Dear Editor,
Acute kidney injury (AKI) remains a common and significant complication in critically ill patients. As no curative treatment exists, prevention of AKI is paramount, especially in high-risk patients. Several randomized controlled trials suggest that a biomarker-guided implementation of the Kidney Disease Improving Global Outcomes (KDIGO) care bundle reduces the incidence of AKI postoperatively [1–3]. Implementation of this care bundle is recommended in high-risk patients after cardiac surgery [4]. This comprises regular monitoring of kidney function, hemodynamic optimization, and consideration of advanced hemodynamic monitoring, as well as avoidance of hyperglycemia, nephrotoxic drugs, and radiocontrast agents, if possible.
So far, the impact of each individual component of the bundle is unclear. Better understanding would enable prioritization, resource-allocation and clinical management of those at high risk of AKI. To investigate the treatment effects of individual bundle components, we combined data of the two PrevAKI-trials including 554 cardiac surgery patients at high risk for AKI, as defined by elevated urinary biomarkers TIMP2*IGFBP7 [1, 2]. Patients were randomized to standard care versus implementation of the care bundle (Supplementary S1).
Univariate logistic regression of the bundle’s components was performed as a risk factor analysis of the whole cohort. Following this, individual treatment effects were analyzed, using the same method for the intervention group only (Fig. 1a). Hypotension, low cardiac index (CI), and use of radiocontrast agents significantly increased the risk for AKI. Optimizing the hemodynamic situation (avoiding hypotension and a low cardiac output state) and avoidance of nephrotoxic drugs were the most important measures to prevent AKI (Fig. 1a). Based on these results, we investigated the role of hemodynamic optimization. AKI occurred significantly less frequently, when hypotension and low CI were prevented (Fig. 1b), particularly for severe stages of AKI.
Fig. 1.
a Univariate, binary logistic regression analysis for development of any AKI. ACEi angiotensin-converting enzyme inhibitors, ARBs angiotensin receptor blockers, OR odds ratio, MAP median arterial pressure, CI cardiac index. Hypotension: MAP < 60 mmHg on one reading or MAP < 65 mmHg on two readings during the intervention period. Hyperglycemia defined as: blood glucose levels ≥ 150 mg/dl longer than three hours during intervention period. b Hemodynamic status and AKI incidence. (gray = high MAP and/or CI; red = low MAP and/or CI). c Treatment effects of hemodynamic optimization for AKI prevention
Testing the effect of hemodynamic optimization, further analyses demonstrated the effect of hemodynamic optimization between the first and the consecutive hemodynamic measurement (Fig. 1c). Patients with hypotension at presentation had statistically lower rates of AKI when successfully optimized until the next measurement, compared to patients in which median arterial pressure optimization could not be achieved. AKI rates were lowest in patients in which hypotension was avoided entirely. Differences of AKI rates in patients with successful optimization of cardiac index were not statistically significant.
In conclusion, our findings demonstrate the importance of maintaining adequate systemic blood pressure and cardiac output. If hypotension or low cardiac output occurs, timely hemodynamic optimization should be performed to prevent AKI. Whilst our analyses suggested a possible role for radiocontrast agents and nephrotoxic drugs, these factors had wide confidence intervals, indicating low certainty of these findings. Besides hemodynamic optimization, other bundle components had little or no impact on the bundle’s overall effectiveness.
