Single-joint Outcome Measures: Preliminary Validation of Patient-reported Outcomes and Physical Examination
Bibliographic record
Abstract
OBJECTIVE: To assess the validity, responsiveness, and reliability of single-joint outcome measures for determining target joint (TJ) response in patients with inflammatory arthritis. METHODS: Patient-reported outcomes (PRO), consisting of responses to single questions about TJ global status on a 100-mm visual analog scale (VAS; TJ global score), function on a 100-mm VAS (TJ function score), and pain on a 5-point Likert scale (TJ pain score) were piloted in 66 inflammatory arthritis subjects in a phase 1/2 clinical study of an intraarticular gene transfer agent and compared to physical examination measures (TJ swelling, TJ tenderness) and validated function questionnaires (Disabilities of the Arm, Shoulder and Hand scale, Rheumatoid Arthritis Outcome Score, and the Health Assessment Questionnaire). Construct validity was assessed by evaluating the correlation between the single-joint outcome measures and validated function questionnaires using Spearman's rank correlation. Responsiveness or sensitivity to change was assessed through calculating effect size and standardized response means (SRM). Reliability of physical examination measures was assessed by determining interobserver agreement. RESULTS: The single-joint PRO were highly correlated with each other and correlated well with validated functional measures. The TJ global score exhibited modest effect size and modest SRM that correlated well with the patient's assessment of response on a 100-mm VAS. Physical examination measures exhibited high interrater reliability, but correlated less well with validated functional measures and the patient's assessment of response. CONCLUSION: Single-joint PRO, particularly the TJ global score, are simple to administer and demonstrate construct validity and responsiveness in patients with inflammatory arthritis. (ClinicalTrials.gov identifier NCT00126724).
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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 | 0.042 |
| 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 | 0.001 |
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".