Bibliographic record
Abstract
OBJECTIVE: To analyze a prospectively maintained pediatric rheumatology clinic disease registry. METHODS: A total of 3269 consecutive referrals to the Pediatric Rheumatology Clinic, University of Saskatchewan, during the period 1981-2004 were analyzed. RESULTS: Among 3269 patients, a diagnosis was established in 2098 (64.2%). Within this group, 72 subjects (3.4%) were determined to be healthy. Of the remaining 2026 diagnosed patients (62.0% of the total population), 1032 (50.9%) had a rheumatic disease and 994 (49.1%) a nonrheumatic disease. A diagnosis was not established in 1171 patients (35.8%). Among the 1032 patients with a rheumatic disease, 326 (31.6%) had juvenile rheumatoid arthritis (JRA), 360 (34.9%) a spondyloarthropathy (SpA), and 225 (21.8%) a collagen vascular/connective tissue rheumatic disease. The remaining 121 patients with a rheumatic disease (11.7%) had a variety of other conditions. Of the 994 nonrheumatic disease patients, 37 (3.7%) with ocular inflammatory conditions had been referred to exclude an associated rheumatic disease. The remaining group of 957 patients comprised 345 (36.1%) with an orthopedic, mechanical or traumatic condition, 231 (24.1%) had an infection, 45 (4.7%) a hematologic or neoplastic disease, and 336 (35.1%) a variety of other conditions. Current clinic point prevalences for JRA, SpA, and collagen vascular diseases are 35.0, 16.9 and 17.7/100,000, respectively. The mean annual clinic referral incidences of JRA, SpA, and collagen vascular/connective tissue diseases were, respectively, 4.7, 5.2, and 1.7/100,000 children. CONCLUSION: Disease registries help establish the frequencies and spectrum of childhood rheumatic diseases and the role of pediatric rheumatology programs in evaluating and caring for children with a wide variety of conditions. Longitudinal disease registries aid in characterizing clinical, epidemiologic, and demographic features of childhood rheumatic diseases.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".