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It has become evident that acute COVID-19 infection can lead to cardiovascular complications. While the exact mechanisms by which COVID-19 affects the cardiovascular system have yet to be fully elucidated, several mechanisms have been proposed, including direct myocardial effects on the virus and systemic inflammation as an indirect result. The cardiovascular complications of COVID-19 have been characterized and described using noninvasive cardiac imaging. The impact of COVID-19 on the cardiovascular system extends beyond the acute phase of the infection and well beyond recovery or the convalescent period. However, the underlying mechanisms of post-viral long-COVID symptoms have yet to be elucidated. It is evident that COVID-19 has become endemic and is here to stay. Future studies are needed (1) to understand the long-term effects of the cardiovascular complications of COVID-19, future cardiovascular events and the impact of mutating variants on cardiovascular complications through data collection and analysis, (2) to identify the most important diagnostic criteria for prognosis of COVID-19 and to understand the disease mechanism through biomarkers and advanced cardiac imaging, including echocardiography and (3) to develop novel strategies to manage and treat these cardiovascular complications using the knowledge gained.

Abstract Background Pre-(PRE) and post-ejection (POE) velocities by mitral annular tissue Doppler (TD) are biphasic and may be related to myocardial deformations. We investigated the predominance and concordance of TD-PRE and POE velocities and their effect on myocardial functions in controls and in heart failure (HF) patients. Methods Retrospectively, 84 HF patients [57.6 years, 28(33%) females, NYHA: 2.3 ± 0.6, EF: 55 ± 15%, 52(62%) preserved EF, and 32(38%) reduced EF], 42 normal young controls, and 26 asymptomatic age matched controls were included. Echocardiography was done and from mitral annular tissue Doppler recordings, the biphasic PRE and POE velocity signals were identified and compared between groups. Results While controls had almost always predominantly positive PRE and negative POE, HF had more negative PRE and positive POE. Moreover, almost all controls exhibited normal concordance (positive PRE and negative POE). HF exhibited more abnormal concordance which was significantly associated with worse NYHA, and parameters of diastolic and systolic functions. Opposite PRE and POE velocities correlated significantly in all groups (PREp vs POEn: young:r = 0.52, p

IntroductionVariable D-dimer trends during hospitalization reportedly result in distinct in-hospital mortality. In this multinational case series from the first and second waves, we show the universality of such D-dimer trends.MethodsWe reviewed 405 patients with COVID-19 during the first wave admitted to three institutions in the United States, Italy, and Colombia, and 111 patients admitted to the U.S. site during the second wave and 55 patients during the third wave. D-dimer was serially followed during hospitalization.ResultsDuring the first wave, 66 (15%) patients had a persistently-low pattern, 33 (8%) had early-peaking, 70 (16%) had mid-peaking, 94 (22%) had fluctuating, 30 (7%) had late-peaking, and 112 (26%) had a persistently-high pattern. During the second and third waves, similar patterns were observed. D-dimer patterns were significantly different in terms of in-hospital mortality similarly in all waves. Patterns were then classified into low-risk patterns (persistently-low and early-peaking), where no deaths were observed in both waves, high-risk patterns (mid-peaking and fluctuating), and malignant patterns (late-peaking and persistently-high). Overall, D-dimer trends were associated with an increased risk for in-hospital mortality in the first wave (overall: HR: 1.73) and stayed the same during the second (HR: 1.67, p < 0.001) and the third (HR: 4.4, p = 0.001) waves.ConclusionD-dimer behavior during COVID-19 hospitalization yielded universal categories with distinct mortality risks that persisted throughout all studied waves of infection. Monitoring D-dimer behavior may be useful in the management of these patients.

Background: Right ventricular (RV) dysfunction in acute COVID-19 was reported to be associated with poor prognosis. We studied the association between parameters of RV dysfunction and in-hospital mortality during the surges caused by different SARS-CoV-2 variants. Methods: In a retrospective single-center study, we enrolled 648 consecutive patients hospitalized with COVID-19 [66 (10 %) hospitalized during the alpha variant surge, 433 (67 %) during the delta variant surge, and 149 (23 %), during the omicron variant surge]. Patients were reported from a hospital with an underreported population of mostly African American and Hispanic patients. Patients were followed for a median of 11 days during which in-hospital death occurred in 155 (24 %) patients [Alpha wave: 25 (38 %), Delta Wave: 112 (26 %), Omicron wave: 18 (12 %), p

