Validation of the OMERACT Magnetic Resonance Imaging Joint Space Narrowing Score for the Wrist in a Multireader Longitudinal Trial
Bibliographic record
Abstract
OBJECTIVE: To assess the intrareader and interreader agreement and sensitivity to change of the Outcome Measures in Rheumatology (OMERACT) Rheumatoid Arthritis Magnetic Resonance Imaging Joint Space Narrowing (RAMRIS-JSN) score in the rheumatoid arthritis (RA) wrist in a longitudinal multireader exercise. METHODS: Coronal T1-weighted MR image sets of 1 wrist from 20 patients with early RA were assessed twice for JSN at 17 sites at baseline and after 36 or 60 months by 4 readers blinded to patient data but not time order. The joints were scored 0-4 according to the OMERACT RAMRIS-JSN score. Intraclass correlation coefficients (ICC), smallest detectable change (SDC), percentage exact/close agreement (PEA/PCA), and standardized response mean (SRM) were calculated. RESULTS: Median baseline and change score was 10.3 and 1.9, respectively. Intrareader ICC for baseline and change scores was good (≥ 0.50) to very good (≥ 0.80) for all and 3 of 4 readers, respectively. Interreader ICC was very good for change (0.93), while poor for baseline score if all 4 readers were included (0.36), but very good if 1 reader was excluded (0.87). Intrareader and interreader SDC was low (2.34-3.18), except for the intrareader SDC for 1 reader (6.75). The mean PEA/PCA was high for baseline and change scores both within and between the readers (51.5-99.2), except for interreader baseline PEA (14.4). SRM was moderate for all readers (0.55-0.77). CONCLUSION: The OMERACT RAMRIS-JSN score showed high overall intrareader and interreader reliability, and moderate sensitivity to change, supporting inclusion of the measure as part of the OMERACT RAMRIS system.
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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 | 0.027 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".