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Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients
Cardiovascular risk factors, biomarkers, and diseases are associated with poor prognosis in COVID-19 infections. Significant progress in artificial intelligence (AI) applied to cardiac imaging has recently been made. We assessed the utility of AI analytic software EchoGo in COVID-19 inpatients. Fift...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501328/ https://www.ncbi.nlm.nih.gov/pubmed/36143448 http://dx.doi.org/10.3390/life12091413 |
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author | Wang, Tom Kai Ming Cremer, Paul C. Chan, Nicholas Piotrowska, Hania Woodward, Gary Jaber, Wael A. |
author_facet | Wang, Tom Kai Ming Cremer, Paul C. Chan, Nicholas Piotrowska, Hania Woodward, Gary Jaber, Wael A. |
author_sort | Wang, Tom Kai Ming |
collection | PubMed |
description | Cardiovascular risk factors, biomarkers, and diseases are associated with poor prognosis in COVID-19 infections. Significant progress in artificial intelligence (AI) applied to cardiac imaging has recently been made. We assessed the utility of AI analytic software EchoGo in COVID-19 inpatients. Fifty consecutive COVID-19+ inpatients (age 66 ± 13 years, 22 women) who had echocardiography in 4/17/2020–8/5/2020 were analyzed with EchoGo software, with output correlated against standard echocardiography measurements. After adjustment for the APACHE-4 score, associations with clinical outcomes were assessed. Mean EchoGo outputs were left ventricular end-diastolic volume (LVEDV) 121 ± 42 mL, end-systolic volume (LVESV) 53 ± 30 mL, ejection fraction (LVEF) 58 ± 11%, and global longitudinal strain (GLS) −16.1 ± 5.1%. Pearson correlation coefficients (p-value) with standard measurements were 0.810 (<0.001), 0.873 (<0.001), 0.528 (<0.001), and 0.690 (<0.001). The primary endpoint occurred in 26 (52%) patients. Adjusting for APACHE-4 score, EchoGo LVEF and LVGLS were associated with the primary endpoint, odds ratios (95% confidence intervals) of 0.92 (0.85–0.99) and 1.22 (1.03–1.45) per 1% increase, respectively. Automated AI software is a new clinical tool that may assist with patient care. EchoGo LVEF and LVGLS were associated with adverse outcomes in hospitalized COVID-19 patients and can play a role in their risk stratification. |
format | Online Article Text |
id | pubmed-9501328 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95013282022-09-24 Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients Wang, Tom Kai Ming Cremer, Paul C. Chan, Nicholas Piotrowska, Hania Woodward, Gary Jaber, Wael A. Life (Basel) Communication Cardiovascular risk factors, biomarkers, and diseases are associated with poor prognosis in COVID-19 infections. Significant progress in artificial intelligence (AI) applied to cardiac imaging has recently been made. We assessed the utility of AI analytic software EchoGo in COVID-19 inpatients. Fifty consecutive COVID-19+ inpatients (age 66 ± 13 years, 22 women) who had echocardiography in 4/17/2020–8/5/2020 were analyzed with EchoGo software, with output correlated against standard echocardiography measurements. After adjustment for the APACHE-4 score, associations with clinical outcomes were assessed. Mean EchoGo outputs were left ventricular end-diastolic volume (LVEDV) 121 ± 42 mL, end-systolic volume (LVESV) 53 ± 30 mL, ejection fraction (LVEF) 58 ± 11%, and global longitudinal strain (GLS) −16.1 ± 5.1%. Pearson correlation coefficients (p-value) with standard measurements were 0.810 (<0.001), 0.873 (<0.001), 0.528 (<0.001), and 0.690 (<0.001). The primary endpoint occurred in 26 (52%) patients. Adjusting for APACHE-4 score, EchoGo LVEF and LVGLS were associated with the primary endpoint, odds ratios (95% confidence intervals) of 0.92 (0.85–0.99) and 1.22 (1.03–1.45) per 1% increase, respectively. Automated AI software is a new clinical tool that may assist with patient care. EchoGo LVEF and LVGLS were associated with adverse outcomes in hospitalized COVID-19 patients and can play a role in their risk stratification. MDPI 2022-09-10 /pmc/articles/PMC9501328/ /pubmed/36143448 http://dx.doi.org/10.3390/life12091413 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Wang, Tom Kai Ming Cremer, Paul C. Chan, Nicholas Piotrowska, Hania Woodward, Gary Jaber, Wael A. Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients |
title | Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients |
title_full | Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients |
title_fullStr | Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients |
title_full_unstemmed | Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients |
title_short | Utility of an Automated Artificial Intelligence Echocardiography Software in Risk Stratification of Hospitalized COVID-19 Patients |
title_sort | utility of an automated artificial intelligence echocardiography software in risk stratification of hospitalized covid-19 patients |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9501328/ https://www.ncbi.nlm.nih.gov/pubmed/36143448 http://dx.doi.org/10.3390/life12091413 |
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