Impact of Prior Cervical Fusion on Patients Undergoing Thoracolumbar Deformity Correction
Bibliographic record
Abstract
STUDY DESIGN: Retrospective analysis of prospectively collected data. OBJECTIVE: Evaluate the impact of prior cervical constructs on upper instrumented vertebrae (UIV) selection and postoperative outcomes among patients undergoing thoracolumbar deformity correction. BACKGROUND: Surgical planning for adult spinal deformity (ASD) patients involves consideration of spinal alignment and existing fusion constructs. METHODS: ASD patients with (ANTERIOR or POSTERIOR) and without (NONE) prior cervical fusion who underwent thoracolumbar fusion were included. Demographics, radiographic alignment, patient-reported outcome measures (PROMs), and complications were compared. Univariate and multivariate analyses were performed on POSTERIOR patients to identify parameters predictive of UIV choice and to evaluate postoperative outcomes impacted by UIV selection. RESULTS: Among 542 patients, with 446 NONE, 72 ANTERIOR, and 24 POSTERIOR patients, mean age was 64.4 years and 432 (80%) were female. Cervical fusion patients had worse preoperative cervical and lumbosacral deformity, and PROMs ( P <0.05). In the POSTERIOR cohort, preoperative LIV was frequently below the cervicothoracic junction (54%) and uncommonly (13%) connected to the thoracolumbar UIV. Multivariate analyses revealed that higher preoperative cervical SVA (coeff=-0.22, 95% CI=-0.43 to -0.01, P =0.038) and C2SPi (coeff=-0.72, 95% CI=-1.36 to -0.07, P =0.031), and lower preoperative thoracic kyphosis (coeff=0.14, 95% CI=0.01-0.28, P =0.040) and thoracolumbar lordosis (coeff=0.22, 95% CI=0.10-0.33, P =0.001) were predictive of cranial UIV. Two-year postoperatively, cervical patients continued to have worse cervical deformity and PROMs ( P <0.05) but had comparable postoperative complications. Choice of thoracolumbar UIV below or above T6, as well as the number of unfused levels between constructs, did not affect patient outcomes. CONCLUSIONS: Among patients who underwent thoracolumbar deformity correction, prior cervical fusion was associated with more severe spinopelvic deformity and PROMs preoperatively. The choice of thoracolumbar UIV was strongly predicted by their baseline cervical and thoracolumbar alignment. Despite their poor preoperative condition, these patients still experienced significant improvements in their thoracolumbar alignment and PROMs after surgery, irrespective of UIV selection. LEVEL OF EVIDENCE: IV.
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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 | 0.003 |
| 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 | 0.001 |
| 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".