Patients with Rheumatoid Arthritis Acquire Sustainable Skills for Home Monitoring: A Prospective Dual-country Cohort Study (ELECTOR Clinical Trial I)
Bibliographic record
Abstract
OBJECTIVE: In an eHealth setting, to investigate intra- and interrater reliability and agreement of joint assessments and Disease Activity Score using C-reactive protein (DAS28-CRP) in patients with rheumatoid arthritis (RA) and test the effect of repeated joint assessment training. METHODS: Patients with DAS28-CRP ≤ 5.1 were included in a prospective cohort study (clinicaltrials.gov: NCT02317939). Intrarater reliability and agreement of patient-performed joint counts were assessed through completion of 5 joint assessments over a 2-month period. All patients received training on joint assessment at baseline; only half of the patients received repeated training. A subset of patients was included in an appraisal of interrater reliability and agreement comparing joint assessments completed by patients, healthcare professionals (HCP), and ultrasonography. Cohen's κ coefficients and intraclass correlation coefficients (ICC) were used for quantifying of reliability of joint assessments and DAS28-CRP. Agreement was assessed using Bland-Altman plots. RESULTS: Intrarater reliability was excellent with ICC of 0.87 (95% CI 0.83-0.90) and minimal detectable change of 1.13. ICC for interrater reliability ranged between 0.69 and 0.90 (good to excellent). Patients tended to rate DAS28-CRP slightly higher than HCP. In patients receiving repeated training, a mean difference in DAS28-CRP of -0.08 was observed (limits of agreements of -1.06 and 0.90). After 2 months, reliability between patients and HCP was similar between groups receiving single or repeated training. CONCLUSION: Patient-performed assessments of joints and DAS28-CRP in an eHealth home-monitoring solution were reliable and comparable with HCP. Patients can acquire the necessary skills to conduct a correct joint assessment after initial and thorough training. [clinicaltrials.gov (NCT02317939)].
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".