Subject(s)
Humans , Male , Adult , Sarcoma/surgery , Sarcoma/diagnostic imaging , Heart Atria/physiopathology , Heart Diseases/physiopathology , Heart Neoplasms/diagnostic imaging , Heart Ventricles/physiopathology , Pacemaker, Artificial , Atrial Fibrillation/complications , X-Rays , Bradycardia/complications , Echocardiography/methods , Tomography/methods , Follow-Up Studies , Rare Diseases/rehabilitation , Drug Therapy/trends , Electrocardiography , Heart/physiopathology , Anti-Arrhythmia Agents/pharmacologyABSTRACT
Biomarkers have a variety of clinical applications in multiple stages of diagnosis and therapy. Troponin T and brain natriuretic peptide are the best-known in the cardiovascular field, but experimental studies have identified new biomarkers with potential clinical value. In this article, novel biomarkers of kidney injury are investigated in the context of their relationship with atherosclerotic coronary disease. This review was carried out through a search in the PubMed database using as keywords each biomarker to be studied with the descriptor (DECS/MeSH) "Myocardial Infarction", and the keywords "coronary" and "cardiovascular", using the Boolean operator "AND". After the selection, 24 articles published between 2003 and 2017 were identified for the review. Eight biomarkers were investigated: neutrophil gelatinase-associated lipocalin (NGAL), fibroblast growth factor 23 (FGF23), tissue inhibitor of metalloproteinase-2 (TIMP-2), syndecan-1, interleukin-6 (IL-6), galectin-3, and the vascular cell adhesion molecules ICAM-1 and VCAM-1. Most identified articles were experimental studies, studies on human subjects having few participants. There are several promising biomarkers in the setting of coronary disease. The main evidence available in the literature suggests that elevated NGAL levels are associated with better prognosis after cardiac arrest and with comorbid kidney injury; elevated FGF23 is associated with coronary artery disease severity; TIMP-2 protects against coronary artery disease; increased expression of syndecan-1 is observed in myocardial infarction (MI) and protects against an exacerbated inflammatory response; IL-6 is associated with atherosclerotic disease and major cardiovascular outcomes; galectin-3 correlates with adverse clinical events post-MI; and elevated ICAM-1/VCAM-1 levels are associated with risk of coronary disease. Further studies are required to better investigate the role of each of these biomarkers in both stable coronary disease and acute coronary syndrome.
Subject(s)
Atherosclerosis , Coronary Artery Disease , Biomarkers , Coronary Artery Disease/diagnosis , Fibroblast Growth Factor-23 , Humans , Prognosis , Tissue Inhibitor of Metalloproteinase-2ABSTRACT
BACKGROUND: It has been recently mathematically demonstrated that the percentage increase in serum creatinine (SCr) can delay acute kidney injury (AKI) diagnosis in patients with previous chronic kidney disease (CKD). Based on creatinine (Cr) kinetics, it was suggested a new AKI classification using absolute increase in SCr elevation over specified time periods. However, this classification has not been evaluated in clinical studies. METHODS: A prospective cohort study evaluated myocardial infarction patients during the first 7 days of hospital stay with daily SCr measurements. They were classified using Kidney Disease Improving Global Outcomes (KDIGO) and Cr kinetics systems. Both classifications were compared by net reclassification improvement (NRI) and area under the receiver operator characteristic (AuROC) curve regarding hospital mortality. RESULTS: A total of 584 patients were included, of which 34.1% had previous CKD. Patients had more AKI by KDIGO than by Cr kinetics criteria (25.7 versus 18.0%, P < 0.001) and 81 patients (13.9%) had different AKI severity classification. Patients with AKI by KDIGO criteria and non-AKI by Cr kinetics had higher hospital mortality rates than patients with non-AKI using both classifications [adjusted mortality odds ratios (ORs): 4.753; 95% confidence interval (CI): 1.119-9.023, P = 0.014]. In patients with previous CKD, NRI analysis was 6.2% favoring Cr kinetics criteria. However, there was no difference using the AuROC curve analysis. In patients with no previous CKD, NRI analysis was 33.0%, favoring KDIGO, and this was in accordance with a better AuROC curve (0.828 versus 0.664, P < 0.05). CONCLUSIONS: AKI classification proposed by a Cr kinetics model can be superior when diagnosing patients with previous CKD. However, KDIGO had a better performance in patients with no previous CKD.
