Predicting the outcome of heart failure against chronic-ischemic heart disease in elderly population – Machine learning approach based on logistic regression, case to Villa Scassi hospital Genoa, Italy

Stojanov, Done and Lazarova, Elena and Veljkova, Elena and Rubartelli, Paolo and Giacomini, Mauro (2023) Predicting the outcome of heart failure against chronic-ischemic heart disease in elderly population – Machine learning approach based on logistic regression, case to Villa Scassi hospital Genoa, Italy. Journal of King Saud University - Science, 35 (3). p. 102573. ISSN 1018-3647

Text 1-s2.0-S1018364723000356-main.pdf - Published Version Download (3MB)

Abstract

Totally 167 patients were admitted at cardiology ward in Villa Scassi hospital, Genoa, Italy. We worked with two control groups: heart failure 59 patients (mean age: 71.37 ± 13.27 years) and chronic-ischemic heart disease 108 patients (mean age: 68.85 ± 11.3 years). Nine parameters: Hb, Serum Creatinine, LDL, HDL, Triglycerides, ALT, AST, hs-cTnI, CRP were evaluated onset to hospitalization. We aimed to identify significant independent predictors relative to the outcome of heart failure versus chronic-ischemic heart disease and select combination of biochemical parameters in logistic regression-based model that would provide on average excellent discrimination to the outcome of heart failure versus chronic-ischemic heart disease in elderly population.

Item Type:	Article
Impact Factor Value:	3.829
Subjects:	Natural sciences > Computer and information sciences Medical and Health Sciences > Health sciences
Divisions:	Faculty of Computer Science
Depositing User:	Done Stojanov
Date Deposited:	13 Feb 2023 10:16
Last Modified:	13 Feb 2023 10:16
URI:	https://eprints.ugd.edu.mk/id/eprint/31408

Actions (login required)

View Item