Cardiac involvement in hospitalized patients with COVID-19 and its incremental value in outcomes prediction

Incidence and Impact of Acute Pericarditis in Hospitalized Patients With COVID-19

Background Acute pericarditis (AP) is considered a cardiovascular complication in patients with COVID-19. We aimed to ass-ess the incidence, associated complications, and clinical impact of AP on hospitalized patients with COVID-19. Methods and Results In this retrospective cohort study, International Classification of Diseases, Tenthth Revision, Clinical Modification (ICD-10) codes were used to identify patients with COVID-19 with or without AP in the National Inpatient Sample 2020 database. We compared outcomes between AP and non-AP groups before and after propensity-score matching for patient and hospital demographics and relevant comorbidities. A total of 211 619 patients with a primary diagnosis of COVID-19 were identified, including 983 (0.46%) patients who had a secondary diagnosis of AP. Before matching, patients with COVID-19 with AP were younger (59.93±19.24 years old versus 64.29±16.82 years old) and more likely to have anemia (40.5% versus 19.9%), cancer (6.7% versus 3.6%), and chronic kidney disease (29.3% versus 19.6%) (all P<0.05). After matching, patients with COVID-19 with AP (n=980), when compared with the matched non-AP group (n=2936), had higher rates of mortality (21.3% versus 11.1%, P<0.001), cardiac arrest (5.0% versus 2.6%, P<0.001), cardiogenic shock (4.2% versus 0.5%, P<0.001), ventricular arrhythmia (4.7% versus 1.9%, P<0.001), acute kidney injury (38.3% versus 28.9%, P<0.001), acute congestive heart failure (14.3% versus 4.8%, P<0.001), and longer length of stay (7.00±10.00 days versus 5.00±7.00 days, P<0.001) and higher total charges ($75066.5±$130831.3 versus $44824.0±$63660.5, P<0.001). Conclusions In hospitalized patients with COVID-19, AP is a rare but severe in-hospital complication and is associated with worse in-hospital outcomes.

Literature Review-Transthoracic Echocardiography, Computed Tomography Angiography, and Their Value in Clinical Decision Making and Outcome Predictions in Patients with COVID-19 Associated Cardiovascular Complications

The sudden outbreak of the COVID-19 pandemic posed a great threat to the world's healthcare systems. It resulted in the development of new methods and algorithms for the diagnosis and treatment of both COVID-19 and its complications. Diagnostic imaging played a crucial role in both cases. Among the most widely used examinations are transthoracic echocardiography (TTE) and computed tomography angiography (CTA). Cardiovascular complications in COVID-19 are frequently associated with a severe inflammatory response, which results in acute respiratory failure, further leading to severe complications of the cardiovascular system. Our review aims to discuss the value of TTE and CTA in clinical decision making and outcome prediction in patients with COVID-19-associated cardiovascular complications. Our review revealed the high clinical value of various TTE findings and their association with mortality and the prediction of patients' clinical outcomes, especially when used with other laboratory parameters. The strongest association between increased mortality and findings in TTE was observed for tachycardia and decreased left ventricular ejection fraction (odds ratio (OR) 24.06) and tricuspid annular plane systolic excursion/pulmonary artery systolic pressure ratio (TAPSE/PASP ratio) < 0.31 mm/mmHg (OR 17.80). CTA is a valuable tool in diagnosing COVID-19-associated pulmonary embolism, but its association with mortality and its predictive role should always be combined with laboratory findings and patients' medical history. D-dimers > 3000 ng/mL were found as the strongest predictors of pulmonary embolism (PE) (OR 7.494). Our review indicates the necessity for an active search for cardiovascular complications in patients with severe COVID-19, as they are linked with an increased probability of fatal outcomes.

Multimodality Cardiac Imaging in COVID

Infection with SARS-CoV-2, the virus that causes COVID, is associated with numerous potential secondary complications. Global efforts have been dedicated to understanding the myriad potential cardiovascular sequelae which may occur during acute infection, convalescence, or recovery. Because patients often present with nonspecific symptoms and laboratory findings, cardiac imaging has emerged as an important tool for the discrimination of pulmonary and cardiovascular complications of this disease. The clinician investigating a potential COVID-related complication must account not only for the relative utility of various cardiac imaging modalities but also for the risk of infectious exposure to staff and other patients. Extraordinary clinical and scholarly efforts have brought the international medical community closer to a consensus on the appropriate indications for diagnostic cardiac imaging during this protracted pandemic. In this review, we summarize the existing literature and reference major societal guidelines to provide an overview of the indications and utility of echocardiography, nuclear imaging, cardiac computed tomography, and cardiac magnetic resonance imaging for the diagnosis of cardiovascular complications of COVID.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.

