Clinical outcomes and proximal junctional failure in adult spinal deformity patients corrected to normative alignment versus functional alignment
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to explore the rate of proximal junctional failure (PJF) and functional outcomes of normative alignment goals compared with alignment targets based on age-appropriate physical function. METHODS: Baseline relationships between age, pelvic incidence (PI), and a component of the T1 pelvic angle (TPA) within the fusion were analyzed in adult spinal deformity (ASD) patients and compared with those of asymptomatic patients. Linear regression modeling was used to determine alignment based on PI and age in asymptomatic patients (normative alignment), and in ASD patients, alignment corresponding to age-appropriate functional status (functional alignment). A cohort of 288 ASD patients was split into two groups based on whether the patient was closer to their normative or functional alignment goal at their 6-week postoperative radiographic follow-up. The rates of proximal junctional kyphosis (PJK) and PJF were determined for each cohort. RESULTS: In the 288 ASD patients included in this pre- to postoperative analysis, there was no difference in baseline alignment or health-related quality of life (HRQOL) between the normative alignment and functional alignment groups. At 6 weeks, patients with normative alignment had a smaller TPA (4.45° vs 14.1°) and PI minus lumbar lordosis (-7.24° vs 7.4°) (both p < 0.0001) and higher PJK (40% vs 27.2%, p = 0.03) and PJF (17% vs 6.8%, p = 0.008) rates than patients with functional alignment. CONCLUSIONS: Correction in ASD patients to normative alignment resulted in higher rates of PJK and PJF without improvements in HRQOL. Correction in ASD patients to functional alignment that mirrors the physical function of their age-matched asymptomatic peers is recommended.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".