Biomechanical Risk Factors for Proximal Junctional Kyphosis
Bibliographic record
Abstract
STUDY DESIGN: Biomechanical analysis of proximal junctional kyphosis (PJK) through computer simulations and sensitivity analysis. OBJECTIVE: To gain biomechanical knowledge on the risk of PJK and find surgical solutions to reduce the risks. SUMMARY OF BACKGROUND DATA: PJK is a pathological kyphotic deformity adjacent to the instrumentation. Clinical studies have documented its risk factors, but still little is known on how it is correlated with various individual instrumentation variables. METHODS: Biomechanical spine models of 6 patients with adult scoliosis were developed, validated, and then used to perform 576 simulations, varying the proximal dissection procedure, the implant type at the upper instrumented vertebra, the sagittal rod curvature, and the proximal diameter of the proximal transition rods. Four biomechanical indices--the proximal junctional kyphotic angle, thoracic kyphosis, proximal flexion force, and proximal flexion moment--were assessed. RESULTS: The bilateral complete facetectomy, the posterior ligaments resection, and the combination of both increased the proximal junctional kyphotic angle (respectively, by 10%, 28% and 53%) and the proximal flexion force (4%, 12%, and 22%) and moment (16%, 44%, and 83%). Compared with pedicle screws at upper instrumented vertebra, proximal transverse process hooks reduced the 3 biomechanical indices by approximately 26%. The use of proximal transition rods with reduced proximal diameter from 5.5 mm to 4 mm decreased the proximal junctional kyphotic angle (by 6%) and the proximal flexion force (4%) and moment (8%). The increase of the sagittal rod curvature from 10° to 20°, 30°, and 40° increased the proximal junctional kyphotic angle (by 6%, 13%, and 19%) and the proximal flexion force (3%, 7%, and 10%) and moment (9%, 18%, and 27%). CONCLUSION: Preserving more posterior proximal intervertebral elements, the use of transition rods and transverse process hooks at upper instrumented vertebra, and reducing the global sagittal rod curvature each decreased the 4 biomechanical indices that may be involved in PJK. LEVEL OF EVIDENCE: N/A.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".