Preoperative Disc Angle is an Important Predictor of Segmental Lordosis After Degenerative Spondylolisthesis Fusion
Bibliographic record
Abstract
Study Design Retrospective Cohort Study Objectives To determine the effect of interbody cages inserted via posterior approach on segmental lordosis in the setting of preoperative lordotic vs kyphotic discs in patients with lumbar degenerative spondylolisthesis (LDS). Methods Retrospective analysis of prospectively collected data on assessment and management of LDS patients from 2 contributing centres. Patients were analyzed preoperatively and at 12-month follow-up with standing lumbar radiographs. Index level segmental lumbar lordosis (SLL), disc angle and global lumbar lordosis was measured. Patients were stratified into 4 groups based on index level disc angle and procedure: preoperative lordotic posterolateral fusion (group L-PLF); preoperative kyphotic PLF (group K-PLF); preoperative lordotic interbody fusion (IF) (group L-IF); preoperative kyphotic IF (group K-IF). Results A total of 100/111 (90%) patients completed follow-up with 40 in group L-IF and 48 in group K-IF. There were 18 patients in group L-PLF and 5 in group K-PLF. Among patients with preoperatively lordotic disc angles who had a worsening of SLL, group L-IF had worse SLL than group L-PLF patients, with differences persisting at one-year (mean difference 2.30, 95% CI, .3, 4.3, P = .029). Patients in group K-IF achieved improvement in SLL at one-year more frequently than group L-IF (67% vs 44%, P = .046), with similar mean improvement magnitude between groups L-IF and K-IF (−1.1, 95% CI, −3.7, 1.6, P = .415). Conclusion Segmental lordosis worsening was greater with preoperative index lordotic disc angles when an interbody cage was used. Patients who have a kyphotic disc preoperatively gain more lordosis with interbody cage use.
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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 | 0.004 |
| 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 | 0.000 | 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".