COVID-19 Clinical Trials: A Primer for the Cardiovascular and Cardio-Oncology Communities

COVID-19's immuno-pathology and cardiovascular diseases

The pandemic of COVID-19 in worldwide causes recent millions of morbidity and mortality in all countries and is the most important challenge in the world in recent years. Coronavirus is a single-stranded RNA virus and infection with COVID-19 leads to acute respiratory distress syndrome, lung inflammation, cytokine storm, and death. The other complications include endothelial dysfunction, activation of coagulation, thromboembolic events, and vascular disease. Cardiovascular complications such as myocardial and stroke ischemia, pulmonary thromboembolism, systemic arterial, and deep vein thrombosis were reported. In this review, we presented immuno-pathological mechanisms and the effects of COVID-19 on the cardiovascular system, heart, vessels, coagulation system, and molecular glance of immuno-inflammation to the COVID-19's pathology on the cardiovascular system.

Comparative analysis of some selected generative adversarial network models for image augmentation: a case study of COVID-19 x-ray and CT images

One of the fastest-growing fields in today’s world is data analytics. Data analytics paved the way for a significant number of research and development in various fields including medicine and vaccine development, DNA analysis, artificial intelligence and many more. Data plays a very important role in providing the required results and helps in making critical decisions and predictions. However, ethical and legislative restrictions sometimes make it difficult for scientists to acquire data. For example, during the COVID-19 pandemic, data was very limited due to privacy and regulatory issues. To address data unavailability, data scientists usually leverage machine learning algorithms such as Generative Adversarial Networks (GAN) to augment data from existing samples. Today, there are over 450 algorithms that are designed to re-generate or augment data in case of unavailability of the data. With many algorithms in the market, it is practically impossible to predict which algorithm best fits the problem in question, unless many algorithms are tested. In this study, we select the most common types of GAN algorithms available for image augmentation to generate samples capable of representing a whole data distribution. To test the selected models, we used two unique datasets, namely COVID-19 CT images and COVID-19 X-Ray images. Five different GAN algorithms, namely CGAN, DCGAN, f-GAN, WGAN, and CycleGAN, were selected and applied to the samples to see how each algorithm reacts to the samples. To evaluate their performances, Visual Turing Test (VTT) and Fréchet Inception Distance (FID) were used. The VTT result shows that a human expert can accurately distinguish between different samples that were produced. Hence, CycleGAN scored 80% in CT image dataset and 77% in X-Ray image dataset. In contrast, the FID result revealed that CycleGAN had a high convergence and therefore generated high quality and clearer images on both datasets compared to CGAN, DCGAN, f-GAN, and WGAN. This study concluded that the CycleGAN model is the best when it comes to image augmentation due to its friendliness and high convergence.

COVID-19 and the Heart: Could Transient Takotsubo Cardiomyopathy Be Related to the Pandemic by Incidence and Mechanisms?

Typical emergency hospital care during the COVID-19 pandemic has centered on pulmonary-focused services. Nonetheless, patients with COVID-19 frequently develop complications associated with the dysfunction of other organs, which may greatly affect prognosis. Preliminary evidence suggests that cardiovascular involvement is relatively frequent in COVID-19 and that it correlates with significant worsening of clinical status and mortality in infected patients. In this article, we summarize current knowledge on the cardiovascular effects of COVID-19. In particular, we focus on the association between COVID-19 and transient takotsubo cardiomyopathy (TTC)—two conditions that preliminarily seem epidemiologically associated—and we highlight cardiovascular changes that may help guide future investigations toward full discovery of this new, complex disease entity. We hypothesize that coronary endothelial dysfunction, along with septic state, inflammatory storm, hypercoagulability, endothelial necrosis, and small-vessel clotting, may represent a fundamental hidden link between COVID-19 and TTC. Furthermore, given the likelihood that new genetic mutations of coronaviruses or other organisms will cause similar pandemics and endemics in the future, we must be better prepared so that a substantial complication such as TTC can be more accurately recognized, its pathophysiology better understood, and its treatment made more justifiable, timely, and effective.

Computational identification of repurposed drugs against viruses causing epidemics and pandemics via drug-target network analysis

Viral epidemics and pandemics are considered public health emergencies. However, traditional and novel antiviral discovery approaches are unable to mitigate them in a timely manner. Notably, drug repurposing emerged as an alternative strategy to provide antiviral solutions in a timely and cost-effective manner. In the literature, many FDA-approved drugs have been repurposed to inhibit viruses, while a few among them have also entered clinical trials. Using experimental data, we identified repurposed drugs against 14 viruses responsible for causing epidemics and pandemics such as SARS-CoV-2, SARS, Middle East respiratory syndrome, influenza H1N1, Ebola, Zika, Nipah, chikungunya, and others. We developed a novel computational “drug-target-drug” approach that uses the drug-targets extracted for specific drugs, which are experimentally validated in vitro or in vivo for antiviral activity. Furthermore, these extracted drug-targets were used to fetch the novel FDA-approved drugs for each virus and prioritize them by calculating their confidence scores. Pathway analysis showed that the majority of the extracted targets are involved in cancer and signaling pathways. For SARS-CoV-2, our method identified 21 potential repurposed drugs, of which 7 (e.g., baricitinib, ramipril, chlorpromazine, enalaprilat, etc.) have already entered clinical trials. The prioritized drug candidates were further validated using a molecular docking approach. Therefore, we anticipate success during the experimental validation of our predicted FDA-approved repurposed drugs against 14 viruses. This study will assist the scientific community in hastening research aimed at the development of antiviral therapeutics.

