Early Compensatory Segmental Angle Changes at L3-L4 and L4-L5 After a L5-S1 Interbody Fusion for a Grade 1 Spondylolisthesis
Bibliographic record
Abstract
STUDY DESIGN: The retrospective study included patients who underwent an L5-S1 anterior (ALIF) or transforaminal (TLIF) lumbar interbody fusion with posterior pedicle screw instrumentation for grade 1 spondylolisthesis from 2018 to 2022. OBJECTIVE: To compare early reciprocal changes at the L3-L4 and L4-L5 adjacent levels 6 months after ALIF or TLIF at L5-S1. BACKGROUND: Degenerative and chronic isthmic spondylolistheses often result in decreased segmental lordosis (SL) at L5-S1. This can lead to lordotic overcompensation at adjacent levels to maintain spinopelvic balance. However, the fate of adjacent angles after interbody fusion is not well understood. PATIENTS AND METHODS: Preoperative and 6-month postoperative measurements of SL (L3-L4, L4-L5, and L5-S1), lumbar lordosis, and pelvic incidence (PI) were obtained from sagittal standing radiographs. Preliminary t tests were performed for descriptive purposes, and multiple regression was used for hypothesis testing. RESULTS: Ninety-eight patients met the inclusion criteria (50 ALIF and 48 TLIF). A greater amount of lordosis achieved at L5-S1 was significantly associated with a greater reduction of SL at L4-L5 ( r = -0.65, P < 0.001) or L3-L4 ( r = -0.46, P < 0.001). A greater preoperative PI was associated with a greater reduction of SL at L4-L5 ( r = -0.42, P < 0.001) and at L3-L4 ( r = -0.44, P < 0.001). CONCLUSION: At 6 months after a lumbar interbody fusion at L5-S1, greater compensatory changes with lordosis reduction are observed at the supra-adjacent L4-L5 and L3-L4 levels in patients achieving greater L5-S1 SL. In addition, preoperative PI played a role in influencing lordotic correction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".