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Predictor and prognostic modeling in cardiorenal syndrome type 2: a retrospective study of multicenter
Bin Wang1, Xie Zheng1, Qinghui Fu2
1The Department of Emergency, People's Hospital of Anji, Anji, Zhejiang, China.
Insights
Type 2 Cardiac Related Syndrome (CRS) patients at high risk can be identified by monitoring creatinine, BUN, platelets, BNP, and PaO2. Early detection aids in managing this condition with high morbidity and mortality.
Area of Science:
- Cardiology
- Nephrology
- Critical Care Medicine
Background:
- Type 2 Cardiac Related Syndrome (CRS) involves renal dysfunction due to chronic cardiac disease.
- It presents high morbidity and mortality, yet lacks effective diagnostic and prognostic tools.
Purpose of the Study:
- To identify independent predictors of adverse outcomes in Type 2 CRS patients.
- To develop a prognostic nomogram for guiding clinical management.
Main Methods:
- Retrospective analysis of 519 Type 2 CRS patients from three hospitals (Jan 2021-Dec 2023).
- Utilized ROC curve analysis, Kaplan-Meier analysis, and Cox regression to identify predictors.
- Developed a nomogram for prognosis prediction.
Main Results:
- Elevated serum creatinine and blood urea nitrogen (BUN).
- Decreased platelet count.
- Elevated B-type natriuretic peptide (BNP) and decreased oxygen partial pressure (PaO2) were independent predictors of adverse outcomes.
Conclusions:
- Serum creatinine, BUN, platelet count, BNP, and PaO2 are key predictors of adverse outcomes in Type 2 CRS.
- Close monitoring of these markers is crucial for early identification of high-risk patients.
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.
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