FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3047391569> ?p ?o ?g. }

• W3047391569 abstract "Background: Identification of systolic heart failure among patients presenting to the emergency department (ED) with acute dyspnea is challenging. The reasons for dyspnea are often multifactorial. A focused physical evaluation and diagnostic testing can lack sensitivity and specificity. The objective of this study was to assess the accuracy of an artificial intelligence-enabled ECG to identify patients presenting with dyspnea who have left ventricular systolic dysfunction (LVSD). Methods: We retrospectively applied a validated artificial intelligence-enabled ECG algorithm for the identification of LVSD (defined as LV ejection fraction ≤35%) to a cohort of patients aged ≥18 years who were evaluated in the ED at a Mayo Clinic site with dyspnea. Patients were included if they had at least one standard 12-lead ECG acquired on the date of the ED visit and an echocardiogram performed within 30 days of presentation. Patients with prior LVSD were excluded. We assessed the model performance using area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Results: A total of 1606 patients were included. Median time from ECG to echocardiogram was 1 day (Q1: 1, Q3: 2). The artificial intelligence-enabled ECG algorithm identified LVSD with an area under the receiver operating characteristic curve of 0.89 (95% CI, 0.86–0.91) and accuracy of 85.9%. Sensitivity, specificity, negative predictive value, and positive predictive value were 74%, 87%, 97%, and 40%, respectively. To identify an ejection fraction <50%, the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were 0.85 (95% CI, 0.83–0.88), 86%, 63%, and 91%, respectively. NT-proBNP (N-terminal pro-B-type natriuretic peptide) alone at a cutoff of >800 identified LVSD with an area under the receiver operating characteristic curve of 0.80 (95% CI, 0.76–0.84). Conclusions: The ECG is an inexpensive, ubiquitous, painless test which can be quickly obtained in the ED. It effectively identifies LVSD in selected patients presenting to the ED with dyspnea when analyzed with artificial intelligence and outperforms NT-proBNP. Graphic Abstract: A graphic abstract is available for this article." @default.
• W3047391569 created "2020-08-10" @default.
• W3047391569 creator A5001963115 @default.
• W3047391569 creator A5002058719 @default.
• W3047391569 creator A5008299307 @default.
• W3047391569 creator A5012240258 @default.
• W3047391569 creator A5020289692 @default.
• W3047391569 creator A5023936819 @default.
• W3047391569 creator A5028294867 @default.
• W3047391569 creator A5043658621 @default.
• W3047391569 creator A5068603678 @default.
• W3047391569 creator A5074046901 @default.
• W3047391569 creator A5080731060 @default.
• W3047391569 creator A5084472773 @default.
• W3047391569 date "2020-08-01" @default.
• W3047391569 modified "2023-10-14" @default.
• W3047391569 title "Artificial Intelligence-Enabled ECG Algorithm to Identify Patients With Left Ventricular Systolic Dysfunction Presenting to the Emergency Department With Dyspnea" @default.
• W3047391569 cites W1557993121 @default.
• W3047391569 cites W1608429456 @default.
• W3047391569 cites W1988816170 @default.
• W3047391569 cites W1996241129 @default.
• W3047391569 cites W2036436069 @default.
• W3047391569 cites W2038813835 @default.
• W3047391569 cites W2039936689 @default.
• W3047391569 cites W2042571564 @default.
• W3047391569 cites W2070247508 @default.
• W3047391569 cites W2074932603 @default.
• W3047391569 cites W2080749874 @default.
• W3047391569 cites W2096254491 @default.
• W3047391569 cites W2100163053 @default.
• W3047391569 cites W2105961226 @default.
• W3047391569 cites W2109723367 @default.
• W3047391569 cites W2119340816 @default.
• W3047391569 cites W2124624517 @default.
• W3047391569 cites W2127301322 @default.
• W3047391569 cites W2132436071 @default.
• W3047391569 cites W2135422127 @default.
• W3047391569 cites W2160371911 @default.
• W3047391569 cites W2169036009 @default.
• W3047391569 cites W2169243823 @default.
• W3047391569 cites W2215874248 @default.
• W3047391569 cites W2292493149 @default.
• W3047391569 cites W2328176404 @default.
• W3047391569 cites W2394990307 @default.
• W3047391569 cites W2473761043 @default.
• W3047391569 cites W2765199849 @default.
• W3047391569 cites W2790317409 @default.
• W3047391569 cites W2886290726 @default.
• W3047391569 cites W2891676555 @default.
• W3047391569 cites W2898291481 @default.
• W3047391569 cites W2901226889 @default.
• W3047391569 cites W2913730011 @default.
• W3047391569 cites W2919098904 @default.
• W3047391569 cites W2920799198 @default.
• W3047391569 cites W2923923482 @default.
• W3047391569 cites W2964795278 @default.
• W3047391569 cites W2966052071 @default.
• W3047391569 cites W2985220169 @default.
• W3047391569 cites W3184177771 @default.
• W3047391569 doi "https://doi.org/10.1161/circep.120.008437" @default.
• W3047391569 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32986471" @default.
• W3047391569 hasPublicationYear "2020" @default.
• W3047391569 type Work @default.
• W3047391569 sameAs 3047391569 @default.
• W3047391569 citedByCount "70" @default.
• W3047391569 countsByYear W30473915692020 @default.
• W3047391569 countsByYear W30473915692021 @default.
• W3047391569 countsByYear W30473915692022 @default.
• W3047391569 countsByYear W30473915692023 @default.
• W3047391569 crossrefType "journal-article" @default.
• W3047391569 hasAuthorship W3047391569A5001963115 @default.
• W3047391569 hasAuthorship W3047391569A5002058719 @default.
• W3047391569 hasAuthorship W3047391569A5008299307 @default.
• W3047391569 hasAuthorship W3047391569A5012240258 @default.
• W3047391569 hasAuthorship W3047391569A5020289692 @default.
• W3047391569 hasAuthorship W3047391569A5023936819 @default.
• W3047391569 hasAuthorship W3047391569A5028294867 @default.
• W3047391569 hasAuthorship W3047391569A5043658621 @default.
• W3047391569 hasAuthorship W3047391569A5068603678 @default.
• W3047391569 hasAuthorship W3047391569A5074046901 @default.
• W3047391569 hasAuthorship W3047391569A5080731060 @default.
• W3047391569 hasAuthorship W3047391569A5084472773 @default.
• W3047391569 hasBestOaLocation W30473915691 @default.
• W3047391569 hasConcept C11413529 @default.
• W3047391569 hasConcept C118552586 @default.
• W3047391569 hasConcept C119857082 @default.
• W3047391569 hasConcept C126322002 @default.
• W3047391569 hasConcept C164705383 @default.
• W3047391569 hasConcept C198433322 @default.
• W3047391569 hasConcept C2778198053 @default.
• W3047391569 hasConcept C2780724011 @default.
• W3047391569 hasConcept C41008148 @default.
• W3047391569 hasConcept C58471807 @default.
• W3047391569 hasConcept C71924100 @default.
• W3047391569 hasConcept C72563966 @default.
• W3047391569 hasConcept C76318530 @default.
• W3047391569 hasConcept C78085059 @default.
• W3047391569 hasConceptScore W3047391569C11413529 @default.
• W3047391569 hasConceptScore W3047391569C118552586 @default.
• W3047391569 hasConceptScore W3047391569C119857082 @default.

• next