Individuals with established cardiovascular disease or a high burden of cardiovascular risk factors may be particularly vulnerable to develop complications from coronavirus disease 2019 (COVID-19). We conducted a prospective cohort study at a tertiary care center to identify risk factors for in-hospital mortality and major adverse cardiovascular events (MACE; a composite of myocardial infarction, stroke, new acute decompensated heart failure, venous thromboembolism, ventricular or atrial arrhythmia, pericardial effusion, or aborted cardiac arrest) among consecutively hospitalized adults with COVID-19, using multivariable binary logistic regression analysis. The study population comprised 586 COVID-19 positive patients. Median age was 67 (IQR: 55-80) years, 47.4% were female, and 36.7% had cardiovascular disease. Considering risk factors, 60.2% had hypertension, 39.8% diabetes, and 38.6% hyperlipidemia. Eighty-two individuals (14.0%) died in-hospital, and 135 (23.0%) experienced MACE. In a model adjusted for demographic characteristics, clinical presentation, and laboratory findings, age (odds ratio [OR], 1.28 per 5 years; 95% confidence interval [CI], 1.13-1.45), prior ventricular arrhythmia (OR, 18.97; 95% CI, 3.68-97.88), use of P2Y 12 -inhibitors (OR, 7.91; 95% CI, 1.64-38.17), higher C-reactive protein (OR, 1.81: 95% CI, 1.18-2.78), lower albumin (OR, 0.64: 95% CI, 0.47-0.86), and higher troponin T (OR, 1.84; 95% CI, 1.39-2.46) were associated with mortality (p<0.05). After adjustment for demographics, presentation, and laboratory findings, predictors of MACE were higher respiratory rates, altered mental status, and laboratory abnormalities, including higher troponin T (p<0.05). In conclusion, poor prognostic markers among hospitalized patients with COVID-19 included older age, pre-existing cardiovascular disease, respiratory failure, altered mental status, and higher troponin T concentrations.

Research into prevention of cardiovascular disease has increasingly focused on mobile health (mHealth) technologies and their efficacy in helping individuals adhere to heart-healthy recommendations, including daily physical activity levels. By including the use of mHealth technologies in the discussion of physical activity recommendations, clinicians empower patients to play an active daily role in modifying their cardiovascular risk-factor profile. In this review, we critically evaluate the mHealth and physical activity literature to determine how these tools may lower cardiovascular risk while providing real-time tracking, feedback, and motivation on physical activity levels. We analyze the various domains-including user knowledge, social support, behavioral change theory, and self-motivation-that potentially influence the effectiveness of smartphone applications to impact individual physical activity levels. In doing so, we hope to provide a thorough overview of the mHealth landscape, in addition to highlighting many of the administrative, reimbursement, and patient-privacy challenges of using these technologies in patient care. Finally, we propose a behavioral change model and checklist for clinicians to assist patients in utilizing mHealth technology to best achieve meaningful changes in daily physical activity levels.

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