ABSTRACT
Background: COVID-19 infection carries significant morbidity and mortality. Current risk prediction for complications in COVID-19 is limited, and existing approaches fail to account for the dynamic course of the disease. Objectives: The purpose of this study was to develop and validate the COVID-HEART predictor, a novel continuously updating risk-prediction technology to forecast adverse events in hospitalized patients with COVID-19. Methods: Retrospective registry data from patients with severe acute respiratory syndrome coronavirus 2 infection admitted to 5 hospitals were used to train COVID-HEART to predict all-cause mortality/cardiac arrest (AM/CA) and imaging-confirmed thromboembolic events (TEs) (n = 2,550 and n = 1,854, respectively). To assess COVID-HEART's performance in the face of rapidly changing clinical treatment guidelines, an additional 1,100 and 796 patients, admitted after the completion of development data collection, were used for testing. Leave-hospital-out validation was performed. Results: Over 20 iterations of temporally divided testing, the mean area under the receiver operating characteristic curve were 0.917 (95% confidence interval [CI]: 0.916-0.919) and 0.757 (95% CI: 0.751-0.763) for prediction of AM/CA and TE, respectively. The interquartile ranges of median early warning times were 14 to 21 hours for AM/CA and 12 to 60 hours for TE. The mean area under the receiver operating characteristic curve for the left-out hospitals were 0.956 (95% CI: 0.936-0.976) and 0.781 (95% CI: 0.642-0.919) for prediction of AM/CA and TE, respectively. Conclusions: The continuously updating, fully interpretable COVID-HEART predictor accurately predicts AM/CA and TE within multiple time windows in hospitalized COVID-19 patients. In its current implementation, the predictor can facilitate practical, meaningful changes in patient triage and resource allocation by providing real-time risk scores for these outcomes. The potential utility of the predictor extends to COVID-19 patients after hospitalization and beyond COVID-19.
ABSTRACT
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.
ABSTRACT
OBJECTIVES: There is increasing evidence of cardiovascular morbidity associated with severe acute respiratory syndrome coronavirus 2 (coronavirus disease 2019). Pro-B-type natriuretic peptide is a biomarker of myocardial stress, associated with various respiratory and cardiac outcomes. We hypothesized that pro-B-type natriuretic peptide level would be associated with mortality and clinical outcomes in hospitalized coronavirus disease 2019 patients. DESIGN: We performed a retrospective analysis using adjusted logistic and linear regression to assess the association of admission pro-B-type natriuretic peptide (analyzed by both cutoff > 125 pg/mL and log transformed pro-B-type natriuretic peptide) with clinical outcomes. We additionally treated body mass index, a confounder of both pro-B-type natriuretic peptide levels and coronavirus disease 2019 outcomes, as an ordinal variable. SETTING: We reviewed hospitalized patients with coronavirus disease 2019 who had a pro-B-type natriuretic peptide level measured within 48 hours of admission between March 1, and August 31, 2020, from a multihospital U.S. health system. PATIENTS: Adult patients (≥ 18 yr old; n = 1232) with confirmed coronavirus disease 2019 admitted to the health system. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: After adjustment for demographics, comorbidities, and troponin I level, higher pro-B-type natriuretic peptide level was significantly associated with death and secondary outcomes of new heart failure, length of stay, ICU duration, and need for ventilation among hospitalized coronavirus disease 2019 patients. This significance persisted after adjustment for body mass index as an ordinal variable. The adjusted hazard ratio of death for log transformed pro-B-type natriuretic peptide was 1.56 (95% CI, 1.23-1.97; p < 0.0001). CONCLUSIONS: Further investigation is warranted on the utility of pro-B-type natriuretic peptide for clinical prognostication in coronavirus disease 2019 as well as implications of abnormal pro-B-type natriuretic peptide in the underlying pathophysiology of coronavirus disease 2019-related myocardial injury.
ABSTRACT
OBJECTIVE: Higher mortality in COVID-19 in men compared to women is recognized, but sex differences in cardiovascular events are less well established. We aimed to determine the independent contribution of sex to stroke, myocardial infarction and death in the setting of COVID-19 infection. METHODS: We performed a retrospective cohort study of hospitalized COVID-19 patients in a racially/ethnically diverse population. Clinical features, laboratory markers and clinical events were initially abstracted from medical records, with subsequent clinician adjudication. RESULTS: Of 2060 patients, myocardial injury (32% vs 23%, p = 0.019), acute myocardial infarction (2.7% vs 1.6%, p = 0.114), and ischemic stroke (1.8% vs 0.7%, p = 0.007) were more common in men vs women. In-hospital death occurred in 160 men (15%) vs 117 women (12%, p = 0.091). Men had higher odds of myocardial injury (odds ratio (OR) 2.04 [95% CI 1.43-2.91], p < 0.001), myocardial infarction (1.72 [95% CI 0.93-3.20], p = 0.085) and ischemic stroke (2.76 [95% CI 1.29-5.92], p = 0.009). Despite adjustment for demographics and cardiovascular risk factors, male sex predicted mortality (HR 1.33; 95% CI:1.01-1.74; p = 0.041). While men had significantly higher markers of inflammation, in sex-stratified analyses, increase in interleukin-6, C-reactive protein, ferritin and d-dimer were predictive of mortality and myocardial injury similarly in both sexes. CONCLUSIONS: Adjusted odds of myocardial injury, ischemic stroke and all-cause mortality, but not myocardial infarction, are significantly higher in men compared to women with COVID-19. Higher inflammatory markers are present in men but associated similarly with risk in both men and women. These data suggest that adverse cardiovascular outcomes in men vs. women are independent of cardiovascular comorbidities.