Recurrent Myocarditis in Patients With Desmosomal Pathogenic Variants: Is Self Antigen Presentation the Link?

Myocarditis is frequently associated with viral infections. Increasing evidence points to an association between myocarditis and inherited cardiomyopathies, though it is unclear whether myocarditis is a driver or an accessory. We present a primary vignette and case series highlighting recurrent myocarditis in patients later found to harbor pathogenic desmosomal variants and provide clinical and basic science context, exploring 2 potentially overlapping hypotheses: that stress induces cellular injury and death in structurally abnormal myocytes and that recurrent viral myocardial and truncated desomosomal protein byproducts as 2 hits could lead to loss of immune tolerance and subsequent autoreactivity.

Stroke and Noninfective Native Valvular Disease.

PURPOSE OF REVIEW: Embolic stroke of undetermined source is a challenging clinical entity. While less common than atrial fibrillation and endocarditis, many noninfective heart valve lesions have been associated with stroke and may be considered as culprits for cerebral infarcts when other more common causes are excluded. This review discusses the epidemiology, pathophysiology, and management of noninfective valvular diseases that are commonly associated with stroke. RECENT FINDINGS: Calcific debris from degenerating aortic and mitral valves may embolize to the cerebral vasculature causing small- or large-vessel ischemia. Thrombus which may be adherent to calcified valvular structures or left-sided cardiac tumors may also embolize resulting in stroke. Tumors themselves, most commonly myxomas and papillary fibroelastomas, may fragment and travel to the cerebral vasculature. Despite this broad differential, many types of valve diseases are highly comorbid with atrial fibrillation and vascular atheromatous disease. Thus, a high index of suspicion for more common causes of stroke is needed, especially given that treatment for valvular lesions typically involves cardiac surgery whereas secondary prevention of stroke due to occult atrial fibrillation is readily accomplished with anticoagulation.

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and mortality. To aid providers' decision-making, we aimed to analyze the electrocardiogram (ECG) using a deep convolutional neural network (CNN) to predict serum troponin I (TnI) from ECGs. We developed a CNN using 64,728 ECGs from 32,479 patients who underwent ECG within 2 h prior to a serum TnI laboratory result at the University of California, San Francisco (UCSF). In our primary analysis, we classified patients into groups of TnI < 0.02 or ≥ 0.02 µg/L using 12-lead ECGs. This was repeated with an alternative threshold of 1.0 µg/L and with single-lead ECG inputs. We also performed multiclass prediction for a set of serum troponin ranges. Finally, we tested the CNN in a cohort of patients selected for coronary angiography, including 3038 ECGs from 672 patients. Cohort patients were 49.0% female, 42.8% white, and 59.3% (19,283) never had a positive TnI value (≥ 0.02 µg/L). CNNs accurately predicted elevated TnI, both at a threshold of 0.02 µg/L (AUC = 0.783, 95% CI 0.780-0.786) and at a threshold of 1.0 µg/L (AUC = 0.802, 0.795-0.809). Models using single-lead ECG data achieved significantly lower accuracy, with AUCs ranging from 0.740 to 0.773 with variation by lead. Accuracy of the multi-class model was lower for intermediate TnI value-ranges. Our models performed similarly on the cohort of patients who underwent coronary angiography. Biomarker-defined myocardial injury can be predicted by CNNs from 12-lead and single-lead ECGs.

Acute coronary syndrome in patients with hemophilia: a delicate balancing act.

Therapeutic advances have resulted in increased life expectancy in patients with hemophilia. Consequently, the prevalence of coronary artery disease in this population is increasing. Little is known about the optimal management of acute coronary syndrome in these patients. Current guidelines for the management of this condition are based mainly on expert opinion and generally recommend administration of the clotting factor prior to the anticoagulant, antiplatelet, and interventional therapies. We report a case that illustrates the potential harm that may come from this approach: evolution of non-ST-segment elevation acute coronary syndrome into ST-elevation acute coronary syndrome during the administration of recombinant clotting factor. We review available literature and describe the refined informatics-based guidelines for managing acute coronary syndrome in patients with hemophilia we developed in response to the presented clinical case. We propose adopting this novel informatics-based approach, which aids in the identification and early treatment of these patients, operationalizes timely involvement of hematology experts, and gathers data for further study.

Identifying risk of adverse outcomes in COVID-19 patients via artificial intelligence-powered analysis of 12-lead intake electrocardiogram.

