Measurement Properties of Outcome Instruments for Large-Vessel Vasculitis: A Systematic Literature Review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the measurement properties of outcome instruments used in large-vessel vasculitis (LVV). METHODS: MEDLINE, Embase, Cochrane, and Scopus databases were searched for studies published from inception to July 14, 2020, that addressed measurement properties of instruments used in giant cell arteritis (GCA) and Takayasu arteritis (TA). The measurement properties of the instruments identified were collected following the Outcome Measures in Rheumatology (OMERACT) and Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) frameworks. Instruments were grouped according to the following domains measured: disease activity/damage, organ function, and health-related quality of life (HRQOL)/health status. RESULTS: From 3534 articles identified, 13 met the predefined criteria. These studies addressed 12 instruments: 4 specific to TA, 2 designed for all types of systemic vasculitis, and 6 non-disease-specific instruments. No instruments specific to GCA were identified. Regarding TA, the Indian Takayasu Clinical Activity Score (ITAS) showed very good consistency, adequate reliability, but doubtful validity for disease activity. The Disease Extent Index-Takayasu (DEI-Tak) showed adequate construct validity but doubtful discriminating validity for disease activity/damage. Instruments, including the Vasculitis Damage Index and the Birmingham Vasculitis Activity Score, were poorly assessed for disease activity/damage. In total, 6 non-vasculitis-specific patient-reported outcome (PRO) instruments showed inadequate validity in GCA/TA. CONCLUSION: The measurement properties of 12 outcome instruments for LVV covering the OMERACT domains of disease activity/damage, organ function, and HRQOL were assessed. The ITAS and the DEI-Tak were the instruments with the most adequate measurement properties for disease activity/damage in TA. Disease activity/damage instruments specific to GCA, as well as validated PROs for both GCA and TA, are lacking.
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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 | 0.024 | 0.123 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".