COVID-19 and the Digitalisation of Cardiovascular Training and Education—A Review of Guiding Themes for Equitable and Effective Post-graduate Telelearning

The coronavirus disease-2019 (COVID-19) pandemic has had an unprecedented impact leading to novel adaptations in post-graduate medical education for cardiovascular and general internal medicine. Whilst the results of initial community COVID-19 vaccination are awaited, continuation of multimodality teaching and training that incorporates telelearning will have enduring benefit to post-graduate education and will place educational establishments in good stead to nimbly respond in future pandemic-related public health emergencies. With the rise in innovative virtual learning solutions, medical educators will have to leverage technology to develop electronic educational materials and virtual courses that facilitate adult learning. Technology-enabled virtual learning is thus a timely progression of hybrid classroom initiatives that are already adopted to varying degrees, with a need for faculty to serve as subject matter experts, to host and moderate online discussions, and to provide feedback and overall mentorship. As an extension from existing efforts, simulation-based teaching (SBT) and learning and the use of mixed reality technology should also form a greater core in the cardiovascular medicine curriculum. We highlight five foundational themes for building a successful e-learning model in cardiovascular and general post-graduate medical training: (1) digital solutions and associated infrastructure; (2) equity in access; (3) participant engagement; (4) diversity and inclusion; and (5) patient confidentiality and governance framework. With digitalisation impacting our everyday lives and now how we teach and train in medicine, these five guiding principles provide a cognitive scaffold for careful consideration of the required ecosystem in which cardiovascular and general post-graduate medical education can effectively operate. With due consideration of various e-learning options and associated infrastructure needs; and adoption of strategies for participant engagement under sound and just governance, virtual training in medicine can be effective, inclusive and equitable through the COVID-19 era and beyond

The Pathogenesis and Long-Term Consequences of COVID-19 Cardiac Injury.

The mechanisms of coronavirus disease-2019 (COVID-19)-related myocardial injury comprise both direct viral invasion and indirect (hypercoagulability and immune-mediated) cellular injuries. Some patients with COVID-19 cardiac involvement have poor clinical outcomes, with preliminary data suggesting long-term structural and functional changes. These include persistent myocardial fibrosis, edema, and intraventricular thrombi with embolic events, while functionally, the left ventricle is enlarged, with a reduced ejection fraction and new-onset arrhythmias reported in a number of patients. Myocarditis post-COVID-19 vaccination is rare but more common among young male patients. Larger studies, including prospective data from biobanks, will be useful in expanding these early findings and determining their validity

The Pathogenesis and Long-Term Consequences of COVID-19 Cardiac Injury.

The mechanisms of coronavirus disease-2019 (COVID-19)-related myocardial injury comprise both direct viral invasion and indirect (hypercoagulability and immune-mediated) cellular injuries. Some patients with COVID-19 cardiac involvement have poor clinical outcomes, with preliminary data suggesting long-term structural and functional changes. These include persistent myocardial fibrosis, edema, and intraventricular thrombi with embolic events, while functionally, the left ventricle is enlarged, with a reduced ejection fraction and new-onset arrhythmias reported in a number of patients. Myocarditis post-COVID-19 vaccination is rare but more common among young male patients. Larger studies, including prospective data from biobanks, will be useful in expanding these early findings and determining their validity

Frequency of Arrhythmias and Postural Orthostatic Tachycardia Syndrome in Patients With Marfan Syndrome: A Nationwide Inpatient Study.

