Patient Acceptable Symptom State in Knee Osteoarthritis Patients Succeeds Across Different Patient-reported Outcome Measures Assessing Physical Function, But Fails Across Other Dimensions and Rheumatic Diseases
Bibliographic record
Abstract
OBJECTIVE: The aims of this study are (1) to establish the Patient Acceptable Symptom State (PASS) cutoff values of different patient-reported outcome measures (PROM) assessing physical function in patients with knee osteoarthritis (OA), and (2) to assess the influence of sex, age, duration of symptoms, and presence of depressive feelings on being in PASS. METHODS: Patients fulfilling the clinical American College of Rheumatology knee OA criteria received standardized nonsurgical treatment and completed different questionnaires at baseline and 3 months assessing physical function: Knee Injury and Osteoarthritis Outcome Score, Lequesne Algofunctional Index, Lower Extremity Functional Scale, numerical rating scale, and the physical function subscale of the Western Ontario and McMaster Universities Osteoarthritis Index. PASS values were defined as the 75th percentile of the score of questionnaires for those patients who consider their state acceptable. RESULTS: (SD 5). Standardized PASS values (95% CI) for different questionnaires for physical function varied between 48 (44-54) and 54 (50-56). Female patients and patients feeling depressed were found to have a lower probability to be in PASS for physical function, with OR (95% CI) varying from 0.45 (0.23-0.91) to 0.50 (0.26-0.97) and from 0.27 (0.14-0.55) to 0.38 (0.19-0.77), respectively. CONCLUSION: PASS cutoff values for physical function are robust across different PROM in patients with knee OA. Our results indicate that PASS values are not consistent across dimensions and rheumatic diseases, and that the use of a generic PASS value for patients with OA or even patients with other rheumatic diseases might not be justifiable.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".