S864 Racial and Ethnic Disparities in Hospitalizations and Emergency Department Use of Persons With Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: The prevalence of inflammatory bowel disease (IBD) is rising worldwide though it remains unknown how race or ethnicity influences IBD-related healthcare utilization. We aimed to determine potential differences in IBD-related hospitalizations and emergency department (ED) visits amongst different races and ethnicities. Methods: Electronic databases (Medline and Embase) were searched through December 20th, 2021. All studies reporting IBD-related hospitalizations, readmission after discharge, and ED visits by race or ethnicity were included. Differences in IBD location, phenotype, and treatment between races and ethnicities were assessed. Effect estimates were reported as odds ratios (OR) with 95% confidence intervals (CI). Where applicable, subgroup analysis restricting patient age (pediatric vs. adult) was performed. Heterogeneity was assessed using the I2 statistic, with >50% suggesting significant heterogeneity. Results: Twenty-three observational studies assessed the influence of race and ethnicity on IBD-related hospitalizations and 7 studies on ED visits. Compared to White patients, the likelihood of IBD-related hospitalization was higher in Black (OR 1.54, 95% CI, 1.06-2.24, I2=77.0%) and Hispanic (OR 1.38, 95% CI, 1.01-1.88, I2=37.0%) but not Asian (OR 0.34, 95% CI, 0.02-7.40, I2=95.0%) or South Asian (OR 1.09, 95% CI, 0.47-2.53, I2=60.0%) patients. Furthermore, Black patients had a higher likelihood of readmission to the hospital up to 12 months after discharge compared to White patients (OR 1.41, 95% CI, 1.09-1.82, I2=41.0%). Black adult, but not pediatric, patients had greater odds of IBD-related ED visits compared to adult White patients (OR 1.74, 95% CI, 1.32-2.30, I2=0%). Compared to White patients, Black patients were less likely to have ileal disease, more likely to have perianal disease, and have similar likelihood of receiving biologic therapy. No differences in disease phenotype or therapy exposure were observed between other races. Conclusion: Black patients with IBD are more likely to be hospitalized, readmitted within 12 months, and visit the ED for IBD reasons compared to White patients. Disease phenotype and severity do not account for these differences. As such, future research is imminently required to determine factors behind these differences to promote, and achieve, equiTable care for all persons living with IBD.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.033 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".