Abstract Background The need for early identification of coronavirus disease (COVID-19) cases in communities was high in Yemen during the first wave of the COVID-19 epidemic because most cases presenting to health facilities were severe. Early detection of cases would allow early interventions to interrupt the transmission chains. This study aimed to describe the implementation of community-based surveillance (CBS) in in internally displaced people (IDP) camps and urban settings in Yemen from 15 April 2020 to 30 September 2020. Methods Following the Centers for Disease Control and Prevention guidance for evaluation of surveillance systems, we assessed the usefulness and acceptability of CBS. For acceptability, we calculated the proportion of trained volunteers who reported disease alerts. To assess the usefulness, we compared the alerts reported through the electronic diseases early warning system (eDEWS) with the alerts reported through CBS and described the response activities implemented. Results In Al-Mukalla City, 18% (14/78) of the volunteers reported at least one alert. In IDP camps, 58% (18/31) of volunteers reported at least one alert. In Al-Mukalla City, CBS detected 49 alerts of influenza-like illness, whereas health facilities detected 561 cases of COVID-19. In IDP camps, CBS detected 91 alerts of influenza-like illness, compared to 10 alerts detected through eDEWS. In IDP camps, CBS detected three other syndromes besides influenza-like illness (febrile illness outbreak suspicion, acute diarrhoea, and skin disease). In IDP camps, public health actions were implemented for each disease detected and no further cases were reported. Conclusions In Yemen, CBS was useful for detecting suspected outbreaks in IDP camps. CBS implementation did not yield expected results in general communities in urban areas in the early stage of the COVID-19 pandemic when little was known about the disease. In the urban setting, the system failed to detect suspected COVID-19 cases and other diseases despite the ongoing outbreaks reported through eDEWS. In Yemen, as in other countries, feasibility and acceptability studies should be conducted few months before CBS expansion in urban communities. The project should be expanded in IDP camps, by creating COVID-19 and other disease outbreak reporting sites.

Exponential growth in data storage and computational power is rapidly narrowing the gap between translating findings from advanced clinical informatics into cardiovascular clinical practice. Specifically, cardiovascular imaging has the distinct advantage in providing a great quantity of data for potentially rich insights, but nuanced interpretation requires a high-level skillset that few individuals possess. A subset of machine learning, deep learning (DL), is a modality that has shown promise, particularly in the areas of image recognition, computer vision, and video classification. Due to a low signal-to-noise ratio, echocardiographic data tend to be challenging to classify; however, utilization of robust DL architectures may help clinicians and researchers automate conventional human tasks and catalyze the extraction of clinically useful data from the petabytes of collected imaging data. The promise is extending far and beyond towards a contactless echocardiographic exam—a dream that is much needed in this time of uncertainty and social distancing brought on by a stunning pandemic culture. In the current review, we discuss state-of-the-art DL techniques and architectures that can be used for image and video classification, and future directions in echocardiographic research in the current era.

Background: Heart failure with preserved ejection fraction (HFpEF) is prevalent in women and is associated with atrial fibrillation (AF). However, sex associations in AF-related HFpEF are not well explored. Aim: We studied differences between men and women with and without AF-related HFpEF symptoms on left ventricular (LV) geometry and diastolic dysfunction (DD) and their effect on cardiovascular events. Methods: Retrospectively, HFpEF patients with and without a history of AF referred for echocardiography were studied. Echocardiographic assessments were focused on LV geometry and diastolic functions. Patients were followed for the occurrence of cardiac events defined as death and cardiac hospitalization. Results: We studied 556 patients [age: 66.7 ± 17 years, 320 (58%) women, 91 (16%) AF]. Compared to HFpEF without AF (HFpEF-AF), HFpEF with AF patients (HFpEF+AF) were older (76 ± 13.8 vs. 64.9 ± 17.3 years, p < 0.001), had more risk factors, comorbidities, left ventricular hypertrophy (32 vs. 13%, p < 0.001), higher relative wall thickness (0.50 ± 0.14 vs. 0.44 ± 0.15, p < 0.001), and DD (56 vs. 30%, all p < 0.001). HFpEF+AF women had the worst clinical, LV geometric, and diastolic functional profiles and highest rates of cardiovascular outcomes compared to HFpEF+AF men and were the only group to predict outcomes (HR: 2.7, 95%CI: 1.4–5.1), while HFpEF-AF women were a low-risk group; HFpEF+AF and HFpEF-AF men had intermediate cardiovascular outcomes which were confirmed after propensity score matching. Conclusions: Among patients with HFpEF, women with AF had more abnormal LV geometry and diastolic function and had an increased risk of adverse cardiovascular outcomes independent of traditional risk factors, comorbidities, and baseline diastolic function.