Nomogram Model for Cardiac Surgery-Associated Acute Kidney Injury Based on Clinical Characteristics Combined with...

Area of Science:

• Nephrology
• Cardiology
• Biomarkers

Background:

• Cardiac surgery-associated acute kidney injury (CSA-AKI) is a significant complication.
• Predictive tools for CSA-AKI are crucial for patient management.

Purpose of the Study:

• To identify risk factors for CSA-AKI in adult patients undergoing cardiac surgery.
• To develop and validate a predictive nomogram model for CSA-AKI using plasma soluble urokinase-type plasminogen activator receptor (suPAR).

Main Methods:

• Plasma suPAR levels were measured using ELISA in 170 patients undergoing cardiac surgery.
• Multivariable logistic regression identified CSA-AKI risk factors.
• A nomogram model was constructed and validated using ROC curve, AUC, Bootstrap, and DCA.

Main Results:

• Independent risk factors for CSA-AKI included male sex, age ≥ 50 years, operation time ≥ 290 minutes, postoperative plasma suPAR at 2 hours, and preoperative left ventricular ejection fraction (LVEF).
• The nomogram model achieved an AUC of 0.817 (95% CI 0.726-0.907).
• The model demonstrated good calibration and clinical utility.

Conclusions:

• Male sex, advanced age, prolonged operation time, low LVEF, and elevated suPAR are key risk factors for CSA-AKI.
• The developed nomogram model is accurate and clinically valuable for predicting CSA-AKI risk.