BACKGROUND: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered by the need to protect healthcare workers. We hypothesize that artificial intelligence (AI) can help identify subtle signs of myocardial involvement in the 12-lead electrocardiogram (ECG), which could help predict complications. OBJECTIVE: Use intake ECGs from COVID-19 patients to train AI models to predict risk of mortality or major adverse cardiovascular events (MACE). METHODS: We studied intake ECGs from 1448 COVID-19 patients (60.5% male, aged 63.4 ± 16.9 years). Records were labeled by mortality (death vs discharge) or MACE (no events vs arrhythmic, heart failure [HF], or thromboembolic [TE] events), then used to train AI models; these were compared to conventional regression models developed using demographic and comorbidity data. RESULTS: A total of 245 (17.7%) patients died (67.3% male, aged 74.5 ± 14.4 years); 352 (24.4%) experienced at least 1 MACE (119 arrhythmic, 107 HF, 130 TE). AI models predicted mortality and MACE with area under the curve (AUC) values of 0.60 ± 0.05 and 0.55 ± 0.07, respectively; these were comparable to AUC values for conventional models (0.73 ± 0.07 and 0.65 ± 0.10). There were no prominent temporal trends in mortality rate or MACE incidence in our cohort; holdout testing with data from after a cutoff date (June 9, 2020) did not degrade model performance. CONCLUSION: Using intake ECGs alone, our AI models had limited ability to predict hospitalized COVID-19 patients' risk of mortality or MACE. Our models' accuracy was comparable to that of conventional models built using more in-depth information, but translation to clinical use would require higher sensitivity and positive predictive value. In the future, we hope that mixed-input AI models utilizing both ECG and clinical data may be developed to enhance predictive accuracy.

Implementation of a fully remote randomized clinical trial with cardiac monitoring.

Background: The coronavirus disease 2019 (COVID-19) pandemic has challenged researchers performing clinical trials to develop innovative approaches to mitigate infectious risk while maintaining rigorous safety monitoring. Methods: In this report we describe the implementation of a novel exclusively remote randomized clinical trial (ClinicalTrials.gov NCT04354428) of hydroxychloroquine and azithromycin for the treatment of the SARS-CoV-2-mediated COVID-19 disease which included cardiovascular safety monitoring. All study activities were conducted remotely. Self-collected vital signs (temperature, respiratory rate, heart rate, and oxygen saturation) and electrocardiographic (ECG) measurements were transmitted digitally to investigators while mid-nasal swabs for SARS-CoV-2 testing were shipped. ECG collection relied on a consumer device (KardiaMobile 6L, AliveCor Inc.) that recorded and transmitted six-lead ECGs via participants' internet-enabled devices to a central core laboratory, which measured and reported QTc intervals that were then used to monitor safety. Results: Two hundred and thirty-one participants uploaded 3245 ECGs. Mean daily adherence to the ECG protocol was 85.2% and was similar to the survey and mid-nasal swab elements of the study. Adherence rates did not differ by age or sex assigned at birth and were high across all reported race and ethnicities. QTc prolongation meeting criteria for an adverse event occurred in 28 (12.1%) participants, with 2 occurring in the placebo group, 19 in the hydroxychloroquine group, and 7 in the hydroxychloroquine + azithromycin group. Conclusions: Our report demonstrates that digital health technologies can be leveraged to conduct rigorous, safe, and entirely remote clinical trials.

Evolution of acute ST-segment elevation myocardial infarction in a patient with ventricular preexcitation.

Wolff-Parkinson-White pattern is a relatively common electrocardiographic phenomenon caused by accessory atrioventricular (AV) conduction, which can make the diagnosis of acute myocardial infarction challenging. There is little existing literature regarding the interpretation of electrocardiograms in patients with accessory AV conduction pathways who present with acute myocardial infarction. We describe a case of electrocardiographic evolution of acute ST-segment elevation myocardial infarction in a patient with Wolff-Parkinson-White pattern, review pseudo-infarction patterns, and discuss proposed mechanisms for these repolarization abnormalities.

The mouse-equivalent of the human BDNF VAL66MET polymorphism increases dorsal hippocampal volume and does not interact with developmental ethanol exposure.

