This media is currently not available.
Uncovering the Links Between Obesity, Race, Gender, and Upper GI Bleeding: Findings From a National Cohort of 2.8 Million Patients
Poster Abstract

Aims

Amidst the growing concern over obesity's health effects, particularly on upper gastrointestinal bleeding (UGIB), this study utilizes the Nationwide Admission Database (HCUP) to explore how obesity, race, and gender influence UGIB and its readmission rates. Covering 2019 to 2024, the research analyzes over 2.8 million adult hospital admissions, specifically examining 234,024 patients with obesity-related diagnoses. The aim is to assess whether obesity correlates with increased UGIB incidences and subsequent short-term readmissions, thereby providing insights into the demographic and clinical factors that may exacerbate UGIB risks and healthcare burdens.

Methods

From 2019 to 2024, the Nationwide Admission Database (HCUP) was accessed to study 2,858,576 adult hospital admissions, analyzing the influence of obesity, race, and gender on upper gastrointestinal bleeding (UGIB) and 30-day and 60-day readmission rates. The study stratified patients by obesity status, using chi-square tests and logistic regression to evaluate UGIB incidence and readmission differences. ROC curves with Area Under the Curve (AUC) assessed predictive accuracy, with statistical significance established at p < 0.05.

Results

From 2019 to 2024, the Nationwide Admission Database (HCUP) was utilized to analyze 2,858,576 adult hospital admissions, focusing on 234,024 patients diagnosed with diverticulitis, including 112,014 obese individuals (BMI > 30). Chi-square tests revealed no significant difference in UGIB incidence between obese and non-obese groups (p = 0.795). However, among obese patients with UGIB, significant associations were found with 30-day (p = 0.032) and 60-day (p = 0.041) readmissions. African Americans showed a significant association with UGIB incidence (p < 0.001). Logistic regression indicated race impacted 30-day readmissions (p < 0.05 for Black and Hispanic patients) and gender influenced 60-day readmissions, notably in males and Hispanics (p < 0.001 and p = 0.031, respectively). ROC analysis demonstrated moderate predictive accuracy for UGIB (AUC = 0.71) and readmissions, with 60-day predictions showing better performance (AUC = 0.89).

Conclusions

This study examines obesity, race, and gender in UGIB outcomes. While obesity didn’t raise initial UGIB risk (p = 0.795), it was linked to higher 30- and 60-day readmissions. African Americans showed notable disparities. Predictive model challenges highlight the need for targeted care and research.