Getting Better or Getting Well? The Patient Acceptable Symptom State (PASS) Better Predicts Patient’s Satisfaction than the Decrease of Pain, in Knee Osteoarthritis Subjects Treated with Viscosupplementation
Bibliographic record
Abstract
Background In the management of knee osteoarthritis (OA), patient-reported-outcomes (PROs) are being developed for relevant assessment of pain. The patient acceptable symptom state (PASS) is a relevant cutoff, which allows classifying patients as being in "an acceptable state" or not. Viscosupplementation is a therapeutic modality widely used in patients with knee OA that many patients are satisfied with despite meta-analyses give conflicting results. Objectives To compare, 6 months after knee viscosupplementation, the percentage of patients who reached the PASS threshold (PASS +) with that obtained from other PROs. Methods Data of 53 consecutive patients treated with viscosupplementation (HANOX-M-XL) and followed using a standardized procedure, were analyzed at baseline and month 6. The PROs were Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and function, patient's global assessment of pain (PGAP), patient's self-assessment of satisfaction, PASS for WOMAC pain and PGAP. Results At baseline, WOMAC pain and PGAP (range 0-10) were 4.6 (1.1) and 6.0 (1.1). At month 6, they were 1.9 (1.2) and 3.1 (5) ( P < 0.0001). At 6 months, 83% of patients were "PASS + pain," 100% "PASS + function," 79% "PASS + PGAP," 79% were satisfied, and 73.6% experienced a ≥50% decrease in WOMAC pain. Among "PASS + pain" and "PASS + PGAP" subjects, 90% and 83.3% were satisfied with the treatment, respectively. Conclusion In daily practice, clinical response to viscosupplementation slightly varies according to PROs. "PASS + PGAP" was the most related to patient satisfaction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".