For patients at risk for AKI, we recommend avoiding even short periods of hypotension [5]. Finally, we suggest that improvement of cardiac index using inotropes, may be a key, yet all too often ignored, aspect of AKI prevention.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We would like to thank Mr Jannik Feld, MSc, Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany and Dr. rer. nat. Joachim Gerß, Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany, for their statistical advice. Furthermore, we thank all PrevAKI-investigators for their contribution, namely Christoph Schmidt, Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany. Andreas Hoffmeier, Department of Cardiac Surgery, University of Münster, Münster, Germany. Hugo van Aken, Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany. Carola Wempe, Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany. Mira Küllmar, Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany. Gianluca Lucchese, Department of Critical Care & Nephrology, King’s College London, Guy’s & St Thomas' Hospital, London, SE1 7EH, UK. Kamran Baig, Department of Critical Care & Nephrology, King's College London, Guy's & St Thomas' Hospital, London, SE1 7EH, UK. Armando Cennamo, Department of Critical Care & Nephrology, King’s College London, Guy’s & St Thomas’ Hospital, London, SE1 7EH, UK. Ronak Rajani, Department of Critical Care & Nephrology, King's College London, Guy's & St Thomas' Hospital, London, SE1 7EH, UK. Stuart McCorkell, Department of Critical Care & Nephrology, King's College London, Guy's & St Thomas' Hospital, London, SE1 7EH, UK. Christian Arndt, Department of Anaesthesiology and Intensive Care Medicine, University Hospital Marburg, Marburg, Germany. Hinnerk Wulf, Department of Anaesthesiology and Intensive Care Medicine, University Hospital Marburg, Marburg, Germany. Marc Irqsusi, Department of Cardiovascular Surgery, Philipps University of Marburg, Marburg, Germany. Fabrizio Monaco, Department of Anesthesia and Intensive Care, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy. Ambra Licia Di Prima, Department of Anesthesia and Intensive Care, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy. Mercedes García Alvarez, Department of Anesthesiology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. Stefano Italiano, Department of Anesthesiology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. Jordi Miralles Bagan, Department of Anesthesiology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain. Gudrun Kunst, Department of Anesthetics, King's College Hospital, Denmark Hill, London, United Kingdom. Shrijit Nair, Department of Anesthetics, King's College Hospital, Denmark Hill, London, United Kingdom. Camilla L’Acqua, Department of Anesthesia and Critical Care, Centro Cardiologico Monzino Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy. Eric Hoste, Department of Intensive Care Medicine, University Hospital Gent, Gent, Belgium. Wim Vandenberghe, Department of Intensive Care Medicine, University Hospital Gent, Gent, Belgium. Patrick M. Honore, Department of Intensive Care, CHU Brugmann University Hospital, Brussels, Belgium. John A. Kellum, Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania. Philippe Grieshaber, Department of Cardiac Surgery, University Hospital Giessen, Giessen, Germany. Christina Massoth, Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany. Raphael Weiss, Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany.
Author contributions
TCVG, MMD and AZ conceived and designed the study and drafted the manuscript. TVCG performed the data retrieval. TVCG, MMD and AZ performed the statistical analysis. TVCG, MMD, MO, LGF and AZ were involved in the interpretation of the data, and made critical revisions to the manuscript. All authors read and approved the final version of the manuscript to be published.
Funding
Open Access funding enabled and organized by Projekt DEAL. The trials were supported by the German Research Foundation (KFO342-1, ZA428/18-1 and ZA428/21-1) to Professor Alexander Zarbock.
Declarations
Conflict of interest
TCVG and MO declared no conflict of interest. AZ reported receiving research grants from Baxter, Fresenius, Astute Medical, and Astellas and receiving personal fees from Fresenius, AM Pharma and Biomerieux. MM reported receiving personal fees from Astute Medical, FMC, and Baxter. LGF declared research support and personal fees from Astute Medical, La Jolla Pharmaceuticals, Medibeacon, Baxter, and Fresenius.
Ethical approval
Not required.
Footnotes
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Contributor Information
Alexander Zarbock, Email: zarbock@uni-muenster.de.
the PrevAKI Investigators:
Christoph Schmidt, Andreas Hoffmeier, Hugo Aken, Carola Wempe, Mira Küllmar, Gianluca Lucchese, Kamran Baig, Armando Cennamo, Ronak Rajani, Stuart McCorkell, Christian Arndt, Hinnerk Wulf, Marc Irqsusi, Fabrizio Monaco, Ambra Licia Di Prima, Mercedes García Alvarez, Stefano Italiano, Jordi Miralles Bagan, Gudrun Kunst, Shrijit Nair, Camilla L’Acqua, Eric Hoste, Wim Vandenberghe, Patrick M Honore, John A Kellum, Philippe Grieshaber, Christina Massoth, and Raphael Weis
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