Physical Predictors of Favorable Postoperative Outcomes in Patients Undergoing Laminectomy or Laminotomy for Central Lumbar Spinal Stenosis: Secondary Analysis of a Randomized Controlled Trial
Bibliographic record
Abstract
Study Design: Secondary analysis of a randomized controlled trial. Objective: To identify preoperative physical variables associated with favorable postoperative outcome in individuals undergoing laminectomy or laminotomy for degenerative central lumbar spinal stenosis. Summary of Background Data: Clinical or condition specific variables have most commonly been studied as predictors of postoperative outcome in lumbar spinal stenosis. If associated to favorable postoperative outcome, modifiable physical variables would inform prehabilitation interventions for patients with degenerative central lumbar spinal stenosis. Methods: Patients awaiting surgery for central lumbar spinal stenosis were recruited to participate in a randomized controlled trial. Following baseline data collection of demographics, clinical portrait and physical testing, participants were randomized to either 6-week active prehabilitation program or hospital standard care. Complete baseline and postoperative data were obtained from 58 participants which were included in the present analysis. Favorable postoperative outcome was determined based on two outcome measures. Favorable outcome was defined as a decrease of ≥30% on the Numerical Rating Scale for leg pain intensity and a decrease of ≥30% on the Oswestry Disability Index for low back disability. Baseline physical variables were used to conduct binary logistic regression. Results: Sixty percent of participants were determined as having a favorable postoperative outcome. None of the included physical variables were found to be predictors of a favorable postoperative outcome based on leg pain intensity and low back pain-associated disability [trunk flexors muscle strength (OR = 0.73; 95%CI (0.02-27.12)] lumbar extensors muscle endurance [OR= 1.09; 95%CI (0.95-1.24)] total ambulation time [OR = 1.00 95%CI (0.99-1.01)] lumbar active range of motion in extension [OR = 1.08; 95%CI (0.95-1.23)] and knee extensors muscle strength [OR=1.02; 95%CI (0.98-1.06)]. Conclusion: Results show that none of the investigated variables, all related to low back and lower limbs physical capacity, were predictors of postoperative recovery. Further testing in larger cohort is needed to assess the full potential of physical outcome measures as predictors of postoperative recovery.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".