Interbody Device Shape and Size Are Important to Strengthen the Vertebra–Implant Interface
Bibliographic record
Abstract
STUDY DESIGN: An in vitro cadaveric study to compare compressive failure load, strength, and stiffness of the implant-vertebra interface. OBJECTIVES: To determine the effect of cage shape (kidney, cloverleaf, or oval) and cage surface area on endplate failure strength and secondly to determine the extent and pattern of trabecular failure adjacent to an interbody device. SUMMARY OF BACKGROUND DATA: Recent studies indicate that the posterolateral and peripheral regions of the endplate are stronger than the central. Current implants are not designed to take advantage of these stronger regions of the endplate. The zone of trabecular failure that results from interbody device subsidence has not been reported extensively in the literature. METHODS: Uniaxial compression testing with unrestricted rotation was carried out on the superior endplates of 48 thoracolumbar (T9-L2) vertebrae with 1 of 3 shaped indentors covering 20% or 40% of the endplate area. Failure load, failure strength, and stiffness were compared. Quantitative computed tomography scans were carried out before and following indentation tests to identify areas of trabecular densification that indicate localized failure. RESULTS: The cloverleaf-shaped indentors resulted in significantly higher (P < 0.001) failure loads (by >45%), strength (>49%), and construct stiffness (>35%) for both the 20% and 40% cross-sectional area sizes. Trabecular bone failure occurred in a semielliptical zone underlying the interbody devices, leaving the endplate and underlying cancellous bone intact. CONCLUSIONS: The cloverleaf-shaped indentor displayed an improved strength and stiffness profile when compared to oval or kidney-shaped indentors of similar surface areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".