Biomechanical analysis of segmental lumbar lordosis and risk of cage subsidence with different cage heights and alternative placements in transforaminal lumbar interbody fusion
Bibliographic record
Abstract
Cage subsidence in transforaminal lumbar interbody fusion (TLIF) is one of the concerns. The objective was to numerically assess the resulting segmental lumbar lordosis (SLL) and stresses at the bone-cage interface as functions of cage height (8- vs. 10-mm) and cage placement (oblique asymmetric, vs. anterior symmetric) for normal and osteoporotic bone quality. A L4-L5 detailed finite element model of TLIF was subjected to the functional loadings of 10 Nm in the physiological planes after the application of a 400 N follower-load. The SLL was increased by 0.9° (11%) and 1.0° (13%), respectively in oblique asymmetric and anterior symmetric cage placement with 8-mm height; they were 1.4° (18%) and 1.7° (21%) for the 10-mm cage. The maximum stresses at the cage-bone interface, in normal bone model, were increased up to 16% and 41% with the 10-mm cage and asymmetric oblique placement, respectively, and they increased up to 16% and 43% in osteoporotic bone model. The greater cage resulted to a higher simulated SLL. Oblique asymmetric placement and the use of a greater cage may increase the risk of cage subsidence. Due to the lower mechanical strength of osteoporotic bone, the risk of cage subsidence should be higher.
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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".