Clinical Composite Measures of Disease Activity for Diagnosis and Followup of Undifferentiated Peripheral Inflammatory Arthritis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To critically appraise the validity of activity indices used in the followup of patients with undifferentiated peripheral inflammatory arthritis (UPIA). METHODS: A systematic review was performed in Medline, Embase, the Cochrane Library, and abstracts presented at the 2007 and 2008 meetings of the American College of Rheumatology and European League Against Rheumatism. Selection criteria were: patients with UPIA, the assessment of instruments to evaluate disease activity, and assessment of validity of the instruments. Two reviewers screened titles and abstracts independently and collected data using ad hoc standard forms. RESULTS: The search yielded 179 articles and 834 abstracts, of which 4 articles and 1 abstract were included. We found no study that validated Disease Activity Score (DAS), Clinical Disease Activity Index (CDAI), or Simplified Disease Activity Index (SDAI). Included studies addressed validation of 4 questionnaires: WHO Disability Assessment Schedule (WHODAS), London Handicap Scale (LHS), Disease Repercussion Profile (DRP), and the Health Assessment Questionnaire (HAQ); and 3 indexes: RA Disease Activity Index (RADAI), McGill Range of Motion Index (McROMI), and NOAR Damaged Joint Count (NOAR-DJC). Questionnaires were self-administered and feasible; RADAI was the most feasible index. Internal consistency was studied in the questionnaires (Cronbach's α > 0.83). Responsiveness was tested in the DRP, LHS, and HAQ, but the approach to study sensitivity to change was poorly explained, with no clear intervention. Construct validity, examined by means of convergence with other instruments, was generally moderate, and slightly higher for the RADAI. CONCLUSION: No instrument of disease activity has been fully validated for use in UPIA. We found no direct evidence of what is the most useful index to follow up patients with UPIA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".