Patient-Reported Outcome Measures for Patients with Upper Extremity Arthritis: Overview of Systematic Reviews
Bibliographic record
Abstract
Background: Arthritis leads to disabilities impacting patients' physical and mental health. Objective: To synthesize the evidence on measurement properties of the patient-reported outcome measures (PROMs) for people with upper extremity arthritis. Design: Overview of systematic reviews (SRs). Methods: We performed an electronic search of 6 databases to retrieve SRs looking at any measurement property related to PROMs for people with upper extremity arthritis. Two authors rated the risk of bias (ROB) of the included SRs using AMSTAR. We extracted data on measurement properties from each SR. Results: From 6 included SRs, 6 PROMs (Arthritis Impact Measurement Scale [AIMS], AIMS-2, AIMS-Short Form, Cedars-Sinai Health-Related Quality of Life for Rheumatoid Arthritis (CSHQ-RA), Revised CSHQ-RA, and Influence of Rheumatic Disease on General Health and Lifestyle) were evaluated in 2 or more SRs. The ROB of the included SRs ranged from moderate to high. Low- to moderate-quality evidence was found of good construct and criterion validity, acceptable content validity, and good responsiveness of the AIMS. We found low- to moderate-quality evidence of good internal consistency, test-retest reliability, and construct validity of the CSHQ-RA. Conclusion: We found a moderate to high ROB in the included SRs on the upper extremity PROMs for patients with arthritis. More evidence was specific to upper extremity arthritis in measures not in common use versus well-validated measures used in upper extremity conditions and recommended in current core sets. These factors suggest an urgent need for additional research to improve the scope and quality of evidence before recommendations can be made specific to patients with arthritis. Registration Number: on PROSPERO CRD 42019137491.
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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 | 0.023 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".