Patient perception of disease burden in diffuse cutaneous systemic sclerosis
Bibliographic record
Abstract
Purpose: Systemic sclerosis is a rare multi-organ autoimmune rheumatic disease, resulting in progressive fibrosis of the skin/internal organs. This study aimed to understand the impact of diffuse cutaneous systemic sclerosis symptoms and disease burden from the patient's perspective. Methods: This was a mixed methodology, market research study involving ethnography, structured interviews, video diaries, and patient tasks. Patients had been diagnosed with diffuse cutaneous systemic sclerosis for ⩾ 6 months and were recruited via healthcare professionals or patient associations (France, Italy, the United Kingdom, and the United States). Patients filmed short (~15 min) daily video diaries about their lives over 7 days and participated in ethnographic sessions, patient tasks, and structured video interviews. In Germany and Spain, patients participated in 60-min telephone interviews. Results: Twenty-three patients (mean age: 54 years; 83% women; minimum disease duration: 6 months) participated in the study. Time to diagnosis was prolonged, as patients overlooked their symptoms and some healthcare professionals attributed symptoms to other causes. Patients rarely received additional information or support services at diagnosis. Importantly, although patients were aware of the seriousness of organ involvement, they reported that skin changes, pain, and fatigue impaired their ability to perform routine tasks. Patients had a high prescription treatment burden (mean: 10 tablets/day; up to >25 tablets/day) with additional non-prescription medication taken for other comorbidities. Treatment discontinuation was common due to side effects. Patients experienced diffuse cutaneous systemic sclerosis as a loss of independence and self-esteem. Moreover, patients tended to have small support networks, and emotional support services were not offered as standard care. Conclusion: Patients with diffuse cutaneous systemic sclerosis had high treatment and disease burdens, with skin changes, pain, and fatigue profoundly affecting their lives. There is an unmet need for patient information at the time of diagnosis and emotional support services throughout the patient's journey with diffuse cutaneous systemic sclerosis. Based on the results of this study, we provide recommendations for improving diffuse cutaneous systemic sclerosis care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".