ArticlePulmonary circulation2022
Improving risk prediction for pulmonary embolism in COVID-19 patients using echocardiography.
Article in Pulmonary circulation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Predicting Acute Cardiovascular Complications in COVID-19: Insights from a Specialized Cardiac Referral Department.Medical science monitor : international medical journal of experimental and clinical research · 2024Article
- Cardiovascular effects of the post-COVID-19 condition.Nature cardiovascular research · 2024Review
- Predictors of pulmonary embolism in hospitalized patients with COVID-19.Thrombosis journal · 2023Article
- Literature Review-Transthoracic Echocardiography, Computed Tomography Angiography, and Their Value in Clinical Decision Making and Outcome Predictions in Patients with COVID-19 Associated Cardiovascular Complications.International journal of environmental research and public health · 2023Review
- Ultrasound during the COVID-19 Pandemic: A Global Approach.Journal of clinical medicine · 2023Review
- Improving risk prediction for pulmonary embolism in COVID-19 patients using echocardiography.Pulmonary circulation · 2022Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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
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Registered trials
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