Prediction of walking ability following posterior decompression for lumbar spinal stenosis
Bibliographic record
Abstract
PURPOSE: Following surgery for lumbar spinal stenosis (LSS) up to 40% of people report persistent walking disability. This study aimed to identify pre-operative factors that are predictive of walking ability post-surgery for LSS. METHODS: An observational cohort study was conducted using data from the British Spine Registry (2017-2018) of adults (≥ 50 years) with LSS, who underwent ≤ 2 level posterior lumbar decompression. Patients receiving fixation or who had previous lumbar surgery were excluded. Walking ability was assessed by a single item on the Oswestry Disability Index and dichotomised into poor/good outcome. Multivariable regression models were performed. RESULTS: (OR 1.52, 95% CI 1.00, 2.30), severity of leg pain (OR 1.10, CI 95% 1.01, 1.21), disability (OR 1.01, 95% CI 1.01, 1.02) and quality of life (OR 0.72, 95% CI 0.56, 0.89). Pre-operative maximum walking distance (OR 1.10, 95% CI 1.05, 1.25) and higher education (OR 0.90, 95% CI 0.80, 0.96) were associated with reduced risk of poor walking ability at 12 months; p < 0.05. Depression, fear of movement and symptom duration were not associated with risk of poor outcome. CONCLUSION: Older age, obesity, greater pre-operative pain and disability and lower quality of life are associated with risk of poor walking ability post-operatively. Greater pre-operative walking and higher education are associated with reduced risk of poor walking ability post-operatively. Patients should be counselled on their risk of poor outcome and considered for rehabilitation so that walking and surgical outcomes may be optimised.
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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 | 0.000 | 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 | 0.001 |
| 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".