Objective Develop and validate a prognostic model for clinical deterioration or death within days of pulmonary embolism (PE) diagnosis using point-of-care criteria. Methods We used prospective registry data from six emergency departments. The primary composite outcome was death or deterioration (respiratory failure, cardiac arrest, new dysrhythmia, sustained hypotension, and rescue reperfusion intervention) within 5 days. Candidate predictors included laboratory and imaging right ventricle (RV) assessments. The prognostic model was developed from 935 PE patients. Univariable analysis of 138 candidate variables was followed by penalized and standard logistic regression on 26 retained variables, and then tested with a validation database (N = 801). Results Logistic regression yielded a nine-variable model, then simplified to a nine-point tool (PE-SCORE): one point each for abnormal RV by echocardiography, abnormal RV by computed tomography, systolic blood pressure < 100 mmHg, dysrhythmia, suspected/confirmed systemic infection, syncope, medico-social admission reason, abnormal heart rate, and two points for creatinine greater than 2.0 mg/dL. In the development database, 22.4% had the primary outcome. Prognostic accuracy of logistic regression model versus PE-SCORE model: 0.83 (0.80, 0.86) vs. 0.78 (0.75, 0.82) using area under the curve (AUC) and 0.61 (0.57, 0.64) vs. 0.50 (0.39, 0.60) using precision-recall curve (AUCpr). In the validation database, 26.6% had the primary outcome. PE-SCORE had AUC 0.77 (0.73, 0.81) and AUCpr 0.63 (0.43, 0.81). As points increased, outcome proportions increased: a score of zero had 2% outcome, whereas scores of six and above had ≥ 69.6% outcomes. In the validation dataset, PE-SCORE zero had 8% outcome [no deaths], whereas all patients with PE-SCORE of six and above had the primary outcome. Conclusions PE-SCORE model identifies PE patients at low- and high-risk for deterioration and may help guide decisions about early outpatient management versus need for hospital-based monitoring.

Background: The novel coronavirus SARS-CoV-2 has caused a pandemic, overwhelming health care systems around the world. Hospitals around the world, including the United States, have been struggling to adapt to the influx of patients with COVID-19, the illness caused by SARS-CoV2, given limited resources and high demand for medical care. Objectives: This article seeks to provide emergency physicians with a guide to sonographic findings in COVID-19 and an algorithm by which point-of-care lung ultrasound may assist emergency physicians caring for these patients during the SARS-CoV-2 pandemic. Discussion: The studies currently being published have established a typical set of ultrasound findings in COVID-19. Point-of-care lung ultrasound is rapid and accessible in most emergency departments in the United States, and even in many resource-poor settings. Conclusion: Point-ofcare ultrasound provides numerous benefits to emergency providers caring for patients with COVID-19, including decreasing resource utilization, assisting in diagnosis, guiding management of the critically ill patient, and aiding in rapid triage of patients under investigations for COVID-19.

Objectives We sought to determine associations of early electrocardiogram (ECG) patterns with clinical deterioration (CD) within 5 days and with RV abnormality (abnlRV) by echocardiography in pulmonary embolism (PE). Methods In this prospective, multicenter study of newly confirmed PE patients, early echocardiography and initial ECG were examined. Initial ECG patterns included lead‐specific ST‐segment elevation (STE) or depression (STD), T‐wave inversion (TWI), supraventricular tachycardia (SVT), sinus tachycardia, and right bundle branch block as complete (cRBBB) or incomplete (iRBBB). We defined CD as respiratory failure, hypotension, dysrhythmia, cardiac arrest, escalated PE intervention, or death within 5 days. We calculated odds ratios (ORs) for CD and abnlRV with univariate and full multivariate models in the presence of other variables. Results Of 1676 patients, 1629 (97.2%) had both ECG and GDE; 415/1676 (24.7%) had CD, and 529/1629 (32.4%) had abnlRV. AbnlRV had an OR for CD of 4.25 (3.35, 5.38). By univariable analysis, the absence of abnormal ECG patterns had OR for CD and abnlRV of 0.34 (0.26, 0.44; p < 0.001) and 0.24 (0.18, 0.31; p < 0.001), respectively. By multivariable analyses, one ECG pattern had a significant OR for CD: SVT 2.87 (1.66, 5.00). Significant ORS for abnlRV were: TWI V2–4 4.0 (2.64, 6.12), iRBBB 2.63 (1.59, 4.38), STE aVR 2.42 (1.58, 3.74), S1‐Q3‐T3 2.42 (1.70, 3.47), and sinus tachycardia 1.68 (1.14, 2.49). Conclusions SVT was an independent predictor of CD. TWI V2–4, iRBBB, STE aVR, sinus tachycardia, and S1‐Q3‐T3 were independent predictors of abnlRV. Finding one or more of these ECG patterns may increase considerations for performance of echocardiography to look for RV abnormalities and, if present, inform concerns for early clinical deterioration.

Objectives Identifying right ventricle (RV) abnormalities is important to stratifying pulmonary embolism (PE) severity. Disposition decisions are influenced by concerns about early deterioration. Triaging strategies, like the Simplified Pulmonary Embolism Severity Index (sPESI), do not include RV assessments as predictors or early deterioration as outcome(s). We aimed to (1) determine if RV assessment variables add prognostic accuracy for 5‐day clinical deterioration in patients classified low risk by sPESI, and (2) determine the prognostic importance of RV assessments compared to other variables and to each other. Methods We identified low risk sPESI patients (sPESI = 0) from a prospective PE registry. From a large field of candidate variables, we developed, and compared prognostic accuracy of, full and reduced random forest models (with and without RV assessment variables, respectively) on a validation database. We reported variable importance plots from full random forest and provided odds ratios for statistical inference of importance from multivariable logistic regression. Outcomes were death, cardiac arrest, hypotension, dysrhythmia, or respiratory failure within 5 days of PE. Results Of 1736 patients, 610 (35.1%) were low risk by sPESI and 72 (11.8%) experienced early deterioration. Of the 610, RV abnormality was present in 157 (25.7%) by CT, 121 (19.8%) by echocardiography, 132 (21.6%) by natriuretic peptide, and 107 (17.5%) by troponin. For deterioration, the receiver operating characteristics for full and reduced random forest prognostic models were 0.80 (0.77–0.82) and 0.71 (0.68–0.73), respectively. RV assessments were the top four in the variable importance plot for the random forest model. Echocardiography and CT significantly increased predicted probability of 5‐day clinical deterioration by the multivariable logistic regression. Conclusions A PE triaging strategy with RV imaging assessments had superior prognostic performance at classifying low risk for 5‐day clinical deterioration versus one without.

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