Myocardial Work in Patients Hospitalized With COVID-19: Relation to Biomarkers, COVID-19 Severity, and All-Cause Mortality

Background COVID-19 infection has been hypothesized to affect left ventricular function; however, the underlying mechanisms and the association to clinical outcome are not understood. The global work index (GWI) is a novel echocardiographic measure of systolic function that may offer insights on cardiac dysfunction in COVID-19. We hypothesized that GWI was associated with disease severity and all-cause death in patients with COVID-19. Methods and Results In a multicenter study of patients admitted with COVID-19 (n=305), 249 underwent pressure-strain loop analyses to quantify GWI at a median time of 4 days after admission. We examined the association of GWI to cardiac biomarkers (troponin and NT-proBNP [N-terminal pro-B-type natriuretic peptide]), disease severity (oxygen requirement and CRP [C-reactive protein]), and all-cause death. Patients with elevated troponin (n=71) exhibited significantly reduced GWI (1508 versus 1707 mm Hg%; P=0.018). A curvilinear association to NT-proBNP was observed, with increasing NT-proBNP once GWI decreased below 1446 mm Hg%. Moreover, GWI was significantly associated with a higher oxygen requirement (relative increase of 6% per 100-mm Hg% decrease). No association was observed with CRP. Of the 249 patients, 37 died during follow-up (median, 58 days). In multivariable Cox regression, GWI was associated with all-cause death (hazard ratio, 1.08 [95% CI, 1.01-1.15], per 100-mm Hg% decrease), but did not increase C-statistics when added to clinical parameters. Conclusions In patients admitted with COVID-19, our findings indicate that NT-proBNP and troponin may be associated with lower GWI, whereas CRP is not. GWI was independently associated with all-cause death, but did not provide prognostic information beyond readily available clinical parameters. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04377035.

Artificial Intelligence-Enhanced Echocardiography for Systolic Function Assessment

The accurate assessment of left ventricular systolic function is crucial in the diagnosis and treatment of cardiovascular diseases. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) are the most critical indexes of cardiac systolic function. Echocardiography has become the mainstay of cardiac imaging for measuring LVEF and GLS because it is non-invasive, radiation-free, and allows for bedside operation and real-time processing. However, the human assessment of cardiac function depends on the sonographer’s experience, and despite their years of training, inter-observer variability exists. In addition, GLS requires post-processing, which is time consuming and shows variability across different devices. Researchers have turned to artificial intelligence (AI) to address these challenges. The powerful learning capabilities of AI enable feature extraction, which helps to achieve accurate identification of cardiac structures and reliable estimation of the ventricular volume and myocardial motion. Hence, the automatic output of systolic function indexes can be achieved based on echocardiographic images. This review attempts to thoroughly explain the latest progress of AI in assessing left ventricular systolic function and differential diagnosis of heart diseases by echocardiography and discusses the challenges and promises of this new field.

Artificial Intelligence-Enhanced Echocardiography for Systolic Function Assessment

The accurate assessment of left ventricular systolic function is crucial in the diagnosis and treatment of cardiovascular diseases. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) are the most critical indexes of cardiac systolic function. Echocardiography has become the mainstay of cardiac imaging for measuring LVEF and GLS because it is non-invasive, radiation-free, and allows for bedside operation and real-time processing. However, the human assessment of cardiac function depends on the sonographer's experience, and despite their years of training, inter-observer variability exists. In addition, GLS requires post-processing, which is time consuming and shows variability across different devices. Researchers have turned to artificial intelligence (AI) to address these challenges. The powerful learning capabilities of AI enable feature extraction, which helps to achieve accurate identification of cardiac structures and reliable estimation of the ventricular volume and myocardial motion. Hence, the automatic output of systolic function indexes can be achieved based on echocardiographic images. This review attempts to thoroughly explain the latest progress of AI in assessing left ventricular systolic function and differential diagnosis of heart diseases by echocardiography and discusses the challenges and promises of this new field.

Pericardial Involvement in Patients Hospitalized With COVID‐19: Prevalence, Associates, and Clinical Implications

Background

The scope of pericardial involvement in COVID‐19 infection is unknown. We aimed to evaluate the prevalence, associates, and clinical impact of pericardial involvement in hospitalized patients with COVID‐19.

Methods and Results

Consecutive patients with COVID‐19 underwent clinical and echocardiographic examination, irrespective of clinical indication, within 48 hours as part of a prospective predefined protocol. Protocol included clinical symptoms and signs suggestive of pericarditis, calculation of modified early warning score, ECG and echocardiographic assessment for pericardial effusion, left and right ventricular systolic and diastolic function, and hemodynamics. We identified predictors of mortality and assessed the adjunctive value of pericardial effusion on top of clinical and echocardiographic parameters. The study included 530 patients. Pericardial effusion was found in 75 (14%), but only 17 patients (3.2%) fulfilled the criteria for acute pericarditis. Pericardial effusion was independently associated with modified early warning score, brain natriuretic peptide, and right ventricular function. It was associated with excess mortality (hazard ratio [HR], 2.44; P=0.0005) in nonadjusted analysis. In multivariate analysis adjusted for modified early warning score and echocardiographic and hemodynamic parameters, it was marginally associated with mortality (HR, 1.86; P=0.06) and improvement in the model fit (P=0.07). Combined assessment for pericardial effusion with modified early warning score, left ventricular ejection fraction, and tricuspid annular plane systolic excursion was an independent predictor of outcome (HR, 1.86; P=0.02) and improved model fit (P=0.02).

Conclusions

In hospitalized patients with COVID‐19, pericardial effusion is prevalent, but rarely attributable to acute pericarditis. It is associated with myocardial dysfunction and mortality. A limited echocardiographic examination, including left ventricular ejection fraction, tricuspid annular plane systolic excursion, and assessment for pericardial effusion, can contribute to outcome prediction.