This study analyzed gender-specific variations in variceal bleeding using the Nationwide Admission Database (HCUP), examining 2,858,576 adult admissions from 2019 to 2024. Focusing on cirrhotic patients, it evaluated differences in 30-day and 60-day readmission rates between genders. Chi-square tests assessed incidence and readmission disparities, while logistic regression explored the impact of gender and race on readmission probabilities. ROC curves and AUC values gauged the models' predictive accuracy, enhancing understanding of gender-based outcomes in cirrhosis management.

Data from the Nationwide Admission Database (HCUP) from 2019 to 2024, covering 2,858,576 admissions, was used to examine gender-specific variations in variceal bleeding among cirrhotic patients. The study focused on assessing 30-day and 60-day readmission rates, using chi-square tests to evaluate incidence and readmission differences between genders and other demographic factors. Logistic regression models analyzed the impact of gender and race on readmission likelihood, particularly among obese patients, with ROC curves and AUC values measuring the predictive accuracy of these models.

From 2019 to 2024, HCUP data on 2.8 million adult admissions identified 94,124 patients with cirrhosis and variceal bleeding. Of these, 43.8% were female. Chi-square analysis showed significant gender disparities in readmissions, with females experiencing higher rates. The 30-day readmission rate had a chi-square of 49,003 (p = 0.214); the 60-day rate showed p < 0.001. Logistic regression revealed gender and race effects, with White females showing the highest coefficients. The 30-day model had strong predictive accuracy (AUC).

This study highlights significant gender disparities in cirrhotic patients with variceal bleeding, with females showing higher 60-day readmission rates than males. Chi-square tests and logistic regression confirmed gender as a key factor influencing readmissions, with White females exhibiting higher risk coefficients. The 30-day readmission model demonstrated high predictive accuracy (AUC), emphasizing the need for gender-specific interventions to manage cirrhosis and reduce readmissions. These findings support personalized strategies for improving care and outcomes in diverse patient groups.