Racial Disparities in Cholecystectomy Rates During Hospitalizations for Acute Gallstone Pancreatitis: A National Survey
Bibliographic record
Abstract
BACKGROUND: Practice guidelines advocate performing cholecystectomy for acute gallstone pancreatitis during the same hospitalization stay. Our objectives were to determine nationwide rates of adherence to these guidelines in the United States and whether this varied with race and ethnicity. METHODS: We queried the Nationwide Inpatient Sample (NIS) to identify admissions for acute gallstone pancreatitis between 1998 and 2003. We calculated overall and race-specific proportions of patients who underwent cholecystectomy or endoscopic retrograde cholangiopancreatography (ERCP) prior to discharge. We used multivariate analysis to determine racial effects while adjusting for age, comorbidity, health insurance payer, and hospital factors. RESULTS: The overall rate of cholecystectomy was 51% and that of either cholecystectomy or ERCP was 62%. Cholecystectomy rates were lower among African Americans (AAs) and Asians compared to Whites (44% and 43%, respectively, vs 50%, P < 0.001). After multivariate adjustment, the odds of cholecystectomy was lower in AAs (OR 0.68, 95% CI 0.63-0.73) and Asians/Pacific Islanders (OR 0.75, 95% CI 0.65-0.87) relative to Whites, while rates were modestly higher among Hispanics (OR 1.12, 95% CI 1.03-1.22). AAs were less likely to receive ERCP than Whites (OR 0.71, 95% CI 0.65-0.78). In contrast, Asians/Pacific Islanders (OR 1.40, 95% CI 1.16-1.69) and Hispanics (OR 1.19, 95% CI 1.09-1.29) were more likely to receive ERCP than Whites. CONCLUSIONS: Despite practice guidelines, about only half of admissions for gallstone pancreatitis receive cholecystectomy during the same hospitalization, and cholecystectomy rates vary substantially by race. These findings raise concerns regarding suboptimal healthcare delivery.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".