Recording of non-musculoskeletal manifestations, comorbidities and safety outcomes in European spondyloarthritis registries: a survey
Bibliographic record
Abstract
Abstract Objectives Real-world evidence is needed to inform treatment strategies for patients with PsA and axial SpA (axSpA) who have non-musculoskeletal manifestations (NMMs), various risk factors and comorbidities. International collaboration is required to ensure statistical power and to enhance generalizability. The first step forward is identifying which data are currently being collected. Across 17 registries participating in the European Spondyloarthritis Research Collaboration (EuroSpA), we aimed to map recording practices for NMMs, comorbidities and safety outcomes in patients with PsA and axSpA. Methods Through a survey with 4,420 questionnaire items, we explored the recording practices of 58 pre-defined conditions (i.e. NMMs, comorbidities and safety outcomes) covering 10 disease areas. In all registries we mapped for each condition whether it was recorded, the recording procedure and the potential to identify it through linkage to other national registries. Results Conditions were generally recorded at entry into the registry and clinical follow-up visits using a pre-specified list or a coding system. Most registries recorded conditions within the following disease areas: NMMs (number of registries, n = 15–16), cardiovascular diseases (n = 10–14), gastrointestinal diseases (n = 12–13), infections (n = 10–13) and death (n = 14). Nordic countries had the potential for data linkage and generally had limited recording of conditions in their registry, while other countries had comprehensive recording practices. Conclusion A wide range of conditions were consistently recorded across the registries. The recording practices of many conditions and disease areas were comparable across the registries. Our findings support the potential for future collaborative research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".