P.137 Biomechanical evaluation of the ProDisc-C stability following graded posterior cervical injury
Bibliographic record
Abstract
Background: There is limited data regarding the development of persistent or recurrent symptoms, and the implications of revision posterior surgery in the setting of previous cervical arthroplasty (CA). The purpose of this study was to analyze segmental kinematics in human cadaveric specimens with and without CA, in the context of graded posterior resection. Methods: Fourteen human cadaveric cervical spines were divided into arthroplasty (ProDisc-C) and control (intact disc) groups. Both groups underwent sequential posterior element resections: unilateral foraminotomy, laminoplasty, and finally laminectomy. Specimens were studied sequentially in two different loading apparatuses during induction of flexion-extension, lateral bending, and axial rotation. Results: Range of motion (ROM) after CA was reduced relative to the control group during axial rotation and lateral bending, but was similar during flexion and extension. With sequential resections, ROM increased by a similar magnitude following foraminotomy and laminoplasty. Laminectomy had a much greater effect following CA compared to the control group, with the largest magnitude of increase in flexion and extension. Conclusions: Foraminotomy and laminoplasty do not seem to induce greater instability in the setting of CA, compared to controls. Laminectomy alone would not be recommended for use with arthroplasty due to the significant change in kinematics, especially in flexion and extension.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".