Evaluation of a Force‐Control Experimental Method to Perform Unconstrained Load‐Induced Subsidence Testing of Spinal Interbody Implants
Bibliographic record
Abstract
Introduction: Intervertebral body fusion devices ("interbody cages") used in spinal surgeries are susceptible to axial and/or rotational subsidence into the underlying vertebral bone. Experimental testing standards to examine implant subsidence, such as ASTM F2267, simplify the implant loading conditions and vertebral bone materials for ease of use and repeatability. Yet, the ability to assess clinically relevant risk of rotational subsidence with these methods is limited. Methods: The present work aimed to develop and evaluate a novel force-control (FC) test method for performing unconstrained load-induced implant subsidence into a heterogeneous material interface. The developed method was compared to the ASTM F2267 method, which uses a lubricated ball-and-socket joint, using the AMTI VIVO joint motion simulator to apply unconstrained loading up to 4 kN. Subsidence testing was performed on two different polyurethane (PU) foam densities (rigid 20 and 30 PCF) sandwiched together providing a heterogeneous boundary interface to induce implant rotation into the less dense foam. Results: < 0.05). Unconstrained axial compression up to 4 kN yielded, on average, 2.5 ± 0.4 mm of axial subsidence for ASTM-based setup compared to 4.8 ± 0.6 mm for the FC setup. The ASTM-based setup had an average implant rotation of 2.8° ± 0.5°, in contrast to the FC setup, with an average of 18.0° ± 0.9°. Additionally, the experimental FC results had good agreement with a computational finite element model of the same FC setup and PU foam materials. Conclusions: This new FC method for unconstrained load-induced subsidence testing demonstrates potential improvements in consideration for rotational implant subsidence and the associated clinical burden in spinal surgery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".