S481 Deciphering the Intersection of Celiac Disease and Eosinophilic Esophagitis in Pediatric and Adult Patients: Insights From a Global Cohort
Bibliographic record
Abstract
Introduction: Eosinophilic esophagitis (EoE) and Celiac Disease (CD) are helper T-cell driven chronic inflammatory gastrointestinal disorders. Previous studies have hinted at a possible association between the two, yet connections on a large scale remain unexplored. This study aimed to examine and characterize EoE and CD connections in a real-world population database. Methods: We queried TriNetX, a global healthcare database for patients based on ICD-10 codes. We divided subjects into 6 cohorts, based on their diagnosis of CD and EoE and age from April 28th, 2003 to April 28th, 2023. EOE and Celiac diagnoses had to be documented twice at least 1 month apart to ensure accuracy as previously described by other authors. Patient demographics, prevalence, incidence, and characteristics of each cohort were extracted over 20 years. Attributes were compared using chi-square testing with significance set at P = 0.05. Results: Analysis demonstrated a higher incidence (511/100,000) and prevalence (3.6%) of EoE in pediatric celiac patients compared to adult celiac patients (146/100,000 and 1.4%, respectively, P < 0.001). Pediatric celiac patients did not differ in incidence of EoE in males and females (P = 0.4448), while among adult celiac patients, females (59%) were more affected (P = 0.001). Geographically in USA, there is a significant difference in the distribution of EoE cases among pediatric celiac patients, adult celiac patients, and the general adult population by region (P = 0.004916). Descriptively, the Midwest appears to have the highest number of cases in both pediatric and adult celiac patients, with the West having the lowest number in the pediatric population and the South having the lowest number in the adult population. The majority of EoE cases in celiac patients were White (82% pediatric, 89% adult). A higher prevalence of asthma, allergic rhinitis, and atopic dermatitis was noted among EoE patients (Table 1). Conclusion: The interplay between EoE and CD reveals a complex relationship, with higher EoE prevalence observed in adult females with CD with no difference among the pediatric population. Notably, the correlation with Th2 mediated conditions underscores a potential crosstalk among these disorders. Geographical variations suggest environmental and dietary influence on EoE development. These insights, which highlight shared disease mechanisms, have crucial implications for patient diagnosis, treatment, and management strategies. Table 1. - Descriptive characteristics of Celiac Disease patients with and without the diagnosis of Eosinophilic Esophagitis from April 28th, 2003 – April 28th, 2023 Peds Celiac (N%) Adults Celiac (N%) Gen Adult pop (N%) Incidence of EoE per 10^5 per year 511 146 15 Prevalence, % 3.6 1.4 0.029 EOE Status EoE No EoE EoE No EoE EoE No EoE Number 480 23,831 503 64,231 29,103 93,534,081 Age, y ± SD 15.9 ± 5.41 19.3 ± 8.39 40.2 ± 15.8 50.9 ± 19.3 44.3 ± 15.9 52.5 ± 18.6 Sex Male 251 (52) 8,004 (34) 206 (41) 16,781 (26) 17,088 (55) 41,793,438 (45) Female 229 (48) 15,817 (66) 297 (59) 47,442 (74) 12,011 (45) 51,557,927 (55) Region Northeast 107 (22) 6,099 (26) 162 (32) 22,702 (35) 9,471 (33) 18,676,929 (20) Midwest 145 (30) 6,251 (26) 125 (25) 10,592 (16) 6,936 (24) 8,813,549 (9) South 140 (29) 6,625 (28) 103 (20) 15,765 (25) 7,243 (25) 27,991,281 (30) West 79 (16) 3,272 (14) 109 (21) 8,759 (14) 5,080 (14) 7,935,841 (8) Unknown 1-10 (2) 41 (1) 1-10 (2) 478 (1) 91 (1) 3,781,839 (4) Ex-US regions 0 1,543 (6) 0 5,935 (9) 282 (1) 26,595,473 (28) Race White 398 (82) 19,006 (80) 451 (89) 53,903 (84) 24,861 (85) 42,018,710 (45) African American 1-10 (2) 439 (2) 14 (2) 1,381 (2) 1,061 (4) 9,099,019 (10) Asian 1-10 (2) 283 (1) 1-10 (1) 734 (1) 287 (1) 2,257,940 (2) American Indian 1-10 (2) 71 (0) 1-10 (1) 132 (0) 79 (0) 288,725 (0) Native Hawaiian 1-10 (2) 17 (0) 1-10 (1) 22 (0) 12 (0) 110,501 (0) Unknown 64 (13) 4,015 (17) 34 (6) 8,059 (13) 2,803 (10) 39,759,186 (43) Ethnicity Hispanic or Latino 26 (5) 1,269 (5) 14 (3) 2,012 (3) 833 (3) 5,015,316 (5) Non-Hispanic or Latino 403 (84) 17,722 (75) 400 (79) 42,248 (66) 22,587 (78) 34,088,581 (37) Unknown 51 (11) 4,840 (2) 89 (18) 19,971 (31) 5,683 (19) 54,430,184 (58) Diagnoses Asthma 156 (33) 3,879 (16) 181 (36) 12,728 (20) 8,890 (31) 40,226 (4) Atopic Dermatitis 60 (13) 907 (4) 24 (5) 1,462 (2) 1,202 (4) 4,405 (0) RA 1-10 (2) 135 (1) 23 (5) 2,084 (3) 395 (1) 5,590 (1) Autoimmune hepatitis 1-10 (2) 71 (0) 1-10 (1) 479 (1) 45 (0) 384 (0) Down syndrome 1-10 (2) 830 (3) 1-10 (1) 765 (1) 28 (0) 607 (0) Turner Syndrome 1-10 (2) 139 (1) 1-10 (1) 150 (0) 1-10 (0) 163 (0) T1DM 51 (11) 3,821 (16) 23 (5) 4,966 (8) 419 (1) 8,265 (1) Autoimmune thyroiditis 23 (5) 1,548 (6) 40 (8) 4,219 (7) 638 (2) 3,083 (0) Allergic rhinitis 170 (35) 3,598 (15) 185 (37) 13,049 (20) 10,351 (36) 33,846 (3) Chronic rhinitis 48 (10) 961 (4) 45 (9) 3,165 (5) 2,503 (9) 6,495 (1) TriNetX does report patient totals less than 10 and therefore are indicated by “1-10” on Table.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".