Finite Element Analysis and Biomechanical Comparison of Short Posterior Spinal Instrumentation with Divergent Bridge Construct versus Parallel Tension Band Construct for Thoracolumbar Spine Fractures
Bibliographic record
Abstract
The ideal treatment for unstable thoracolumbar fractures remains controversial with posterior reduction and stabilization, anterior reduction and stabilization, combined posterior and anterior reduction and stabilization, and even nonoperative management advocated. Short segment posterior osteosynthesis of these fractures has less comorbidities compared with the other operative approaches but settles into kyphosis over time. Biomechanical comparison of the divergent bridge construct versus the parallel tension band construct was performed for anteriorly destabilized T11-L1 spine segments using three different models: (1) finite element analysis (FEA), (2) a synthetic model, and (3) a human cadaveric model. Outcomes measured were construct stiffness and ultimate failure load. Our objective was to determine if the divergent pedicle screw bridge construct would provide more resistance to kyphotic deforming forces. All three modalities showed greater stiffness with the divergent bridge construct. The FEA calculated a stiffness of 21.6 N/m for the tension band construct versus 34.1 N/m for the divergent bridge construct. The synthetic model resulted in a mean stiffness of 17.3 N/m for parallel tension band versus 20.6 N/m for the divergent bridge (p = 0.03), whereas the cadaveric model had an average stiffness of 15.2 N/m in the parallel tension band compared with 18.4 N/m for the divergent bridge (p = 0.02). Ultimate failure load with the cadaveric model was found to be 622 N for the divergent bridge construct versus 419 N (p = 0.15) for the parallel tension band construct. This study confirms our clinical experience that the short posterior divergent bridge construct provides greater stiffness for the management of unstable thoracolumbar fractures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".