Predictor and prognostic modeling in cardiorenal syndrome type 2: a retrospective study of multicenter.

BACKGROUND

Type 2 CRS is characterized by the development of renal dysfunction secondary to chronic cardiac disease. Despite its high morbidity and mortality, there is a lack of robust diagnostic tools and prognostic models to guide clinical management.

METHODS

This multicenter retrospective study included patients diagnosed with CRS type 2 based on the 2019 American Heart Association definition. Data were collected from electronic medical records of three hospitals between January 2021 and December 2023. Advanced statistical methods, including receiver operating characteristic (ROC) curve analysis, univariate Kaplan-Meier (KM) analysis, and multivariable Cox proportional hazards regression, were utilized to develop a nomogram for predicting patient prognosis.

RESULTS

The study included 519 patients with CRS-2. Independent predictors of adverse outcomes included elevated serum creatinine and blood urea nitrogen (BUN) levels, decreased platelet count, elevated B-type natriuretic peptide (BNP), and decreased oxygen partial pressure (PaO2). These findings suggest that close monitoring of these markers is essential in clinical practice to identify patients at high risk of adverse events early on.

CONCLUSION

Our study provides evidence that serum creatinine, BUN, platelet count, BNP, and PaO2 are independent predictors of adverse outcomes in patients with Type 2 CRS.