Children with systemic autoinflammatory diseases have multiple, mixed ethnicities that reflect regional ethnic diversity
Bibliographic record
Abstract
OBJECTIVES: To evaluate the ethnic diversity of children with a systemic autoinflammatory disease (SAID) in a multi-ethnic Canadian province. METHODS: Self-reported ethnicity of 149 children and adolescents with a SAID in British Columbia, Canada, was analysed for ethnic representation among individual patients, across the cohort, within particular SAIDs, and compared to provincial census data on ethnic diversity. RESULTS: Half of reported cases had a diagnosis of either PFAPA (23.5%) or an unclassifiable autoinflammatory syndrome (31.5%), with a monogenic SAID diagnosed in only 12.8% of cases. The majority of participants (73.1%) were mixed ethnicity with European and Asian heritage reported most frequently (57.0% and 23.0% of all responses, respectively). Ethnic diversity reflected regional diversity except for West Asian, Arabic, Jewish, and Eastern European heritage, which were over-represented in SAID patients, and Chinese descent, which was under-represented in our cohort compared to the general population of British Columbia. CONCLUSIONS: Results from this study show extensive multi-ethnic diversity in individual patients and across the various SAIDs inclusive of monogenic SAIDs that are frequently associated with particular ethnicities. Although not disproportionately represented, this is the first report of systemic autoinflammatory disease in Canadian children of Indigenous heritage.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".