Unsupervised machine learning demonstrates the prognostic value of TAPSE/PASP ratio among hospitalized patients with COVID-19.

BACKGROUND: The ratio of tricuspid annular plane systolic excursion (TAPSE) to pulmonary artery systolic pressure (PASP) is a validated index of right ventricular-pulmonary arterial (RV-PA) coupling with prognostic value. We determined the predictive value of TAPSE/PASP ratio and adverse clinical outcomes in hospitalized patients with COVID-19. METHODS: Two hundred and twenty-nine consecutive hospitalized racially/ethnically diverse adults (≥18 years of age) admitted with COVID-19 between March and June 2020 with clinically indicated transthoracic echocardiograms (TTE) that included adequate tricuspid regurgitation (TR) velocities for calculation of PASP were studied. The exposure of interest was impaired RV-PA coupling as assessed by TAPSE/PASP ratio. The primary outcome was in-hospital mortality. Secondary endpoints comprised of ICU admission, incident acute respiratory distress syndrome (ARDS), and systolic heart failure. RESULTS: One hundred and seventy-six patients had both technically adequate TAPSE measurements and measurable TR velocities for analysis. After adjustment for age, sex, BMI, race/ethnicity, diabetes mellitus, and smoking status, log(TAPSE/PASP) had a significantly inverse association with ICU admission (p = 0.015) and death (p = 0.038). ROC analysis showed the optimal cutoff for TAPSE/PASP for death was 0.51 mm mmHg-1 (AUC = 0.68). Unsupervised machine learning identified two groups of echocardiographic function. Of all echocardiographic measures included, TAPSE/PASP ratio was the most significant in predicting in-hospital mortality, further supporting its significance in this cohort. CONCLUSION: Impaired RV-PA coupling, assessed noninvasively via the TAPSE/PASP ratio, was predictive of need for ICU level care and in-hospital mortality in hospitalized patients with COVID-19 suggesting utility of TAPSE/PASP in identification of poor clinical outcomes in this population both by traditional statistical and unsupervised machine learning based methods.

Improving risk prediction for pulmonary embolism in COVID-19 patients using echocardiography.

SARS-CoV-2 infection is associated with increased risk for pulmonary embolism (PE), a fatal complication that can cause right ventricular (RV) dysfunction. Serum D-dimer levels are a sensitive test to suggest PE, however lacks specificity in COVID-19 patients. The goal of this study was to identify a model that better predicts PE diagnosis in hospitalized COVID-19 patients using clinical, laboratory, and echocardiographic imaging predictors. We performed a cross-sectional study of 302 adult patients admitted to the Johns Hopkins Hospital (March 2020-February 2021) for COVID-19 infection who underwent transthoracic echocardiography and D-dimer testing; 204 patients had CT angiography. Clinical, laboratory and imaging predictors including, but not limited to, D-dimer and RV dysfunction were used to build prediction models for PE using logistic regression. Model discrimination was assessed using area under the receiver operator curve (AUC) and calibration using Hosmer-Lemeshow χ 2 statistic. Internal validation was performed. The prevalence of PE was 7.6%. The model with positive D-dimer above 5 mg/L, RV dysfunction on echocardiography, and troponin had an AUC of 0.77, and cross-validated AUC of 0.74. D-dimer (>5 mg/L) had a positive association with PE (adj odds ratio = 4.40; 95% confidence interval: [1.80, 10.78]). We identified a model including clinical, imaging and laboratory variables that predicted PE in hospitalized COVID-19 patients. Positive D-dimer >5, RV dysfunction on echocardiography, and troponin were important predictors for calculating likelihood of PE diagnosis. This approach may be useful to aid in clinical decision-making related to diagnostic imaging and treatment. Prospective studies are needed to evaluate impact on patient outcomes.

Multimodality Imaging for Cardiac Evaluation in Patients with COVID-19.

PURPOSE OF REVIEW: A growing number of cardiovascular manifestations resulting from the novel SARS-CoV-2 coronavirus (COVID-19) have been described since the beginning of this global pandemic. Acute myocardial injury is common in this population and is associated with higher rates of morbidity and mortality. The focus of this review centers on the recent applications of multimodality imaging in the diagnosis and management of COVID-19-related cardiovascular conditions. RECENT FINDINGS: In addition to standard cardiac imaging techniques such as transthoracic echocardiography, other modalities including computed tomography and cardiac magnetic resonance imaging have emerged as useful adjuncts in select patients with COVID-19 infection, particularly those with suspected ischemic and nonischemic myocardial injury. Data have also emerged suggesting lasting COVID-19 subclinical cardiac effects, which may have long-term prognostic implications. With the spectrum of COVID-19 cardiovascular manifestations observed thus far, it is important for clinicians to recognize the role, strengths, and limitations of multimodality imaging techniques in this patient population.

Multimodality Imaging in Evaluation of Cardiovascular Complications in Patients With COVID-19: JACC Scientific Expert Panel.

Standard evaluation and management of the patient with suspected or proven cardiovascular complications of coronavirus disease-2019 (COVID-19), the disease caused by severe acute respiratory syndrome related-coronavirus-2 (SARS-CoV-2), is challenging. Routine history, physical examination, laboratory testing, electrocardiography, and plain x-ray imaging may often suffice for such patients, but given overlap between COVID-19 and typical cardiovascular diagnoses such as heart failure and acute myocardial infarction, need frequently arises for advanced imaging techniques to assist in differential diagnosis and management. This document provides guidance in several common scenarios among patients with confirmed or suspected COVID-19 infection and possible cardiovascular involvement, including chest discomfort with electrocardiographic changes, acute hemodynamic instability, newly recognized left ventricular dysfunction, as well as imaging during the subacute/chronic phase of COVID-19. For each, the authors consider the role of biomarker testing to guide imaging decision-making, provide differential diagnostic considerations, and offer general suggestions regarding application of various advanced imaging techniques.