Quantifying the Importance of Upper Cervical Extension Reserve in Adult Cervical Deformity Surgery and Its Impact on Baseline Presentation and Outcomes
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The concept of upper cervical ( C0-C2) extension reserve (ER) capacity, ER relaxation, and their impact on outcomes following surgical correction of adult cervical deformity (ACD) has not been extensively studied. We aimed to evaluate the impact of upper cervical ER on postoperative disability and outcomes. METHODS: Patients with ACD, from a retrospective cohort study of a prospectively collected multicenter database, undergoing subaxial cervical fusion with 2-year (2Y) follow-up data were included. ER was defined as: ΔC0-C2 sagittal Cobb angle between neutral and extension. Relaxation of ER was defined as the ER mean in those that met all ideal thresholds in radiographic parameters for Passias et al CD modifiers. We used multivariable logistic regression to adjust for confounding, with conditional inference tree approaches used to determine thresholds that affect postoperative ER resolution on patient-reported outcomes. RESULTS: A total of 108 patients with ACD met inclusion. Preoperative C0-C2 ER was 8.7° ± 9.0°, and at last follow-up was 10.3° ± 11.1°. Preoperatively 29% of the cohort had adequate ER, whereas 60% had improved ER postoperatively, with 50% achieving adequate ER by 2Y. Lower ER correlated with greater CD ( P < .05). Preoperatively, greater ER had lower Neck Disability Index ( P < .001). Controlled analysis found improved ER to have a greater likelihood of achieving Neck Disability Index minimum clinically important difference (odds ratio 6.94, [1.378-34.961], P = .019). In those with inadequate ER at baseline, the preoperative C2-C7 of < -18° and T1 slope-cervical Lordosis mismatch of >59° for T1 slope-cervical Lordosis mismatch was predictive of ER resolution. In those with preoperative C2-C7 >-18°, a T1PA of >13° was predictive of postoperative return of ER (all P < .05). Surgical correction of C2-C7 by > 16° from baseline was found to be predictive of ER return. CONCLUSION: Increased preoperative use of the C0-C2 ER in CD was associated with worse baseline regional and global alignment and adversely affected health-related measures. Most of the patients had ER relaxation postoperatively. In those who didn't, however, there was a decreased likelihood of achieving satisfactory outcomes.
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 | 0.002 | 0.007 |
| 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 | 0.001 |
| 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".