Are We Getting Better at Achieving Optimal Lumbar Segmental Sagittal Alignment in Complex Adult Spine Deformity Surgery?
Bibliographic record
Abstract
STUDY DESIGN: Retrospective multicenter study. OBJECTIVE: To investigate how advances in spine realignment have impacted lumbar segmental alignment. SUMMARY OF BACKGROUND DATA: The understanding of spine alignment and adult spinal deformity (ASD) management continues to advance. It remains unknown how these advances have influenced lumbar segmental alignment changes in the setting of surgical correction. METHODS: Patients undergoing primary thoracolumbar fusion for ASD were stratified based on enrolment in two distinct multicenter registries; forming an 'Early' (2008-2017) and a 'Late cohort' (2018-present). Patients were further stratified based on pelvic incidence (PI) and Roussouly type. Segmental alignment was determined based on published values of asymptomatic individuals. Pelvic incidence-based alignment and Roussouly-based alignment were determined in alignment with previously published normative values. Means comparisons tests and multivariate analyses compared segmental and regional parameters between groups. RESULTS: One thousand two hundred forty patients included (622 EARLY, 618 LATE). The mean age was 61.4±14.5 years, body mass index (BMI) was 28.0±5.8 kg/m 2 , and Charlson comorbidity index (CCI) was 1.55±1.70. 70.2% of patients were female sex. LATE consistently displayed better L5 to S1 alignment across all PI and Roussouly types ( P =0.001). However, EARLY demonstrated better L4 to 5 alignment ( P =0.001). Improved alignment in L5 to S1, L4 to 5, and L3 to 4 was associated with achieving minimum clinically important difference in ODI scores and decreased risk of mechanical complications. Both cohorts demonstrated low rates of matching L4 to S1 regional and overall lumbar lordosis L1 to S1 alignment, with no differences between both groups. By lordosis distribution index, both groups had predominantly hyperlordotic maldistribution postop, but LATE had more 'Aligned' patients (15.9 vs. 11%, P <0.001). CONCLUSIONS: Over the past 15 years, surgeons seem to be better at restoring ideal lumbar segmental sagittal alignment in ASD patients. However, idealized correction does not seem to be uniform across all lumbar segments, representing an opportunity for further improvement. LEVEL OF EVIDENCE: Level III.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".