Background Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder affecting multiple systems, particularly the cardiovascular system. The leading causes of death in MFS are aortopathies and valvular disease. We wanted to identify the frequency of arrhythmia and postural orthostatic tachycardia syndrome, length of hospital stay, health care-associated costs (HAC), and in-hospital mortality in patients with MFS. Methods and Results The National Inpatient Sample database from 2005 to 2014 was queried using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes for MFS and arrhythmias. Patients were classified into subgroups: supraventricular tachycardia, ventricular tachycardia (VT), atrial fibrillation, atrial flutter, and without any type of arrhythmia. Data about length of stay, HAC, and in-hospital mortality were also abstracted from National Inpatient Sample database. Adjusted HAC was calculated as multiplying HAC and cost-to-charge ratio; 12 079 MFS hospitalizations were identified; 1893 patients (15.7%) had an arrhythmia; and 4.9% of the patients had postural orthostatic tachycardia syndrome. Median values of length of stay and adjusted HAC in VT group were the highest among the groups (VT: 6 days, $18 975.8; supraventricular tachycardia: 4 days,$11 906.6; atrial flutter: 4 days, $11 274.5; atrial fibrillation: 5 days,$10431.4; without any type of arrhythmia: 4 days, $8336.6; both P=0.0001). VT group had highest in-patient mortality (VT: 5.3%, atrial fibrillation: 4.1%, without any type of arrhythmia: 2.1%, atrial flutter: 1.7%, supraventricular tachycardia: 0%; P<0.0001) even after adjustment for potential confounders (without any type of arrhythmia versus VT; odds ratio [95% CI]: 3.18 [1.62-6.24], P=0.001). Conclusions Arrhythmias and postural orthostatic tachycardia syndrome in MFS were high and associated with increased length of stay, HAC, and in-hospital mortality especially in patients with VT

State of the Art Review on Genetics and Precision Medicine in Arrhythmogenic Cardiomyopathy.

Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiomyopathy characterised by ventricular arrhythmia and an increased risk of sudden cardiac death (SCD). Numerous genetic determinants and phenotypic manifestations have been discovered in ACM, posing a significant clinical challenge. Further to this, wider evaluation of family members has revealed incomplete penetrance and variable expressivity in ACM, suggesting a complex genotype-phenotype relationship. This review details the genetic basis of ACM with specific genotype-phenotype associations, providing the reader with a nuanced perspective of this condition; whilst also proposing a future roadmap to delivering precision medicine-based management in ACM

Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

Background: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. // Methods: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. // Results: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. // Conclusions: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing

Sex-specific associations between daytime sleepiness, chronic diseases and mortality in obstructive sleep apnea

ObjectiveExcessive daytime sleepiness (EDS) is common in obstructive sleep apnea (OSA) and has been linked to adverse outcomes, albeit inconsistently. Furthermore, whether the prognostic impact of EDS differs as a function of sex is unclear. We aimed to assess the associations between EDS and chronic diseases and mortality in men and women with OSA.MethodsNewly-diagnosed adult OSA patients who underwent sleep evaluation at Mayo Clinic between November 2009 and April 2017 and completed the Epworth Sleepiness Scale (ESS) for assessment of perceived sleepiness (N = 14,823) were included. Multivariable-adjusted regression models were used to investigate the relationships between sleepiness, with ESS modeled as a binary (ESS &gt; 10) and as a continuous variable, and chronic diseases and all-cause mortality.ResultsIn cross-sectional analysis, ESS &gt; 10 was independently associated with lower risk of hypertension in male OSA patients (odds ratio [OR], 95% confidence interval [CI]: 0.76, 0.69–0.83) and with higher risk of diabetes mellitus in both OSA men (OR, 1.17, 95% CI 1.05–1.31) and women (OR 1.26, 95% CI 1.10–1.45). Sex-specific curvilinear relations between ESS score and depression and cancer were noted. After a median 6.2 (4.5–8.1) years of follow-up, the hazard ratio for all-cause death in OSA women with ESS &gt; 10 compared to those with ESS ≤ 10 was 1.24 (95% CI 1.05–1.47), after adjusting for demographics, sleep characteristics and comorbidities at baseline. In men, sleepiness was not associated with mortality.ConclusionThe implications of EDS for morbidity and mortality risk in OSA are sex-dependent, with hypersomnolence being independently associated with greater vulnerability to premature death only in female patients. Efforts to mitigate mortality risk and restore daytime vigilance in women with OSA should be prioritized

Beyond gene-disease validity: capturing structured data on inheritance, allelic-requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

BACKGROUND: As availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including as secondary findings. METHODS: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. RESULTS: For 36/65 gene-disease pairs, loss-of-function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using CardiacG2P as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. CONCLUSIONS: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is pre-requisite for scalable genomic testing

Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions

BACKGROUND: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. METHODS: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. RESULTS: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. CONCLUSIONS: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing