Scleroderma: health services utilization from patients' perspective.
Bibliographic record
Abstract
OBJECTIVE: To evaluate utilization of the health care system by patients with scleroderma by determining which physicians are diagnosing and following patients, what tests are being used, and what is the time to diagnosis, as measured over the past 3 decades. METHODS: A self-administered questionnaire (available in English and French) was mailed up to twice to 1,437 members of 12 provincial chapters of the Scleroderma Society of Canada. RESULTS: The overall response rate was 63%. Eighty-nine percent of respondents were female. Sixty percent were between the ages of 30 and 59 years. Forty-three percent were diagnosed by a rheumatologist. Among patients with diffuse disease, 90% have been followed by a rheumatologist; however just over half of patients have seen a gastroenterologist (54%), cardiologist (51%), respirologist (67%), and less than half have seen a dermatologist (42%), nephrologist (13%), physiotherapist (46%), or occupational therapist (34%). The mean time to diagnosis over the last 3 decades is 2.4 years. At diagnosis less than 50% of patients had an electrocardiogram, echocardiogram, gastroscopy, thorax CT, or skin thickness measurements, whereas over 50% of patients had a chest radiograph and pulmonary function testing. CONCLUSION: Less than half of patients were diagnosed by a rheumatologist, and time to diagnosis from onset of symptoms has remained unchanged over the last 3 decades. Despite their complex, multisystemic disease, less than 50% of patients see sub-specialists or had baseline screening tests for organ involvement of their systemic sclerosis. Further research is needed on health services utilization and on determinants of access to care by patients with scleroderma.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".