Background COVID-19 has caused a global pandemic unprecedented in a century. Though primarily a respiratory illness, cardiovascular risk factors predict adverse outcomes. We aimed to investigate the role of baseline echocardiographic abnormalities in further refining risk in addition to clinical risk factors. Methods Adults with COVID-19 positive RT-PCR test across St Luke’s University Health Network between March 1st 2020-October 31st 2020 were identified. Those with trans-thoracic echocardiography (TTE) within 15–180 days preceding COVID-19 positivity were selected, excluding severe valvular disease, acute cardiac event between TTE and COVID-19, or asymptomatic patients positive on screening. Demographic, clinical, and echocardiographic variables were manually extracted from patients’ EHR and compared between groups stratified by disease severity. Logistic regression was used to identify independent predictors of hospitalization. Results 192 patients met inclusion criteria. 87 (45.3%) required hospitalization, 34 (17.7%) suffered severe disease (need for ICU care/mechanical ventilation/in-hospital death). Age, co-morbidities, and several echocardiographic abnormalities were more prevalent in those with moderate-severe disease than in mild disease, with notable exceptions of systolic/diastolic dysfunction. On multivariate analysis, age (OR 1.039, 95% CI 1.011–1.067), coronary artery disease (OR 4.184, 95% CI 1.451–12.063), COPD (OR 6.886, 95% CI 1.396–33.959) and left atrial diameter ≥ 4.0 cm (OR 2.379, 95% CI 1.031–5.493) predicted need for hospitalization. Model showed excellent discrimination (ROC AUC 0.809, 95% CI 0.746–0.873). Conclusions Baseline left atrial enlargement is an independent risk factor for risk of hospitalization among patients with COVID-19. When available, baseline LA enlargement may identify patients for (1) closer outpatient follow up, and (2) counseling vaccine-hesitancy. Supplementary Information The online version contains supplementary material available at 10.1007/s10554-022-02565-4.
Spontaneous coronary artery dissection (SCAD) is a non-traumatic spontaneous separation of a coronary wall that can present as acute myocardial infarction. Pregnant females are already at a considerably higher risk of acute myocardial infarction when compared to non-pregnant women of child-bearing age, and dissection explains the majority of these cases. Here, we present a 36-year-old female at 36-weeks gestation who experienced ventricular fibrillation arrest after ST-segment elevation myocardial infarction (STEMI) secondary to spontaneous dissection of the left anterior descending (LAD) coronary artery.
Background Age and medical co-morbidities are known predictors of disease severity in coronavirus disease-2019 (COVID-19). Whether baseline transthoracic echocardiographic (TTE) abnormalities could refine risk-stratification in this context remains unknown. Purpose To analyze performance of a risk score combining clinical and pre-morbid TTE features in predicting risk of hospitalization among patients with COVID-19. Methods Adult patients testing positive for COVID-19 between March 1st and October 31st, 2020 with pre-infection TTE (within 15–180 days) were selected. Those with severe valvular disease, acute cardiac events between TTE and COVID-19, or asymptomatic carriers of virus (on employment screening/nursing home placement) were excluded. Baseline demographic, clinical co-morbidities, and TTE findings were extracted from electronic health records and compared between groups stratified by hospital admission. Total sample was randomly split into training (≈70%) and validation (≈30%) sets. Age was transformed into ordered categories based on cubic spline regression. Regression model was developed on the training set. Variables found significant (at p<0.10) on univariate analysis were selected for multivariate analysis with hospital admission as outcome. β-coefficients were obtained from 5000 bootstrapped samples after forced entry of significant variables, and scores assigned using Schneeweiss's scoring system. Final risk score performance was compared between training/validation cohorts using receiver-operating curve (ROC) and calibration curve analyses. Results 192 patients were included, 83 (43.2%) were admitted. Clinical/TTE characteristics stratified by hospitalization are in Table 1. Moderate or worse pulmonary hypertension and left atrial enlargement were only TTE parameters with coefficients deserving a score (Table 1). The risk score had excellent discrimination in training and validation sets (figure 1 left panel; AUC 0.785 versus 0.836, p=0.452). Calibration curves showed strong linear correlation between predicted and observed probabilities of hospitalization in both training and validation sets (Figure 1, middle and right panels, respectively). ROC analysis revealed a score ≥7 as having best overall quality with sensitivity and specificity of 70–75% in both training and validation sets. A score ≥12 had 98% and 97% specificity and ≥14 had 100% specificity. Conclusion A combined clinical and echocardiographic risk score shows promise in predicting risk of hospitalization among patients with COVID-19, and hence help anticipate resource utilization. External validation and comparison against clinical risk score alone is worth further investigation. FUNDunding Acknowledgement Type of funding sources: None.
Background: COVID-19 has caused an unprecedented global pandemic, with cardiovascular risk factors predicting outcomes. We investigated whether baseline trans-thoracic echocardiography could refine risk beyond clinical risk factors. Methods: Symptomatic COVID-19 positive (RT-PCR) adults across St Luke’s University Health Network between March 1st-October 31st 2021, with trans-thoracic echocardiography (TTE) within 15-180 days preceding COVID-19 positivity were selected. Demographic/clinical/echocardiographic variables were extracted from patients’ EHR and compared between groups stratified by disease severity. Logistic regression was used to identify independent predictors of hospitalization. Results: 192 patients were included. 87 (45.3%) required hospitalization, 34 (17.7%) suffered severe disease (need for ICU care/mechanical ventilation/in-hospital death). Age, co-morbidities, and several echocardiographic abnormalities were more prevalent in moderate-severe versus mild disease. On multivariate analysis, age (OR 1.039, 95% CI 1.011-1.067), coronary artery disease (OR 4.184, 95% CI 1.451-12.063), COPD (OR 6.886, 95% CI 1.396-33.959) and left atrial (LA) diameter ≥4.0cm (OR 2.379, 95% CI 1.031-5.493) predicted need for hospitalization. Model showed excellent discrimination (ROC AUC 0.809, 95% CI 0.746-0.873). Conclusion: Baseline LA enlargement independently predicts risk of hospitalization in COVID-19. When available, baseline LA enlargement could identify patients for 1) closer outpatient follow-up, and 2) counseling vaccine-hesitancy.
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