Social Determinants of Outcomes in Inflammatory Bowel Disease
Bibliographic record
Abstract
INTRODUCTION: In a population-based inflammatory bowel disease (IBD) cohort, we aimed to determine whether having lower socioeconomic status (LSS) impacted on outcomes. METHODS: We identified all 9,298 Manitoba residents with IBD from April 1, 1995, to March 31, 2018 by applying a validated case definition to the Manitoba Health administrative database. We could identify all outpatient physician visits, hospitalizations, surgeries, intensive care unit admissions, and prescription medications. Their data were linked with 2 Manitoba databases, one identifying all persons who received Employment and Income Assistance and another identifying all persons with Child and Family Services contact. Area-level socioeconomic status was defined by a factor score incorporating average household income, single parent households, unemployment rate, and high school education rate. LSS was identified by any of ever being registered for Employment and Income Assistance or with Child and Family Services or being in the lowest area-level socioeconomic status quintile. RESULTS: Comparing persons with LSS vs those without any markers of LSS, there were increased rates of annual outpatient physician visits (relative risk [RR] = 1.10, 95% confidence interval [CI] = 1.06-1.13), hospitalizations (RR = 1.38, 95% CI = 1.31-1.44), intensive care unit admission (RR = 1.94, 95% CI = 1.65-2.27), use of corticosteroids >2,000 mg/yr (RR = 1.12, 95% CI = 1.03-1.21), and death (hazard ratio 1.53, 95% CI = 1.36-1.73). Narcotics (RR = 2.17, 95% CI = 2.01-2.34) and psychotropic medication use (RR = 1.98, 95% CI = 1.84-2.13) were increased. The impact of LSS was greater for those with Crohn's disease than for those with ulcerative colitis. DISCUSSION: LSS was associated with worse outcomes in persons with IBD. Social determinants of health at time of diagnosis should be highly considered and addressed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".