Responsiveness of Outcome Measures in Nonsurgical Patients with Lumbar Spinal Stenosis
Bibliographic record
Abstract
STUDY DESIGN: Secondary analysis from a randomized controlled trial on nonsurgical interventions for patients with lumbar spinal stenosis (LSS). OBJECTIVE: The aim of this study was to assess the responsiveness of the Self-Paced Walking Test (SPWT), Swiss Spinal Stenosis Questionnaire (SSS), and Oswestry Disability Index (ODI) and determine their minimal clinically important differences (MCID) in nonsurgical LSS patients. SUMMARY OF BACKGROUND DATA: Limited information is available about the responsiveness of these tests in nonsurgical LSS population. METHODS: A total of 180 participants completed the SPWT, SSS, and ODI at baseline, 2, and 6 months. Responsiveness was assessed by distribution-based method, including effect size and standardized response mean, and anchor-based method, using the patient global index of change (PGIC) as the external anchor to distinguish responders and non-responders. Areas under the curve (AUC) were calculated along with MCIDs for "minimal" and "moderate improvement" subgroups. RESULTS: The following values represent 2- and 6-month analyses of each outcome measure, respectively. Standard effect sizes: 0.48 and 0.50 for SPWT, -0.42 and -0.36 for SSS, and -0.29 and -0.25 for ODI. Spearman correlation coefficients between PGIC and outcomes were: 0.44 and 0.39 for SPWT, -0.53 and -0.55 for SSS, and -0.46 and -0.54 for ODI. MCIDs for the "minimal improvement" subgroup were: 375.9 and 319.3 ms for SPWT, -5.3 and -5.8 points for SSS, and -9.3 and -10.8 points for ODI. AUCs was 0.68 to 0.76. MCIDs for the "moderate improvement" subgroup were: 344.2 and 538.2 m for SPWT, -5.5 and -7.5 points for SSS, and -9.1 and -13.6 points for ODI. AUCs ranged from 0.68 to 0.76. CONCLUSION: The SPWT, SSS, and ODI are responsive outcome measures to assess nonsurgical patients with LSS. This finding, along with the reported MCIDs, can help clinicians to monitor changes in their patients' walking and physical function over time and make clinical decisions. They also provide researchers with reference for future studies in LSS.Level of Evidence: 2.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".