Low-Density Pedicle Screw Constructs Are Associated with Lower Incidence of Proximal Junctional Failure in Adult Spinal Deformity Surgery
Bibliographic record
Abstract
STUDY DESIGN: Retrospective cohort study. OBJECTIVE: Determine whether screws per level and rod material/diameter are associated with incidence of proximal junctional kyphosis (PJF). SUMMARY OF BACKGROUND DATA: PJF is a common and particularly adverse complication of adult spinal deformity (ASD) surgery. There is evidence that the rigidity of posterior spinal constructs may impact risk of PJF. METHODS: Patients with ASD and 2-year minimum follow-up were included. Only patients undergoing primary fusion of more than or equal to five levels with lower instrumented vertebrae (LIV) at the sacro-pelvis were included. Screws per level fused was analyzed with a cutoff of 1.8 (determined by receiver operating characteristic curve (ROC) analysis). Multivariable logistic regression was utilized, controlling for age, body mass index (BMI), 6-week postoperative change from baseline in lumbar lordosis, number of posterior levels fused, sex, Charlson comorbidity index, approach, osteotomy, upper instrumented vertebra (UIV), osteoporosis, preoperative TPA, and pedicle screw at the UIV (as opposed to hook, wire, etc.). RESULTS: In total, 504 patients were included. PJF occurred in 12.7%. The mean screws per level was 1.7, and 56.8% of patients had less than 1.8 screws per level. No differences were observed between low versus high screw density groups for T1-pelvic angle or magnitude of lordosis correction (both P > 0.15). PJF occurred in 17.0% versus 9.4% of patients with more than or equal to 1.8 versus less than 1.8 screws per level, respectively (P < 0.05). In multivariable analysis, patients with less than 1.8 screws per level exhibited lower odds of PJF (odds ratio (OR) 0.48, P < 0.05), and a continuous variable for screw density was significantly associated with PJF (OR 3.87 per 0.5 screws per level, P < 0.05). Rod material and diameter were not significantly associated with PJF (both P > 0.1). CONCLUSION: Among ASD patients undergoing long-segment primary fusion to the pelvis, the risk of PJF was lower among patients with less than 1.8 screws per level. This finding may be related to construct rigidity. Residual confounding by other patient and surgeon-specific characteristics may exist. Further biomechanical and clinical studies exploring this relationship are warranted.Level of Evidence: 3.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".