Towards Equitable Surgical Management of Inflammatory Bowel Disease: A Systematic Review of Disparities in Surgery for Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Existing evidence for disparities in inflammatory bowel disease is fragmented and heterogenous. Underlying mechanisms for differences in outcomes based on race and socioeconomic status remain undefined. We performed a systematic review of the literature to examine disparities in surgery for inflammatory bowel disease in the United States. METHODS: Electronic databases were searched from 2000 through June 11, 2021, to identify studies addressing disparities in surgical treatment for adults with inflammatory bowel disease. Eligible English-language publications comparing the use or outcomes of surgery by racial/ethnic, socioeconomic, geographic, and/or institutional factors were included. Studies were grouped according to whether outcomes of surgery were reported or surgery itself was the relevant end point (utilization). Quality was assessed using the Newcastle-Ottawa Scale for observational studies. RESULTS: Forty-five studies were included. Twenty-four reported surgical outcomes and 21addressed utilization. Race/ethnicity was considered in 96% of studies, socioeconomic status in 44%, geographic factors in 27%, and hospital/surgeon factors in 22%. Although study populations and end points were heterogeneous, Black and Hispanic patients were less likely to undergo abdominal surgery when hospitalized; they were more likely to have a complication when they did have surgery. Differences based on race were correlated with socioeconomic factors but frequently remained significant after adjustments for insurance and baseline health. CONCLUSIONS: Surgical disparities based on sociologic and structural factors reflect unidentified differences in multidisciplinary disease management. A broad, multidimensional approach to disparities research with more granular and diverse data sources is needed to improve health care quality and equity for inflammatory bowel disease.
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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 | 0.015 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".