Association between exposure to proton pump inhibitors and hyperuricemia: risk prediction model establishment and...

This study aims to explore whether the exposure to proton pump inhibitor (PPI) is a potential independent risk factor for the development of new-onset hyperuricemia in patients who were hospitalized due to gastrointestinal bleeding, and to establish a validated clinical prediction indicator.

We conducted a retrospective cohort study involving inpatients of the gastroenterology department admitted to West China Hospital between August 2022 and August 2025. LASSO and logistic regression were utilized to determine potential risk factors, and a nomogram prediction model was subsequently established accordingly. The model's discriminative ability was assessed using the area under the receiver operating characteristic (ROC) curve (AUC). Calibration curves and decision curve analysis (DCA) were utilized to evaluate the model's accuracy and clinical utility.

Of the 1900 patients enrolled, 10.5% developed new-onset hyperuricemia. Multivariate analysis identified PPI as a significant independent risk factor for new-onset hyperuricemia with adjusted odds ratio (OR) (95% CI) of 4.86 (3.04, 7.78). The nomogram incorporated ten predictors: gender, age, hospital time, BMI, smoking, triglyceride levels, PPIs, CCBs, diuretics, and hyperlipidemia. The model exhibited good discrimination, with AUCs of 0.759 (95% CI: 0.718∼0.800) and 0.727 (95% CI: 0.654∼0.799) in the training and validation set, respectively. The Hosmer-Lemeshow test demonstrated the model was well-calibrated (P > 0.05), and DCA confirmed that the model provided significant clinical net benefits.

PPI exposure may be a potential independent risk factor for new-onset hyperuricemia in patients who were hospitalized due to gastrointestinal bleeding. The developed nomogram demonstrates good predictive performance and may assist clinicians in assessing hyperuricemia risk and optimizing individualized patient management.