A machine learning-based lung ultrasound algorithm for the diagnosis of acute heart failure
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11739-024-03627-2.pdf
Reference42 articles.
1. McDonagh TA, Metra M, Adamo M, Gardner RS, Baumbach A, Böhm M et al (2021) 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 42(36):3599–3726. https://doi.org/10.1093/eurheartj/ehab368
2. Chioncel O, Mebazaa A, Harjola VP, Coats AJ, Piepoli MF, Crespo-Leiro MG et al (2017) Clinical phenotypes and outcome of patients hospitalized for acute heart failure: the ESC Heart Failure Long-Term Registry. Eur J Heart Fail 19(10):1242–1254. https://doi.org/10.1002/ejhf.890
3. Platz E, Jhund PS, Girerd N, Pivetta E, McMurray JJV, Peacock WF et al (2019) Expert consensus document: reporting checklist for quantification of pulmonary congestion by lung ultrasound in heart failure. Eur J Heart Fail 21(7):844–851. https://doi.org/10.1002/ejhf.1499
4. Kobayashi M, Gargani L, Palazzuoli A, Ambrosio G, Bayés-Genis A, Lupon J et al (2021) Association between right-sided cardiac function and ultrasound-based pulmonary congestion on acutely decompensated heart failure: findings from a pooled analysis of four cohort studies. Clin Res Cardiol 110(8):1181–1192. https://doi.org/10.1007/s00392-020-01724-8
5. Chouihed T, Coiro S, Zannad F, Girerd N (2016) Lung ultrasound: a diagnostic and prognostic tool at every step in the pathway of care for acute heart failure. Am J Emerg Med 34(3):656–657. https://doi.org/10.1016/j.ajem.2015.12.030
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