence of Comminution and Posterior Ligamentous Complex Integrity on Treatment Decision Making in Thoracolumbar Burst Fractures Without Neurologic Deficit?
Bibliographic record
Abstract
STUDY DESIGN: A prospective study. OBJECTIVE: to evaluate the impact of vertebral body comminution and Posterior Ligamentous Complex (PLC) integrity on the treatment recommendations of thoracolumbar fractures among an expert panel of 22 spine surgeons. METHODS: A review of 183 prospectively collected thoracolumbar burst fracture computed tomography (CT) scans by an expert panel of 22 trauma spine surgeons to assess vertebral body comminution and PLC integrity. This study is a sub-study of a prospective observational study of thoracolumbar burst fractures (Spine TL A3/A4). Each expert was asked to grade the degree of comminution and certainty about the PLC disruption from 0 to 100, with 0 representing the intact vertebral body or intact PLC and 100 representing complete comminution or complete PLC disruption, respectively. RESULTS: ≥45% comminution had a 74% chance of having surgery recommended, while <25% comminution had an 86.3% chance of non-surgical treatment. A comminution from 25 to 45% had a 57% chance of non-surgical management. ≥55% PLC injury certainity had a 97% chance of having surgery, and ≥45-55% PLC injury certainty had a 65%. <20% PLC injury had a 64% chance of having non-operative treatment. A 20 to 45% PLC injury certainity had a 56% chance of non-surgical management. There was fair inter-rater agreement on the degree of comminution (ICC .57 [95% CI 0.52-.63]) and the PLC integrity (ICC .42 [95% CI 0.37-.48]). CONCLUSION: The study concludes that vetebral comminution and PLC integrity are major dterminant in decision making of thoracolumbar fractures without neurological deficit. However, more objective, reliable, and accurate methods of assessment of these variables are warranted.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".