Activation of the renin-angiotensin-aldosterone system is associated with Acute Kidney Injury in COVID-19

Dudoignon, Emmanuel; Moreno, Nabila; Deniau, Benjamin; Coutrot, Maxime; Longer, Romain; Amiot, Quentin; Mebazaa, Alexandre; Pirracchio, Romain; Dépret, François; Legrand, Matthieu

doi:10.1016/j.accpm.2020.06.006

Cited by 41 publications

(46 citation statements)

References 7 publications

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“…Specifically, COVID-19-associated ARDS is often treated by increasing positive end-expiratory pressure (PEEP), which leads to increased intrathoracic pressure and can ultimately result in increased renal venous pressure and reduced filtration, which may be further amplified if intra-abdominal pressure is elevated (for example, with fluid overload) 51 . In addition, all forms of positive pressure ventilation can increase sympathetic tone, leading to secondary activation of the renin–angiotensin system 52 , 53 . In the setting of ARDS after shock resolution, patients are often managed with a restrictive fluid strategy.…”

Section: Pathophysiology and Effects Of Treatmentmentioning

confidence: 99%

COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup

et al. 2020

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Kidney involvement in patients with coronavirus disease 2019 (COVID-19) is common, and can range from the presence of proteinuria and haematuria to acute kidney injury (AKI) requiring renal replacement therapy (RRT; also known as kidney replacement therapy). COVID-19-associated AKI (COVID-19 AKI) is associated with high mortality and serves as an independent risk factor for all-cause in-hospital death in patients with COVID-19. The pathophysiology and mechanisms of AKI in patients with COVID-19 have not been fully elucidated and seem to be multifactorial, in keeping with the pathophysiology of AKI in other patients who are critically ill. Little is known about the prevention and management of COVID-19 AKI. The emergence of regional ‘surges’ in COVID-19 cases can limit hospital resources, including dialysis availability and supplies; thus, careful daily assessment of available resources is needed. In this Consensus Statement, the Acute Disease Quality Initiative provides recommendations for the diagnosis, prevention and management of COVID-19 AKI based on current literature. We also make recommendations for areas of future research, which are aimed at improving understanding of the underlying processes and improving outcomes for patients with COVID-19 AKI.

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Section: Pathophysiology and Effects Of Treatmentmentioning

confidence: 99%

COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup

et al. 2020

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“…SARS-CoV2 has been suggested to modulate the renin-angiotensin-aldosterone system (RAAS). Evidence of activation of the RAAS in patients with COVID-19 who have acute kidney injury, leading to increased sCr, has been reported [ 40 ]. Several studies have also reported that liver damage occurred in severe cases of COVID-19 infection at rates ranging from 58% to 78% [ 41 , 42 ].…”

Section: Discussionmentioning

confidence: 99%

Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation

Pan¹,

Li²,

Xiao³

et al. 2020

J Med Internet Res

111

106

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Background Patients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and methods to assess patients’ prognosis early and administer precise treatment are of great significance. Objective The aim of this study was to use machine learning to construct a model for the analysis of risk factors and prediction of mortality among ICU patients with COVID-19. Methods In this study, 123 patients with COVID-19 in the ICU of Vulcan Hill Hospital were retrospectively selected from the database, and the data were randomly divided into a training data set (n=98) and test data set (n=25) with a 4:1 ratio. Significance tests, correlation analysis, and factor analysis were used to screen 100 potential risk factors individually. Conventional logistic regression methods and four machine learning algorithms were used to construct the risk prediction model for the prognosis of patients with COVID-19 in the ICU. The performance of these machine learning models was measured by the area under the receiver operating characteristic curve (AUC). Interpretation and evaluation of the risk prediction model were performed using calibration curves, SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), etc, to ensure its stability and reliability. The outcome was based on the ICU deaths recorded from the database. Results Layer-by-layer screening of 100 potential risk factors finally revealed 8 important risk factors that were included in the risk prediction model: lymphocyte percentage, prothrombin time, lactate dehydrogenase, total bilirubin, eosinophil percentage, creatinine, neutrophil percentage, and albumin level. Finally, an eXtreme Gradient Boosting (XGBoost) model established with the 8 important risk factors showed the best recognition ability in the training set of 5-fold cross validation (AUC=0.86) and the verification queue (AUC=0.92). The calibration curve showed that the risk predicted by the model was in good agreement with the actual risk. In addition, using the SHAP and LIME algorithms, feature interpretation and sample prediction interpretation algorithms of the XGBoost black box model were implemented. Additionally, the model was translated into a web-based risk calculator that is freely available for public usage. Conclusions The 8-factor XGBoost model predicts risk of death in ICU patients with COVID-19 well; it initially demonstrates stability and can be used effectively to predict COVID-19 prognosis in ICU patients.

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“…As a result of the viral tropism to the kidneys, acute renal injury was found to be the second most observed COVID-19 complication in the USA (22.2%) [ 77 ] and China (25.2%) [ 67 ]. Thus, there is compelling evidences that patients with acute kidney injury at admission exhibit activation of RAAS, as documented by higher plasmatic renin and aldosterone levels and lower urinary sodium levels in patients with acute kidney injury [ 109 ], as well as the association of plasmatic aldosterone and C-reactive protein levels and COVID-19 severity [ 110 ]. Since hypokalaemia was found to be prevalent in patients with COVID-19 pneumonia (~ 30%) and is an indicator of RAAS activity, it was suggested that hypokalaemia could be used as a surrogate marker of COVID-19 progression and an independent risk factor for invasive mechanical ventilation requirement [ 111 ].…”

Section: Comorbidities and Ace/ace2 Balance Disruptionmentioning

confidence: 99%

COVID-19: angiotensin-converting enzyme 2 (ACE2) expression and tissue susceptibility to SARS-CoV-2 infection

Beyerstedt

Casaro

Rangel

2021

Eur J Clin Microbiol Infect Dis

596

481

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Activation of the renin-angiotensin-aldosterone system is associated with Acute Kidney Injury in COVID-19

Cited by 41 publications

References 7 publications

COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup

COVID-19-associated acute kidney injury: consensus report of the 25th Acute Disease Quality Initiative (ADQI) Workgroup

Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation

COVID-19: angiotensin-converting enzyme 2 (ACE2) expression and tissue susceptibility to SARS-CoV-2 infection

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