The Evaluation of a Novel Three-Dimensional Printed Expandable Pedicle Screw Sleeve Insert
Bibliographic record
Abstract
When used in combination with decompression, spinal fusion is a successful procedure for treating patients with spinal stenosis and degenerative spondylolisthesis. While a number of auxiliary devices have been proposed to enhance the fixation of the screw within the pedicle and vertebral body, there is conflicting information regarding the efficacy of their use. Therefore, the aim of this study was to determine the ability of a novel expandable pedicle screw to improve the fixation of the pedicle screw within the pedicle and vertebral body. A three-dimensional (3D) printed, screw sleeve was designed that expanded within the pedicle and vertebral body when a standard pedicle screw was inserted into it. The left and right pedicle of ten (N = 10) cadaveric lumbar spine specimens (L3–L5) were randomly assigned to be instrumented with either a pedicle screw and the sleeve or a pedicle screw only. Following instrumentation, the screws were exposed to tensile load at 5 mm/min until failure. The failure force, failure deformation, and area under the force–deformation curve were determined and compared between screw conditions. There were no significant differences between the screws and sleeve, and the screw only conditions for the failure force (p = 0.24), failure displacement (p = 0.10), and area under the curve (p = 0.38). While the novel screw sleeve presented here performed as well as a screw without a sleeve, it was better than other screw augmentation devices reported previously. In addition, it is likely that this device would prove useful as an enhancement to revision.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".