A3 CELIAC DISEASE AUTOIMMUNITY INCREASING AMONG VARIOUS PEDIATRIC SUBGROUPS IN ALBERTA, CANADA
Bibliographic record
Abstract
Abstract Background Celiac disease (CeD) autoimmunity, defined as elevated tissue transglutaminase (TTG) levels with or without biopsy confirmation, is rising among children in Canada; however, further investigation is needed to understand if this varies across pediatric subpopulations. Aims To evaluate incidence and trends in CeD autoimmunity among different pediatric subgroups. Methods Using population-based administrative data, we identified individuals under 15 years old during their first positive TTG test in Alberta from April 2015 to March 2024. Based on the year of test, we determined socioeconomic status by matching patient postal code to census level dissemination area (which translate to material and social deprivation quintiles) and geographic residence. Incidence per 100,000 person-years (PY) and 95% confidence intervals (CIs) were calculated for subgroups (sex, age, rurality, material and social deprivation) within time periods (pre-pandemic [2015–2019], pandemic [2020–2022], and post-pandemic [2023–2024]). Incidence rate ratios (IRRs) were estimated to compare pre-pandemic and post-pandemic rates. Results A total of 5,141 children with incident CeD autoimmunity were identified. The highest incidence was observed post-pandemic (92 per 100,000 PY), particularly among those aged 5–9 years (135 per 100,000 PY), those living in the least materially deprived areas (117 per 100,000 PY), and females (113 per 100,000 PY). All subgroups saw significantly higher rates in the post-pandemic period relative to the pre-pandemic period, except for those most materially deprived (IRR = 1.1 [95% CI: 0.9, 1.4]). A larger increase in rates was seen in those most materially privileged (IRR = 1.7 [95% CI: 1.5, 2.0]). A change in incidence was also more pronounced among children in rural (IRR = 1.7 [95% CI: 1.5, 1.9]) compared to those in urban areas (IRR = 1.3 [95% CI: 1.2, 1.4]). Conclusions Although rates of CeD autoimmunity vary between pediatric subpopulations, most groups are experiencing significant increases over time. This includes populations historically experiencing lower rates (e.g., those in rural areas), indicating a mounting burden of CeD for the future. Incidence rates for CeD autoimmunity across subgroups and time *comparing post-pandemic to pre-pandemic Funding Agencies CIHRTRIANGLE (Training a new generation of researchers in gastroenterology and liver)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".