Onset to first visit intervals in childhood rheumatic diseases.
Bibliographic record
Abstract
OBJECTIVE: To determine time intervals between onset of symptoms of a childhood rheumatic disease and first visit to a pediatric rheumatology clinic and to evaluate factors influencing onset to first visit intervals. METHODS: Onset to first visit intervals were analyzed in 836 children representing the 10 most common diseases in a pediatric rheumatology clinic population of 1093. RESULTS: Among 836 subjects, 469 (56.1%) could identify month of symptom onset. Among patients with juvenile rheumatoid arthritis (JRA) 125 of 195 (64.1%) with pauciarticular, 58 of 105 (55.2%) with polyarticular, and 28 of 36 (77.8%) with systemic subtypes were able to determine time interval between symptom onset and first visit. Month intervals were confidently established in 80 of 250 with a spondyloarthropathy (32.4%), 19 of 52 (36.5%) with psoriatic arthropathy, 65 of 72 (90.3%) with Henoch-Schönlein purpura (HSP), 50 of 56 (89.3%) with Kawasaki disease, 22 of 34 (64.7%) with systemic lupus erythematosus, 13 of 18 (72.2%) with dermatomyositis, and 9 of 18 (50%) with localized scleroderma. Determination of onset was significantly more likely in HSP than in other diagnostic categories except systemic JRA, and more likely in Kawasaki disease than other disease categories except systemic JRA and dermatomyositis. In the group of 469, 287 (61.2%) were seen within 2 months of symptom onset and 447 (95.3%) within 1 year of symptom onset. CONCLUSION: Diseases ordinarily typified by an abrupt and acute onset of symptoms were referred most promptly, suggesting that acuity of symptoms at disease onset is the factor that most influences promptness of referral. Prospective studies are required to establish how onset to first visit intervals might influence disease outcomes and to devise best practice referral guidelines.
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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 | 0.001 | 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".