The Influence of Preoperative Back Pain on the Outcome of Lumbar Decompression Surgery
Bibliographic record
Abstract
STUDY DESIGN: Prospective study with 12-month follow-up. OBJECTIVE: To examine how the relative severity of low back pain (LBP) to leg/buttock pain (LP) influences the outcome of decompression surgery for spinal stenosis. SUMMARY OF BACKGROUND DATA: Decompression surgery is a common treatment for lumbar spinal canal stenosis, with generally good outcome. However, concomitant LBP at presentation can make it difficult to decide whether decompression alone will result in a good overall outcome. METHODS: The Spine Society of Europe Spine Tango system was used to acquire the data from 221 patients. Inclusion criteria were lumbar degenerative spinal stenosis, first-time surgery, maximum 3 affected levels, and decompression as the only procedure. Before and 12 months after surgery, patients completed the multidimensional Core Outcome Measures Index (COMI; includes 0-10 LP and LBP scales); at 12 months, global outcome was rated on a Likert-scale and dichotomized into "good" and "poor" groups. RESULTS: There was a low but significant positive correlation between baseline LP-minus-LBP scores and both improvement in the multidimensional COMI score after 12 months (r = 0.21, P = 0.003) and the score on the 12-month global outcome scale (r = 0.19, P = 0.007). In the good outcome group, mean baseline LP was 2.3 (+/-3.7) points higher than LBP; in the poor group, the corresponding value was 0.8 (+/-3.4) (P = 0.01 between groups). In multivariate regression analyses (controlling for age, gender, comorbidity), baseline LBP intensity was the most significant predictor of the 12-month COMI score, and preoperative LP-minus-LBP score of the global outcome (each P < 0.05). CONCLUSION: Overall, greater back pain relative to LP at baseline was associated with a significantly worse outcome after decompression. This finding seems intuitive, but has rarely been quantified in the many predictor studies conducted to date. Consideration of relative LBP and LP scores may assist in clinical decision-making and in establishing realistic patient expectations.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".