Machine learning and LACE index for predicting 30-day readmissions after heart failure hospitalization in elderly patients-Reference-Cited by-同舟云学术

Machine learning and LACE index for predicting 30-day readmissions after heart failure hospitalization in elderly patients

Published:2022-06-04 Issue:6 Volume:17 Page:1727-1737
ISSN:1828-0447
Container-title:Internal and Emergency Medicine
language:en
Short-container-title:Intern Emerg Med

Author:

Polo Friz Hernan^ORCID,Esposito Valentina,Marano Giuseppe,Primitz Laura,Bovio Alice,Delgrossi Giovanni,Bombelli Michele,Grignaffini Guido,Monza Giovanni,Boracchi Patrizia

Publisher

Springer Science and Business Media LLC

Subject

Emergency Medicine,Internal Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11739-022-02996-w.pdf

Reference35 articles.

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2. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS et al (2016) ESC guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J 2015:ehw128

3. Bergethon K, Ju C, De Vore A, Hardy NC, Fonarow GC, Yancy CW, Heidenreich PA, Bhatt DL, Peterson ED, Hernandez AF (2016) Trends in 30-day readmission rates for patients hospitalized with heart failure. Circulation. 9:e002594. https://doi.org/10.1161/CIRCHEARTFAILURE.115.002594 (originally published June 14, 2016)

4. Ponikowski P, Anker SD, AlHabib KF, Cowie MR, Force TL, Hu S et al (2014) Heart failure: preventing disease and death worldwide. ESC Hear Fail 1:4–25

5. Ambrosy AP, Fonarow GC, Butler J, Chioncel O, Greene SJ, Vaduganathan M et al (2014) The global health and economic burden of hospitalizations for heart failure: lessons learned from hospitalized heart failure registries. J Am Coll Cardiol Elsevier Inc 63:1123–1133. https://doi.org/10.1016/j.jacc.2013.11.053

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