Article
Biochemistry & Molecular Biology
Laura Gonzalez-Lafuente, Jose Alberto Navarro-Garcia, Angela Valero-Almazan, Elena Rodriguez-Sanchez, Sara Vazquez-Sanchez, Elisa Mercado-Garcia, Patricia Pineros, Jonay Poveda, Maria Fernandez-Velasco, Makoto Kuro-O, Luis M. Ruilope, Gema Ruiz-Hurtado
Summary: Acute kidney injury (AKI) is associated with an elevated risk of cardiovascular major events and mortality. The presence of AKI and its evolution are significantly associated with an alteration in the anti-aging factor klotho expression. A decrease in klotho expression aggravates cardiac damage after AKI, affecting Ca2+ handling and increasing the risk of Ca2+ pro-arrhythmic events.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemistry & Molecular Biology
Marta Martin-Lorenzo, Angeles Ramos-Barron, Paula Gutierrez-Garcia, Ariadna Martin-Blazquez, Aranzazu Santiago-Hernandez, Emilio Rodrigo Calabia, Carlos Gomez-Alamillo, Gloria Alvarez-Llamas
Summary: This study identified molecular features in preoperative samples that can predict the development of AKI associated with cardiac surgery. Among these features, uKIM-1 and spermidine showed strong predictive value. These findings may be useful in preventing postoperative AKI and improving the prognosis of patients undergoing cardiac surgery.
Article
Pharmacology & Pharmacy
Zhonghui Duan, Minjie Jiang, Xiaojie Huang, Haixia Liu, Hongwei Yu, Qinghua Meng
Summary: Urinary biomarkers can be useful in differentiating between PRA and other types of AKI in patients with hepatitis B cirrhosis. Elevated urinary NGAL can reflect the degree of kidney injury and is an independent risk factor for nonresponse to volume expansion therapy in patients with hepatitis B cirrhosis and AKI.
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Surgery
Rui Fan, Wei Qin, Hao Zhang, Lichun Guan, Wuwei Wang, Jian Li, Wen Chen, Fuhua Huang, Hang Zhang, Xin Chen
Summary: This study established novel prediction models based on early postoperative biomarkers to predict acute kidney injury (AKI) after cardiac surgery. A nomogram model was constructed using logistic regression and the least absolute shrinkage and selection operator. Three tree-based machine learning models were also established: eXtreme Gradient Boosting (XGBoost), random forest (RF), and deep forest (DF). The models achieved good discrimination and calibration.
FRONTIERS IN SURGERY
(2023)
Article
Urology & Nephrology
Chao Xiong, Sheng Shi, Liang Cao, Hongbai Wang, Lijuan Tian, Yuan Jia, Min Zeng, Jianhui Wang
Summary: This study investigated the association between early postoperative serum magnesium and cardiac surgery-associated AKI in adults. The results showed that patients with higher serum magnesium levels had a higher risk of developing postoperative AKI.
Article
Cardiac & Cardiovascular Systems
Jurij Matija Kalisnik, Klemen Steblovnik, Eva Hrovat, Ales Jerin, Milan Skitek, Christian Dinges, Theodor Fischlein, Janez Zibert
Summary: This study found that a combination of NGAL, CysC, and creatinine can enable the early detection of acute kidney injury after cardiac surgery. By measuring the concentrations and sequential changes of these biomarkers, it is possible to predict renal injury in patients more accurately, with a sensitivity of 77% and specificity of 68%.
JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE
(2022)
Article
Cardiac & Cardiovascular Systems
Jurij Matija Kalisnik, Andre Bauer, Ferdinand Aurel Vogt, Franziska Josephine Stickl, Janez Zibert, Matthias Fittkau, Thomas Bertsch, Samuel Kounev, Theodor Fischlein
Summary: This study aimed to use artificial intelligence-based algorithms to improve the early detection of cardiac surgery-associated acute kidney injury. A model called 'Detect-A(K)I' was developed and showed good discriminatory characteristics in detecting acute kidney injury within 12 hours after surgery. The model achieved an area under the curve of 88.0%, sensitivity of 78.0%, specificity of 78.9%, and accuracy of 82.1%. The model incorporated various demographic and clinical variables to improve its performance.
EUROPEAN JOURNAL OF CARDIO-THORACIC SURGERY
(2022)
Article
Medical Laboratory Technology
Laura Gonzalez-Lafuente, Jose Alberto Navarro-Garcia, Elena Rodriguez-Sanchez, Jennifer Aceves-Ripoll, Jonay Poveda, Sara Vazquez-Sanchez, Elisa Mercado-Garcia, Maria Fernandez-Velasco, Makoto Kuro-O, Fernando Liano, Luis M. Ruilope, Gema Ruiz-Hurtado
Summary: Biomarkers of mineral bone disorders and cardiac damage are altered in patients with acute kidney injury (AKI) and may contribute to increased cardiac events and mortality rates. Monitoring these biomarkers could be crucial in predicting and preventing mortality in AKI patients.
