PORTRESS – the PORTuguese Reuma.pt registry for Sjögren’S disease
Bibliographic record
Abstract
Aims: Sjgren' s disease (SjD) is a complex disease with a wide variety of manifestations and outcomes.We recently created PORTRESS, the Portuguese SjD registry within Reuma.pt.We aim to describe this registry and characterize our national cohort.Methods: We included patients with a clinical diagnosis of SjD, registered in PORTRESS up to November 2023.Demographic, clinical, treatment, and patient-reported outcomes (PROs) data were collected.Variables were compared according to parametric or non-parametric tests, as applicable.Results: A total of 1375 patients were included.Patients fulfilled AECG 2002 or ACR/EULAR 2016 classification criteria in 62% and 57% of cases, respectively, although more than half didn't have a complete assessment of all items.Of note, the vast majority (93%) had both SjD manifestations and a positive anti-Ro and/or minor salivary gland biopsy.Most patients (88%) exhibited at least one active ESSDAI domain during the course of their disease.Hydroxychloroquine and corticosteroids were used in 52% and 30% of patients, while other immunosuppressants and pilocarpine in 12% and 18% of cases, respectively.The mean ESSDAI at inclusion was 3.04.4(range 0-42), and, at the last follow-up, 2.13.7 (0-31), corresponding to a significant decrease.Dryness, pain and fatigue PROs were scored high, with a significant increase from baseline to follow-up.Conclusion: PORTRESS is a web-based SjD registry facilitating efficient nationwide data storage.It enables research, trial recruitment, and a comprehensive longitudinal view of patients' evolution.Although systemic activity improved over follow-up, symptom burden worsened when compared to baseline, underlining a major unmet need in SjD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".