No abstract

A novel coronavirus, SARS-CoV-2, thought to have originated from bats causes COVID-19 infection which was first reported from Wuhan, China in December 2019. This virus has a high infectivity rate and has impacted a significant chunk of the population worldwide. The spectrum of disease ranges from mild to severe with respiratory system being the most commonly affected. Cardiovascular system often gets involved in later stages of the disease with acute cardiac injury, heart failure and arrhythmias being the common complications. In addition, the presence of cardiovascular co-morbidities such as hypertension, coronary artery disease in these patients are often associated with poor prognosis. It is still not clear regarding the exact mechanism explaining cardiovascular system involvement in COVID-19. Multiple theories have been put forward however, more robust studies are required to fully elucidate the “heart and virus” link. The disease has already made its presence felt on the global stage and its impact in the developing countries is going to be profound. These nations not only have a poorly developed healthcare system but there is also a huge burden of cardiovascular diseases. As a result, COVID-19 would adversely impact the already overburdened healthcare network leading to impaired cardiovascular care delivery especially for acute coronary syndrome and heart failure patients.

Introduction Cardiovascular dysautonomia comprising postural orthostatic tachycardia syndrome (POTS) and orthostatic hypotension (OH) is one of the presentations in COVID-19 recovered subjects. We aim to determine the prevalence of cardiovascular dysautonomia in post COVID-19 patients and to evaluate an Artificial Intelligence (AI) model to identify time domain heart rate variability (HRV) measures most suitable for short term ECG in these subjects. Methods This observational study enrolled 92 recently COVID-19 recovered subjects who underwent measurement of heart rate and blood pressure response to standing up from supine position and a 12-lead ECG recording for 60 s period during supine paced breathing. Using feature extraction, ECG features including those of HRV (RMSSD and SDNN) were obtained. An AI model was constructed with ShAP AI interpretability to determine time domain HRV features representing post COVID-19 recovered state. In addition, 120 healthy volunteers were enrolled as controls. Results Cardiovascular dysautonomia was present in 15.21% (OH:13.04%; POTS:2.17%) . Patients with OH had significantly lower HRV and higher inflammatory markers. HRV (RMSSD) was significantly lower in post COVID-19 patients compared to healthy controls (13.9 ± 11.8 ms vs 19.9 ± 19.5 ms; P = 0.01) with inverse correlation between HRV and inflammatory markers. Multiple perceptron was best performing AI model with HRV(RMSSD) being the top time domain HRV feature distinguishing between COVID-19 recovered patients and healthy controls. Conclusion Present study showed that cardiovascular dysautonomia is common in COVID-19 recovered subjects with a significantly lower HRV compared to healthy controls. The AI model was able to distinguish between COVID-19 recovered patients and healthy controls.

Background Coronavirus disease 2019 (COVID-19) has led to a widespread morbidity and mortality. Limited data exists regarding the involvement of cardiovascular system in COVID-19 patients. We sought to evaluate the cardiovascular (CV) complications and its impact on outcomes in symptomatic COVID-19 patients. Methods This was a single center observational study among symptomatic COVID-19 patients. Data regarding clinical profile, laboratory investigations, CV complications, treatment and outcomes were collected. Cardiac biomarkers and 12 lead electrocardiograms were done in all while echocardiography was done in those with clinical indications for the same. Corrected QT-interval (QTc) at baseline and maximum value during hospitalization were computed. Results Of the 108 patients, majority of them were males with a mean age of 51.2 ± 17.7 years. Hypertension (38%) and diabetes (32.4%) were most prevalent co-morbidities. ECG findings included sinus tachycardia in 18 (16.9%), first degree AV block in 5 (4.6%), VT/VF in 2 (1.8%) and sinus bradycardia in one (0.9%). QTc prolongation was observed in 17.6% subjects. CV complications included acute cardiac injury in 25.9%, heart failure, cardiogenic shock and acute coronary syndrome in 3.7% each, “probable” myocarditis in 2.8% patients. Patients with acute cardiac injury had higher mortality than those without (16/28 [57.1%] vs 14/78 [17.5%]; P < 0.0001). Multivariate logistic regression analysis showed that acute cardiac injury (OR: 11.3), lymphopenia (OR: 4.91), use of inotropic agents (OR: 2.46) and neutrophil-lymphocyte ratio (OR:1.1) were independent predictors of mortality. Conclusions CV complications such as acute cardiac injury is common in COVID-19 patients and is associated with worse prognosis.