Race and Inflammatory Bowel Disease in an Urban Healthcare System
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) is increasingly common among non-Caucasian populations, but interracial differences in disease characteristics and management are not well-characterized. AIMS: We tested the hypothesis that disease characteristics and management vary by race among IBD patients in an ethnically diverse healthcare system. METHODS: A retrospective study of the safety net healthcare system of San Francisco, CA, from 1996 to 2009 was undertaken. Patient records with International Classification of Diseases, 9th Revision (ICD9) codes 555.xx, 556.xx, and 558.xx were reviewed. Adult patients with confirmed IBD diagnoses were included. Interracial variations in disease characteristics and management were assessed broadly; focused between-race comparisons identified specific differences. RESULTS: The 228 subjects included 77 (33.4%) with Crohn's disease (CD), 150 (65.8%) with ulcerative colitis, and 1 (0.4%) with IBD, type unclassified. The race distribution included 105 (46.1%) white, 34 (14.9%) black, 35 (15.4%) Hispanic, and 51 (22.4%) Asian subjects. Asians and Hispanics were diagnosed at older ages (41.0 and 37.1 years, respectively) and had shorter disease durations (5.4 and 5.2 years, respectively) than whites (30.5 years at diagnosis and 8.6 years duration, P < 0.05) and blacks (31.7 years at diagnosis and 12.1 years duration, P < 0.05). CD was more common among blacks (50% of subjects) than Asians (25.5% of subjects, P = 0.015). The Montreal classification of IBD was similar among races. Hispanics were less likely than others to be treated with 5-aminosalicylates (5-ASA), immunomodulators, and steroids. Medical and surgical management was otherwise similar among races. CONCLUSIONS: Modest race-based differences in IBD characteristics exist in this racially diverse healthcare system, but the management of IBD is similar among race groups.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".