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Updated: Aug 23, 2025

A Large Animal Model for Acute Kidney Injury by Temporary Bilateral Renal Artery Occlusion
Published on: February 2, 2021
The multifactorial dynamic perfusion index: A predictive tool of cardiac surgery associated acute kidney injury
Marco Ranucci1, Umberto Di Dedda1, Mauro Cotza1
1Department of Cardiovascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, Milan, Italy.
Insights
A new model integrating dynamic cardiopulmonary bypass (CPB) data significantly improves prediction of cardiac surgery-associated acute kidney injury (CSA-AKI). This multifactorial dynamic perfusion index (MDPI) offers better predictive ability than static risk models for CSA-AKI.
Area of Science:
- Nephrology
- Cardiology
- Critical Care Medicine
Background:
- Cardiac surgery-associated acute kidney injury (CSA-AKI) is a significant complication.
- Preoperative and intraoperative factors contribute to CSA-AKI, but cardiopulmonary bypass (CPB) factors require further elucidation in a unified model.
Purpose of the Study:
- To develop a dynamic predictive model for CSA-AKI.
- To assess the predictive performance of a novel multifactorial dynamic perfusion index (MDPI) compared to existing static risk models.
Main Methods:
- Retrospective analysis of 910 adult cardiac surgery patients.
- Development of a static risk model (SRM) using baseline data.
- Creation of a dynamic perfusion risk (DPR) model incorporating CPB-related data (duration, oxygen delivery, mean arterial pressure, lactate, transfusion).
- Integration of SRM and DPR into the MDPI model.
- Assessment of model discrimination and calibration using AUC.
Main Results:
- The static risk model (SRM) had an AUC of 0.696.
- The dynamic perfusion risk (DPR) model showed an improved AUC of 0.723.
- The multifactorial dynamic perfusion index (MDPI) achieved the highest AUC of 0.769, significantly outperforming both SRM and DPR.
- MDPI demonstrated superior discrimination and calibration compared to static models.
Conclusions:
- Incorporating dynamic CPB indices enhances the predictive accuracy of preoperative risk scores for CSA-AKI.
- The MDPI model offers superior predictive ability over existing static risk models.
- MDPI is a promising tool for advanced goal-directed perfusion strategies in cardiac surgery.
Introduction:
cardiac surgery associated acute kidney injury (CSA-AKI) has a number of preoperative and intraoperative risk factors. Cardiopulmonary bypass (CPB) factors have not yet been elucidated in a single multivariate model. The aim of this study is to develop a dynamic predictive model for CSA-AKI.
Methods:
retrospective study on 910 consecutive adult cardiac surgery patients. Baseline data were used to settle a preoperative CSA-AKI risk model (static risk model, SRM); CPB related data were assessed for association with CSA-AKI. CPB duration, nadir oxygen delivery, time of exposure to a low oxygen delivery, nadir mean arterial pressure, peak lactates and red blood cell transfusion were included in a multivariate dynamic perfusion risk (DPR). SRM and DPR were merged into a final logistic regression model (multifactorial dynamic perfusion index, MDPI). The three risk models were assessed for discrimination and calibration.
Results:
the SRM model had an AUC of 0.696 (95% CI 0.663-0.727), the DPR model of 0.723 (95% CI 0.691-0.753), and the MDPI model an AUC of 0.769 (95% CI 0.739-0.798). The difference in AUC between SRM and DPR was not significant (p = 0.495) whereas the AUC of MDPI was significantly larger than that of SRM (p = 0.004) and DPR (p = 0.015).
Conclusions:
inclusion of dynamic indices of the quality of CPB improves the discrimination and calibration of the preoperative risk scores. The MDPI has better predictive ability than the existing static risk models and is a promising tool to integrate different factors into an advanced concept of goal-directed perfusion.
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