Highest Achievable Outcomes for Patients Undergoing Cervical Deformity Corrective Surgery by Frailty
Bibliographic record
Abstract
BACKGROUND: Frailty is influential in determining operative outcomes, including complications, in patients with cervical deformity (CD). OBJECTIVE: To assess whether frailty status limits the highest achievable outcomes of patients with CD. METHODS: Adult patients with CD with 2-year (2Y) data included. Frailty stratification: not frail (NF) <0.2, frail (F) 0.2 to 0.4, and severely frail (SF) >0.4. Analysis of covariance established estimated marginal means based on age, invasiveness, and baseline deformity, for improvement, deterioration, or maintenance in Neck Disability Index (NDI), Modified Japanese Orthopaedic Association (mJOA), and Numerical Rating Scale Neck Pain. RESULTS: One hundred twenty-six patients with CD included 29 NF, 83 F, and 14 SF. The NF group had the highest rates of deterioration and lowest rates of improvement in cervical Sagittal Vertical Axis and horizontal gaze modifiers. Two-year improvements in NDI by frailty: NF: -11.2, F: -16.9, and SF: -14.6 ( P = .524). The top quartile of NF patients also had the lowest 1-year (1Y) NDI (7.0) compared with F (11.0) and SF (40.5). Between 1Y and 2Y, 7.9% of patients deteriorated in NDI, 71.1% maintained, and 21.1% improved. Between 1Y and 2Y, SF had the highest rate of improvement (42%), while NF had the highest rate of deterioration (18.5%). CONCLUSION: Although frail patients improved more often by 1Y, SF patients achieve most of their clinical improvement between 1 and 2Y. Frailty is associated with factors such as osteoporosis, poor alignment, neurological status, sarcopenia, and other medical comorbidities. Similarly, clinical outcomes can be affected by many factors (fusion status, number of pain generators within treated levels, integrity of soft tissues and bone, and deformity correction). Although accounting for such factors will ultimately determine whether frailty alone is an independent risk factor, these preliminary findings may suggest that frailty status affects the clinical outcomes and improvement after CD 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".