Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography
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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Pulmonary Circulation |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/pul2.12036 |
| _version_ | 1828172341822095360 |
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| author | Monika A. Satoskar Thomas Metkus Alborz Soleimanifard Julie K. Shade Natalia A. Trayanova Erin D. Michos Monica Mukherjee Madeline Schiminger Wendy S. Post Allison G. Hays |
| author_facet | Monika A. Satoskar Thomas Metkus Alborz Soleimanifard Julie K. Shade Natalia A. Trayanova Erin D. Michos Monica Mukherjee Madeline Schiminger Wendy S. Post Allison G. Hays |
| author_sort | Monika A. Satoskar |
| collection | DOAJ |
| description | 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 χ2 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. |
| first_indexed | 2024-04-12T03:38:42Z |
| format | Article |
| id | doaj.art-3664d6ef90cb455d8f4dae8d5e7ddf56 |
| institution | Directory Open Access Journal |
| issn | 2045-8940 |
| language | English |
| last_indexed | 2024-04-12T03:38:42Z |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Pulmonary Circulation |
| spelling | doaj.art-3664d6ef90cb455d8f4dae8d5e7ddf562022-12-22T03:49:20ZengWileyPulmonary Circulation2045-89402022-01-01121n/an/a10.1002/pul2.12036Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiographyMonika A. Satoskar0Thomas Metkus1Alborz Soleimanifard2Julie K. Shade3Natalia A. Trayanova4Erin D. Michos5Monica Mukherjee6Madeline Schiminger7Wendy S. Post8Allison G. Hays9Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USADepartment of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USADivision of Cardiology Johns Hopkins School of Medicine Baltimore Maryland USADepartment of Biomedical Engineering and Medicine Johns Hopkins Baltimore Maryland USADepartment of Biomedical Engineering and Medicine Johns Hopkins Baltimore Maryland USADepartment of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USADivision of Cardiology Johns Hopkins School of Medicine Baltimore Maryland USADivision of Cardiology The Johns Hopkins Hospital Baltimore Maryland USADepartment of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore Maryland USADivision of Cardiology Johns Hopkins School of Medicine Baltimore Maryland USAAbstract 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 χ2 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.https://doi.org/10.1002/pul2.12036cardiac biomarkersD‐dimerprediction modelingright ventricular dysfunction |
| spellingShingle | Monika A. Satoskar Thomas Metkus Alborz Soleimanifard Julie K. Shade Natalia A. Trayanova Erin D. Michos Monica Mukherjee Madeline Schiminger Wendy S. Post Allison G. Hays Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography Pulmonary Circulation cardiac biomarkers D‐dimer prediction modeling right ventricular dysfunction |
| title | Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography |
| title_full | Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography |
| title_fullStr | Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography |
| title_full_unstemmed | Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography |
| title_short | Improving risk prediction for pulmonary embolism in COVID‐19 patients using echocardiography |
| title_sort | improving risk prediction for pulmonary embolism in covid 19 patients using echocardiography |
| topic | cardiac biomarkers D‐dimer prediction modeling right ventricular dysfunction |
| url | https://doi.org/10.1002/pul2.12036 |
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