Identifying Possible Outcome Domains from Existing Outcome Measures to Inform an OMERACT Core Domain Set for Safety in Rheumatology Trials
Bibliographic record
Abstract
OBJECTIVE: The Outcome Measures in Rheumatology (OMERACT) Safety Working Group objective was to identify harm domains from existing outcome measurements in rheumatology. METHODS: Systematically searching the MEDLINE database on January 24, 2017, we identified full-text articles that could be used for harm outcomes in rheumatology. Domains/items from the identified instruments were described and the content synthesized to provide a preliminary framework for harm outcomes. RESULTS: From 435 possible references, 24 were read in full text and 9 were included: 7 measurement instruments were identified. Investigation of domains/items revealed considerable heterogeneity in the grouping and approach. CONCLUSION: The ideal way to assess harm aspects from the patients' perspective has not yet been ascertained.
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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 | 0.212 | 0.385 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.029 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".