Prediction for Risk of Hypouricemia in Hospitalized Patients: A Single-center, Retrospective Cohort Study

Intern Med. 2024 Sep 11. doi: 10.2169/internalmedicine.3517-24. Online ahead of print.

Abstract

Background Hypouricemia, defined as a serum uric acid (SUA) level ≤2 mg/dL, could be a risk factor for death in hospitalized patients. However, how explanatory variables can explain hypouricemia as an objective variable in a logistic regression analysis remains unknown. Purpose To predict the risk factors for hypouricemia in hospitalized patients using a robust Bayesian logistic (RBL) model. Methods This study retrospectively enrolled patients who visited Yonago Medical Center between April 2020 and March 2021. The association between potential risk factors and hypouricemia was analyzed using the RBL model in Python-modulated PyMC3. The final model was selected based on the lowest Watanabe-Akaike information criterion (WAIC). Results Of the 618 patients, 64 (10.4%) had hypouricemia. Based on the model according to the lowest WAIC, independent risk factors for hypouricemia were febuxostat [odds ratio (OR) 5.46, 95% confidence interval (CI) 2.32-13.4], amino acids in parenteral nutrition (OR 5.19, 95% CI 1.62-15.1), TMP-SMX (OR 4.20, 95% CI 1.66-10.9), emaciation (OR 3.48, 95% CI 1.75-7.21), and serum sodium level (OR 0.90, 95% CI 0.84-0.96). Conclusion The RBL model predicted amino acids in parenteral nutrition, TMP-SMX, emaciation, and low serum sodium levels for hypouricemia, in addition to the authentic risk factor febuxostat.

Keywords: Bayesian logistic analysis; TMP-SMX; amino acid in parenteral nutrition; febuxostat; hospitalized patients; hypouricemia; low serum sodium level.