COVID-19 from the interdisciplinary standpoint. Round table

On February 25, 2021, an expert round table was held, which considered the problem of interdisciplinary discussion of a coronavirus disease 2019 (COVID-19) and the development of joint actions for management of patients with chronic noncommunicable diseases during a pandemic.

Host Diversity and Potential Transmission Pathways of SARS-CoV-2 at the Human-Animal Interface

Emerging infectious diseases present great risks to public health. The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing coronavirus disease 2019 (COVID-19), has become an urgent public health issue of global concern. It is speculated that the virus first emerged through a zoonotic spillover. Basic research studies have suggested that bats are likely the ancestral reservoir host. Nonetheless, the evolutionary history and host susceptibility of SARS-CoV-2 remains unclear as a multitude of animals has been proposed as potential intermediate or dead-end hosts. SARS-CoV-2 has been isolated from domestic animals, both companion and livestock, as well as in captive wildlife that were in close contact with human COVID-19 cases. Currently, domestic mink is the only known animal that is susceptible to a natural infection, develop severe illness, and can also transmit SARS-CoV-2 to other minks and humans. To improve foundational knowledge of SARS-CoV-2, we are conducting a synthesis review of its host diversity and transmission pathways. To mitigate this COVID-19 pandemic, we strongly advocate for a systems-oriented scientific approach that comprehensively evaluates the transmission of SARS-CoV-2 at the human and animal interface.

A virtual-hybrid approach to launching a cardio-oncology clinic during a pandemic

BACKGROUND

As cardiovascular disease is a leading cause of death in cancer survivors, the new subspecialty of Cardio-Oncology has emerged to address prevention, monitoring, and management of cardiovascular toxicities to cancer therapies. During the coronavirus disease of 2019 (COVID-19) pandemic, we developed a Virtual-Hybrid Approach to build a de novo Cardio-Oncology Clinic.

METHODS

We conceptualized a Virtual-Hybrid Approach including three arms: information seeking in locations with existing Cardio-Oncology clinics, information gathering at the location for a new clinic, and information sharing to report clinic-building outcomes. A retrospective review of outcomes included collection and synthesis of data from our first 3 months (at pandemic peak) on types of appointments, cancers, drugs, and cardiotoxicities. Data were presented using descriptive statistics.

RESULTS

A de-novo Cardio-Oncology clinic was developed structured from the ground up to integrate virtual and in-person care in a hybrid and innovative model, using the three arms of the Virtual-Hybrid Approach. First, we garnered in-person and virtual preparation through hands-on experiences, training, and discussions in existing Cardio-Oncology Clinics and conferences. Next, we gleaned information through virtual inquiry and niche-building. With partners throughout the institution, a virtual referral process was established for outpatient referrals and inpatient e-consult referrals to actualize a hybrid care spectrum for our patients administered by a multidisciplinary hybrid care team of clinicians, ancillary support staff, and clinical pharmacists. Among the multi-subspecialty clinic sessions, approximately 50% were in Cardio-Oncology, 20% in Preventive Cardiology, and 30% in General Cardiology. In the hybrid model, the Heart & Vascular Center had started to re-open, allowing for 65% of our visits to be in person. In additional analyses, the most frequent cardiovascular diagnosis was cardiomyopathy (34%), the most common cancer drug leading to referral was trastuzumab (29%), and the most prevalent cancer type was breast cancer (42%).

CONCLUSION

This Virtual-Hybrid Approach and retrospective review provides guidance and information regarding initiating a brand-new Cardio-Oncology Clinic during the pandemic for cancer patients/survivors. This report also furnishes virtual resources for patients, virtual tools for oncologists, cardiologists, and administrators tasked with starting new clinics during the pandemic, and innovative future directions for this digital pandemic to post-pandemic era.

An unexplained death after routine cardiac surgery: how long have we dealt with coronavirus disease 2019?

We present a case report of fatal respiratory failure after cardiac surgery in the early stages of the coronavirus disease 2019 outbreak. Although not supported by epidemiological data nor clinical course, coronavirus disease 2019 infection was revealed post-mortem by immunohistochemical detection of the severe acute respiratory syndrome coronavirus 2 spike protein in lung tissue.