Clinical Classification of Patients With Lumbar Spinal Stenosis Based on Their Leg Pain Syndrome
Bibliographic record
Abstract
In Brief Study Design. Prospective follow-up and retrospective review of 174 patients surgically treated for degenerative lumbar spinal stenosis. Objective. To examine whether the type of leg pain syndrome associated with lumbar spinal stenosis is correlated with outcome. Summary of Background Data. Although classifying patients based on their leg pain syndrome is useful in planning surgical decompression, there is no validated method of classification and its prognostic significance remains unknown. Methods. Based on the type of leg pain, the patients were classified into 2 groups: unilateral and bilateral. Improvement in functional status was evaluated using the Quebec Back Pain Disability Scale; the symptoms were rated on a visual analog scale and the change from baseline to 2-year evaluation was noted. Associations between score changes and baseline variables were examined using multivariate analysis. Results. The type of leg pain was independently associated with improvements in function and leg symptom scores but was not associated with improvement in the back pain score. After surgery, patients with unilateral leg pain had significantly greater improvements in function and leg symptoms than patients with bilateral leg pain. Conclusion. In patients undergoing surgery for degenerative lumbar spinal stenosis, the preoperative type of leg pain predicts function and leg symptom outcomes. A total of 174 patients who underwent surgery for lumbar spinal stenosis were classified based on the type of leg pain. The preoperative leg pain type predicted 2-year outcomes. After surgery, patients with unilateral leg pain had greater improvement in function and leg symptoms than patients with bilateral leg pain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 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".