The scleroderma patient-centered intervention network cohort: Baseline clinical features and comparison with other large scleroderma cohorts
Bibliographic record
Abstract
Objectives. The Scleroderma Patient-centered Intervention Network (SPIN) Cohort is a web-based cohort designed to collect patient-reported outcomes at regular intervals as a framework for conducting trials of psychosocial, educational, self-management and rehabilitation interventions for patients with SSc. The aim of this study was to present baseline demographic, medical and patient-reported outcome data of the SPIN Cohort and to compare it with other large SSc cohorts. Methods. Descriptive statistics were used to summarize SPIN Cohort characteristics; these were compared with published data of the European Scleroderma Trials and Research (EUSTAR) and Canadian Scleroderma Research Group (CSRG) cohorts. Results. Demographic, organ involvement and antibody profile data for SPIN (N = 1125) were generally comparable with that of the EUSTAR (N = 7319) and CSRG (N = 1390) cohorts. There was a high proportion of women and White patients in all cohorts, though relative proportions differed. Scl70 antibody frequency was highest in EUSTAR, somewhat lower in SPIN, and lowest in CSRG, consistent with the higher proportion of interstitial lung disease among dcSSc patients in SPIN compared with in CSRG (48.5 vs 40.3%). RNA polymerase III antibody frequency was highest in SPIN and remarkably lower in EUSTAR (21.1 vs 2.4%), in line with the higher prevalence of SSc renal crisis (4.5 vs 2.1%) in SPIN. Conclusion. Although there are some differences, the SPIN Cohort is broadly comparable with other large prevalent SSc cohorts, increasing confidence that insights gained from the SPIN Cohort should be generalizable, although it should be noted that all three cohorts include primarily White participants.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".