Persistent Lower Extremity Compensation for Sagittal Imbalance After Surgical Correction of Complex Adult Spinal Deformity: A Radiographic Analysis of Early Impact
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Achieving spinopelvic realignment during adult spinal deformity (ASD) surgery does not always produce ideal outcomes. Little is known whether compensation in lower extremities (LEs) plays a role in this disassociation. The objective is to analyze lower extremity compensation after complex ASD surgery, its effect on outcomes, and whether correction can alleviate these mechanisms. METHODS: We included patients with complex ASD with 6-week data. LE parameters were as follows: sacrofemoral angle, knee flexion angle, and ankle flexion angle. Each parameter was ranked, and upper tertile was deemed compensation. Patients compensating and not compensating postoperatively were propensity score matched for body mass index, frailty, and T1 pelvic angle. Linear regression assessed correlation between LE parameters and baseline deformity, demographics, and surgical details. Multivariate analysis controlling for baseline deformity and history of total knee/hip arthroplasty evaluated outcomes. RESULTS: Two hundred and ten patients (age: 61.3 ± 14.1 years, body mass index: 27.4 ± 5.8 kg/m2, Charlson Comorbidity Index: 1.1 ± 1.6, 72% female, 22% previous total joint arthroplasty, 24% osteoporosis, levels fused: 13.1 ± 3.8) were included. At baseline, 59% were compensating in LE: 32% at hips, 39% knees, and 36% ankles. After correction, 61% were compensating at least one joint. Patients undercorrected postoperatively were less likely to relieve LE compensation (odds ratio: 0.2, P = .037). Patients compensating in LE were more often undercorrected in age-adjusted pelvic tilt, pelvic incidence, lumbar lordosis, and T1 pelvic angle and disproportioned in Global Alignment and Proportion (P < .05). Patients matched in sagittal age-adjusted score at 6 weeks but compensating in LE were more likely to develop proximal junctional kyphosis (odds ratio: 4.1, P = .009) and proximal junctional failure (8% vs 0%, P = .035) than those sagittal age-adjusted score-matched and not compensating in LE. CONCLUSION: Perioperative lower extremity compensation was a product of undercorrecting complex ASD. Even in age-adjusted realignment, compensation was associated with global undercorrection and junctional failure. Consideration of lower extremities during planning is vital to avoid adverse outcomes in perioperative course after complex ASD surgery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".