Racial Disparities in Surgery
Bibliographic record
Abstract
Objective: To determine if Black race is associated with worse short-term postoperative morbidity and mortality when compared to White race in a contemporary, cross-specialty-matched cohort. Background: Growing evidence suggests poorer outcomes for Black patients undergoing surgery. Methods: A retrospective analysis was conducted comprising of all patients undergoing surgery in the National Surgical Quality Improvement Program dataset between 2012 and 2018. One-to-one coarsened exact matching was conducted between Black and White patients. Primary outcome was rate of 30-day morbidity and mortality. Results: After 1:1 matching, 615,118 patients were identified. Black race was associated with increased rate of all-cause morbidity (odds ratio [OR] = 1.10, 95% confidence interval [CI] 1.08–1.13, P < 0.001) and mortality (OR = 1.15, 95% CI 1.01–1.31, P = 0.039). Black race was associated with increased risk of re-intubation (OR = 1.33, 95% CI 1.21–1.48, P < 0.001), pulmonary embolism (OR = 1.55, 95% CI 1.40–1.71, P < 0.001), failure to wean from ventilator for >48 hours (OR = 1.14, 95% CI 1.02–1.29, P < 0.001), progressive renal insufficiency (OR = 1.63, 95% CI 1.43–1.86, P < 0.001), acute renal failure (OR = 1.39, 95% CI 1.16–1.66, P < 0.001), cardiac arrest (OR = 1.47, 95% CI 1.24–1.76 P < 0.001), bleeding requiring transfusion (OR = 1.39, 95% CI 1.34–1.43, P < 0.001), DVT/thrombophlebitis (OR = 1.24, 95% CI 1.14–1.35, P < 0.001), and sepsis/septic shock (OR = 1.09, 95% CI 1.03–1.15, P < 0.001). Black patients were also more likely to have a readmission (OR = 1.12, 95% CI 1.10–1.16, P < 0.001), discharge to a rehabilitation center (OR = 1.73, 95% CI 1.66–1.80, P < 0.001) or facility other than home (OR = 1.20, 95% CI 1.16–1.23, P < 0.001). Conclusion and Relevance: This contemporary matched analysis demonstrates an association with increased morbidity, mortality, and readmissions for Black patients across surgical procedures and specialties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".