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Atherosclerotic heart disease remains a major cause of morbidity and mortality worldwide. The past few decades have seen the emergence of chronic inflammation as a mediator of atherosclerosis. Although the heart and vascular system remain the organ systems most affected in the atherosclerotic process, chronic inflammation and ischemia trigger a systemic multi-organ response. The liver is a critical organ for systemic hemostasis and recent developments have established an important role of the liver in response to atherosclerosis and myocardial ischemia. In addition, the rapid emergence of systemic liver diseases has unraveled a pathophysiological link with heart disease with therapeutic implications. In this review, we explore the relationship between the liver and the heart in myocardial ischemia, describe epidemiological associations between various liver pathologies and coronary heart disease, and elucidate practical challenges in the clinical management of patients with concomitant coronary heart disease and hepatic abnormalities., Competing Interests: Declaration of Competing Interest The author has no financial or other conflicts of interest to disclose., (Copyright © 2021. Published by Elsevier Inc.)

Background: Electrocardiogram (ECG) differentiation of wide complex tachycardia (WCT) into ventricular tachycardia (VT) and supraventricular tachycardia with aberration (SVT-A) is often challenging., Objective: To determine if the presence of Q-waveforms (QS, Qr, QRs) in the inferior leads (II, III, aVF) can differentiate VT from SVT-A in a WCT compared to Brugada algorithm. We studied 2 inferior lead criteria namely QWC-A where all the inferior leads had a similar Q wave pattern and QWC-B where only lead aVF had a Q-waveform., Methods: A total of 181 consecutive cases of WCT were identified, digitally separated into precordial leads and inferior leads and independently reviewed by 2 electrophysiologists. An electrocardiographic diagnosis of VT or SVT-A was assigned based on Brugada and inferior lead algorithms. Results were compared to the final clinical diagnosis., Results: VT was the final clinical diagnosis in 24.9% of ECG cohort (45/181); 75.1% (136/181) were SVT-A. QWC-A and QWC-B had a high specificity (93.3% and 82.8%) and accuracy (78.2% and 71.0%), but low sensitivity (33.3% and 35.6%) in differentiating VT from SVT-A. The Brugada algorithm yielded a sensitivity of 82.2% and specificity of 68.4%. Area under the curve in ROC analysis was highest with Brugada algorithm (0.75, 95% CI 0.69-0.81) followed by QWC-A (0.63, 95% CI 0.56-0.70) and QWC-B (0.59, 95% CI 0.52-0.67)., Conclusion: QWC-A and QWC-B criteria had poor sensitivity but high specificity in diagnosing VT in patients presenting with WCT. Further research combining this simple criterion with other newer diagnostic algorithms can potentially improve the accuracy of the overall diagnostic algorithm., Competing Interests: Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2020.)

Background: When patients present with pleural effusion and structural abnormalities consistent with malignancy on imaging, the traditional approach has been to perform a thoracentesis and await the results before proceeding to more invasive diagnostic procedures. The objective of this study was to evaluate whether concurrent thoracentesis and tissue biopsy is superior to sequential sampling., Methods: Retrospective chart review was performed for patients who had a pleural cytology from May 2014 until January 2017. Patients without parenchymal, pleural, or mediastinal abnormalities and those with a prior primary thoracic malignancy were excluded. Patients with an effusion and additional suspect findings were grouped based upon whether initial approach was concurrent versus sequential. The following outcomes were documented: lag time to diagnosis from thoracentesis, lag time to hematology/oncology (HONC) service consult, time to molecular study results, lag time to therapy, and time to death., Results: Of 565 cases, 45 met criteria, 28 (62%) having undergone concurrent and 17 (38%) sequential sampling. The median lag time to biopsy for the concurrent group, 3 days, was significantly shorter than the 9-day lag time for the sequential group (P=0.006). Five patients in the sequential group and one in the concurrent group were lost to follow-up. Patients in the concurrent group had earlier diagnosis and oncology visits (2 d, 7 d) than those in the sequential group (6.5 d, 16 d) (P<0.001 and <0.039, respectively). Time from diagnosis to death did not differ for the 2 groups., Conclusion: For patients presenting with pleural effusion accompanied by additional suspect findings, concurrent tissue sampling, and thoracentesis may both reduce loss to follow up and accelerate care.

Atherosclerosis is a chronic inflammatory disease. Pathophysiological similarities between chronic infections and atherosclerosis triggered interest in a clinical association between these conditions. Various infectious microbes have been linked to atherosclerotic vascular disease in epidemiological studies. However, this association failed to satisfy the Koch's postulates of causation with multiple clinical trials demonstrating inefficacy of anti-infective therapies in mitigating atherosclerotic cardiovascular events. Identification of underlying pathophysiological mechanisms and experience with vaccination against various infectious agents has ushered a new avenue of efforts in the development of an anti-atherosclerotic vaccine. Studies in animal models have identified various innate and adaptive immune pathways in atherosclerosis. In this review, we discuss the patho-biological link between chronic infections and atherosclerosis, evaluate existing evidence of animal and human trials on the association between infections and cardiovascular disease and introduce the concept of an anti-atherosclerotic vaccine., (Published by Oxford University Press on behalf of the European Society of Cardiology 2017. This work is written by US Government employees and is in the public domain in the US.)