Meaningful changes in physical function and pain in patients with knee osteoarthritis
Bibliographic record
Abstract
Abstract Background This study aims to establish meaningful within-person change (MWPC) thresholds for the Total Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC®), its Physical Function (PF) subscale, and the Visual Analog Scale (VAS) for Pain, in patients with knee osteoarthritis (OA). A secondary objective is to evaluate the effectiveness of a single injection of autologous culture-expanded adipose tissue-derived mesenchymal stem cells (ADMSCs) using these thresholds. Methodology The study included 252 patients with knee OA enrolled in a clinical trial. An anchor-based predictive modeling approach, using KOOS-12, SF-36, and IKDC scores with literature-based cut-offs, was applied to determine MWPC thresholds for WOMAC and VAS Pain. MWPC thresholds were derived from both the ADMSCs injection and Control (autoserum) groups at 3- and 6-month follow-ups. Treatment effectiveness was assessed by comparing MWPC range with between-group differences and within-person changes. Results MWPC thresholds were identified as follows: 5–17 points for WOMAC Total, 4–12 points for WOMAC PF, and 8–14 points for VAS Pain (all on 0–100 scales). The adjusted differences between the ADMSCs injection and Control (autoserum) groups of all three measures (3 months: WOMAC Total 5.9, WOMAC Function 4.2, VAS Pain 8.6; 6 months: WOMAC Total 9.3, WOMAC Function 6.5, VAS Pain 11.7) were within each corresponding MWPC threshold range. Conclusions The proposed MWPC thresholds could be beneficial for healthcare professionals as a tool to identify meaningful change in physical function and pain in response to treatment and evaluate the meaningfulness of treatment benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".