TRANSLATIONAL RESEARCH
(2022)
Article
Microbiology
Ying Li, Xinyi Jiang, Jingchun Chen, Yali Hu, Yunpeng Bai, Wang Xu, Linling He, Yirong Wang, Chunbo Chen, Jimei Chen
Summary: This study investigated the potential contributions of gut microbiota alterations in cardiac surgery-associated acute kidney injury (CSA-AKI). The results showed that CSA-AKI patients had different gut microbiota compared to non-CSA-AKI patients, suggesting that dysbiosis of gut microbiota may influence the development of CSA-AKI.
FRONTIERS IN MICROBIOLOGY
(2023)
Article
Cell Biology
Long Zhao, Chenyu Li, Chen Guan, Ning Song, Hong Luan, Congjuan Luo, Wei Jiang, Quandong Bu, Yanfei Wang, Lin Che, Yan Xu
Summary: Studies have shown that in the early stage of acute kidney injury, the expression of SRF is significantly elevated, making it a potential early diagnostic biomarker. Analysis of microarray data related to kidney injury revealed a dramatic increase in SFR in mouse renal tissue 2-4 hours after ischemia/ reperfusion.
Article
Biochemistry & Molecular Biology
Marco Allinovi, Francesco Sessa, Gianluca Villa, Andrea Cocci, Samantha Innocenti, Maria Zanazzi, Lorenzo Tofani, Laura Paparella, Dritan Curi, Calogero Lino Cirami, Riccardo Campi, Andrea Mari, Agostino Ognibene, Maria Lorubbio, Alessandra Fanelli, Stefano Romagnoli, Paola Romagnani, Andrea Minervini
Summary: The study aimed to identify and compare serum and urinary predictors for predicting long-term decline in glomerular filtration rate (GFR) after robotic Nephron-Spearing Surgery (rNSS). The results showed that patients who developed clinical acute kidney injury (AKI) had a more pronounced decline in eGFR at 24 months. KineticGFR at 4 hours and NephroCheck at 10 hours were found to be efficient predictors of post-operative AKI and long-term eGFR decline. Combining these biomarkers could help identify high-risk patients as early as 10 hours after surgery.
Review
Medicine, General & Internal
Christina Massoth, Alexander Zarbock
Summary: Acute kidney injury after cardiac surgery presents specific patterns of damage and recovery, which are crucial for management and outcomes. The KDIGO classification only partially covers the conceptual framework and is insufficient for a comprehensive diagnosis. This review discusses the strengths and limitations of recent criteria for CSA-AKI and provides an overview of biomarkers. The evolving understanding of CSA-AKI as a time-sensitive condition has led to an increased demand for enhancing diagnostic criteria and implementing biomarkers in clinical practice.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Urology & Nephrology
Jonathan G. Amatruda, Michelle M. Estrella, Amit X. Garg, Heather Thiessen-Philbrook, Eric McArthur, Steven G. Coca, Chirag R. Parikh, Michael G. Shlipak
Summary: Preoperative U alpha 1m concentrations may identify patients at high risk of AKI and other adverse events after cardiac surgery, but postoperative U alpha 1m concentrations do not appear to be informative in predicting adverse outcomes.
AMERICAN JOURNAL OF NEPHROLOGY
(2021)
Article
Cardiac & Cardiovascular Systems
Ezzeldin A. Mostafa, Khaled M. Shahin, Ashraf A. H. El Midany, Aly S. Hassaballa, Ismail N. El-Sokkary, Mohamed A. Gamal, Mohamed E. Elsaid, Moustafa G. ElBarbary, Ramy Khorshid, Shady E. Elelwany
Summary: This study evaluated the predictive power of the CSA-NGAL score in stratifying patients with postoperative acute kidney injury (AKI) after cardiac surgery. The results showed that the CSA-NGAL score has high sensitivity, specificity, and positive predictive value. It can be used to improve clinical decision-making and resource allocation for high-risk patients.
HEART LUNG AND CIRCULATION
(2022)
Article
Cardiac & Cardiovascular Systems
Christopher T. Ryan, Zijian Zeng, Subhasis Chatterjee, Matthew J. Wall, Marc R. Moon, Joseph S. Coselli, Todd K. Rosengart, Meng Li, Ravi K. Ghanta
Summary: Machine learning models using electronic medical records can predict the risk of acute kidney injury after cardiac surgery, facilitating risk assessment and interventions postoperatively.
JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY
(2023)