Determining the minimal clinically important differences in activity, fatigue, and sleep quality in patients with rheumatoid arthritis.
Bibliographic record
Abstract
OBJECTIVE: To determine the minimal clinically important differences (MCID) in the patient-reported outcomes of activity (0-30, number of days of limitation), fatigue (0 = none, 100 = complete), and sleep quality (0 = no problems, 100 = worst case) for patients with rheumatoid arthritis (RA). METHODS: Two randomized controlled trials comparing abatacept to placebo in RA patients were considered: ATTAIN (n = 391) and AIM (n = 652). An internal anchor-based approach was used to derive the MCID using the Health Assessment Questionnaire, patient global assessment, and pain as anchors. Minimal important change in activity, fatigue, and sleep were determined by estimating mean changes in these outcomes in patients showing change in a narrow range about the MCID of the internal anchor. Correlation analysis was used to determine the consistency of the changes in the outcomes and anchors, and a Delphi process was used to determine the final MCID values. RESULTS: For the 2 trials, consistent patterns of change for activity, fatigue, and sleep and the internal anchors were found with correlations in the range of 0.5, 0.7, and 0.4, respectively. The mean changes for activity, fatigue, and sleep in a narrow range about the MCID of the 3 internal anchors corresponding to the 2 trials were: 3.4 to 4.3 for activity; 6.7 to 17.0 for fatigue; and 4.1 to 7.3 for sleep. Following the Delphi process the MCID determined were 4 for activity, 10 for fatigue, and 6 for sleep. CONCLUSION: These MCID for activity limitation, fatigue, and sleep problems can be used in designing clinical trials and providing benchmarks in assessing patient improvement.
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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 | 0.028 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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".