A relatively common polymorphism in the human brain-derived neurotrophic factor (BDNF) gene (Val66Met, which corresponds to Val68Met in mice) has been shown to modulate cognitive function and vulnerability to mental health disorders. This substitution impairs trafficking and activity-dependent release of BDNF. A number of studies with both humans and transgenic mice suggest that carriers of the Met allele have deficits in the structure and/or function of the hippocampal formation. Using a relatively new transgenic mouse model of this polymorphism, we recently demonstrated that it modulates the effects of developmental ethanol exposure in the hippocampus. Here, we further characterized the effect of this polymorphism on hippocampal morphology and its interaction with ethanol vapor exposure during the 2nd and 3rd trimester equivalents of human pregnancy. We found that BDNFmet/met mice have slightly larger hippocampal volumes than BDNFval/val mice. Ethanol vapor exposure during the 2nd and 3rd trimester equivalents of human pregnancy increased hippocampal volume in a single hippocampal subregion, the CA1 stratum radiatum. Ethanol exposure did not interact with BDNF genotype to affect volume in any hippocampal subregion. These results suggest that the Val66Met polymorphism does not reduce hippocampal size (i.e., it rather increases it slightly) or increase susceptibility to prenatal ethanol exposure-induced structural hippocampal damage during adulthood.

Pulmonary arterial capacitance predicts outcomes in patients with pulmonary hypertension independent of race/ethnicity, sex, and etiology.

BACKGROUND: Pulmonary arterial capacitance (PAC) is a strong hemodynamic predictor of outcomes in patients with pulmonary hypertension (PH). Its value across subgroups of race/ethnicity, sex, and PH etiologies is unclear. We hypothesized that the association of PAC with outcomes would not vary across World Health Organization (WHO) PH group, race/ethnicity, or sex. METHODS: We performed a retrospective study in patients with PH diagnosed and managed at the Pulmonary Hypertension Comprehensive Care Center of a tertiary care hospital (n = 270). Demographic, diagnostic, treatment, and outcome data were extracted from the electronic medical record. Cox proportional hazards models were used to model time from right heart catheterization to event in univariate and multivariable models. Our primary outcome was all-cause mortality and our secondary outcome was PH hospitalization. RESULTS: The median age of the cohort was 56 years (±14.6), and 67% were female. In multivariable Cox models adjusted for significant covariates, decreased PAC remained independently and significantly associated with both all-cause mortality (p = 0.029) and hospitalization for PH (p = 0.010). No significant interactions were observed between PAC and race, sex, or WHO group. Hispanic patients exhibited a significant independent association with increased hospitalizations (p = 0.030), and there was a trend toward increased all-cause mortality in African Americans. WHO group 2 PH was associated with more frequent hospitalization (p = 0.004). CONCLUSIONS: Decreased PAC is significantly associated with mortality and hospitalization in PH patients independent of race, sex, and PH subgroups. Further investigation is required to characterize the effects and determinants of racial disparities in PH.

Beyond Men, Women, or Both: A Comprehensive, LGBTQ-Inclusive, Implicit-Bias-Aware, Standardized-Patient-Based Sexual History Taking Curriculum.

Introduction: This standardized-patient-based module prepares medical students to take inclusive, comprehensive sexual histories from patients of all sexual orientations and gender identities. Health disparities faced by lesbian, gay, bisexual, transgender, and queer (LGBTQ) people are at least partially the result of inadequate access to health care and insufficient provider training. This module incorporates implicit bias activities to emphasize the important role providers can play in mitigating these disparities through compassionate, competent care. Furthermore, two of the three included cases highlight the negative impact sexual dysfunction can have on emotional well-being. Methods: Over 3 hours, students participate in a 30-minute large-group lecture and three 40-minute small-group standardized patient encounters with debrief. Prework consists of a short video on sexual history taking, assigned readings, and an implicit bias activity. These materials are included in this resource, along with lecture slides, facilitator guide, and standardized patient cases. Though the cases are adaptable to all levels of medical education, this module is designed for second-year and early third-year medical students. Results: Qualitative student evaluations were positive, and postparticipation surveys revealed statistically significant improvement in comfort with their ability to take a sexual history in general, and take one from patients with a differing sexual orientation. Deployed in the second year of our Doctoring curriculum, this module continues to receive positive evaluations. Discussion: Introducing these skills begins to address the curricular deficiencies seen across medical education and lays the foundation for a more competent health care workforce to address the needs of LGBTQ patients.