cardiac surgery
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2022 ◽  
Vol 77 ◽  
pp. 110596
Teresa Pérez ◽  
Angel M. Candela-Toha ◽  
Loubna Khalifi ◽  
Alfonso Muriel ◽  
M. Carmen Pardo

2022 ◽  
Vol 272 ◽  
pp. 166-174
Lauren V Huckaby ◽  
Laura M Seese ◽  
Nicholas Hess ◽  
Edgar Aranda-Michel ◽  
Ibrahim Sultan ◽  

2022 ◽  
Vol 23 (2) ◽  
pp. 84-86
Marco Pocar ◽  
Pasquale Totaro ◽  
Mauro Rinaldi ◽  
Stefano Pelenghi

2022 ◽  
Vol 76 ◽  
pp. 110583
Alexander Fuchs ◽  
Paul Philipp Heinisch ◽  
Markus M. Luedi ◽  
Catherine S. Reid

2022 ◽  
Vol 17 (1) ◽  
Zrinka Požgain ◽  
Grgur Dulić ◽  
Goran Kondža ◽  
Siniša Bogović ◽  
Ivan Šerić ◽  

Abstract Background Postoperative cognitive decline following cardiac surgery is one of the frequently reported complications affecting postoperative outcome, characterized by impairment of memory or concentration. The aetiology is considered multifactorial and the research conducted so far has presented contradictory results. The proposed mechanisms to explain the cognitive decline associated with cardiac surgery include the neurotoxic accumulation of β-amyloid (Aβ) proteins similar to Alzheimer's disease. The comparison of coronary artery bypass grafting procedures concerning postoperative cognitive decline and plasmatic Aβ1-42 concentrations has not yet been conducted. Methods The research was designed as a controlled clinical study of patients with coronary artery disease undergoing surgical myocardial revascularization with or without the use of a cardiopulmonary bypass machine. All patients completed a battery of neuropsychological tests and plasmatic Aβ1-42 concentrations were collected. Results The neuropsychological test results postoperatively were significantly worse in the cardiopulmonary bypass group and the patients had larger shifts in the Aβ1-42 preoperative and postoperative values than the group in which off-pump coronary artery bypass was performed. Conclusions The conducted research confirmed the earlier suspected association of plasmatic Aβ1-42 concentration to postoperative cognitive decline and the results further showed that there were less changes and lower concentrations in the off-pump coronary artery bypass group, which correlated to less neurocognitive decline. There is a lot of clinical contribution acquired by this research, not only in everyday decision making and using amyloid proteins as biomarkers, but also in the development and application of non-pharmacological and pharmacological neuroprotective strategies.

2022 ◽  
Vol 8 ◽  
Yichi Zhang ◽  
Haige Zhao ◽  
Qun Su ◽  
Cuili Wang ◽  
Hongjun Chen ◽  

Introduction:Acute kidney injury (AKI) after cardiac surgery is independently associated with a prolonged hospital stay, increased cost of care, and increased post-operative mortality. Delayed elevation of serum creatinine (SCr) levels requires novel biomarkers to provide a prediction of AKI after cardiac surgery. Our objective was to find a novel blood biomarkers combination to construct a model for predicting AKI after cardiac surgery and risk stratification.Methods:This was a case-control study. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to Gene Expression Omnibus (GEO) dataset GSE30718 to seek potential biomarkers associated with AKI. We measured biomarker levels in venous blood samples of 67 patients with AKI after cardiac surgery and 59 control patients in two cohorts. Clinical data were collected. We developed a multi-biomarker model for predicting cardiac-surgery-associated AKI and compared it with a traditional clinical-factor-based model.Results:From bioinformatics analysis and previous articles, we found 6 potential plasma biomarkers for the prediction of AKI. Among them, 3 biomarkers, such as growth differentiation factor 15 (GDF15), soluble suppression of tumorigenicity 2 (ST2, IL1RL1), and soluble urokinase plasminogen activator receptor (uPAR) were found to have prediction ability for AKI (area under the curve [AUC] > 0.6) in patients undergoing cardiac surgery. They were then incorporated into a multi-biomarker model for predicting AKI (C-statistic: 0.84, Brier 0.15) which outperformed the traditional clinical-factor-based model (C-statistic: 0.73, Brier 0.16).Conclusion:Our research validated a promising plasma multi-biomarker model for predicting AKI after cardiac surgery.

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