Mortality Prediction in Patients With or Without Heart Failure Using a Machine Learning Model

Se Yong Jang; Jin Joo Park; Eric Adler; Emily Eshraghian; Faraz S Ahmad; Claudio Campagnari; Avi Yagil; Barry Greenberg

doi:10.1016/j.jacadv.2023.100554

Mortality Prediction in Patients With or Without Heart Failure Using a Machine Learning Model

JACC Adv. 2023 Aug 22;2(7):100554. doi: 10.1016/j.jacadv.2023.100554. eCollection 2023 Sep.

Authors

Se Yong Jang^{1

2}, Jin Joo Park^{1

3}, Eric Adler¹, Emily Eshraghian¹, Faraz S Ahmad^{4

5}, Claudio Campagnari⁶, Avi Yagil^{1

7}, Barry Greenberg¹

Affiliations

¹ Department of Cardiology, University of California, San Diego, California, USA.
² Division of Cardiology, Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
³ Division of Cardiology, Department of Internal Medicine, Cardiovascular Center, Seoul National University Bundang Hospital, Seoul, Republic of Korea.
⁴ Division of Cardiology, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
⁵ Bluhm Cardiovascular Institute Center for Artificial Intelligence in Cardiovascular Medicine, Northwestern Medicine, Chicago, Illinois, USA.
⁶ Physics Department, University of California, Santa Barbara, California, USA.
⁷ Physics Department, University of California, San Diego, California, USA.

Abstract

Background: Most risk prediction models are confined to specific medical conditions, thus limiting their application to general medical populations.

Objectives: The MARKER-HF (Machine learning Assessment of RisK and EaRly mortality in Heart Failure) risk model was developed in heart failure (HF) patients. We assessed the ability of MARKER-HF to predict 1-year mortality in a large community-based hospital registry database including patients with and without HF.

Methods: This study included 41,749 consecutive patients who underwent echocardiography in a tertiary referral hospital (4,640 patients with and 37,109 without HF). Patients without HF were further subdivided into those with (n = 22,946) and without cardiovascular disease (n = 14,163) and also into cohorts based on recent acute coronary syndrome or history of atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, diabetes mellitus, hypertension, or malignancy.

Results: The median age of the 41,749 patients was 65 years, and 56.2% were male. The receiver operated area under the curves for MARKER-HF prediction of 1-year mortality of patients with HF was 0.729 (95% CI: 0.706-0.752) and for patients without HF was 0.770 (95% CI: 0.760-0.780). MARKER-HF prediction of mortality was consistent across subgroups with and without cardiovascular disease and in patients diagnosed with acute coronary syndrome, atrial fibrillation, chronic obstructive pulmonary disease, chronic kidney disease, diabetes mellitus, or hypertension. Patients with malignancy demonstrated higher mortality at a given MARKER-HF score than did patients in the other groups.

Conclusions: MARKER-HF predicts mortality for patients with HF as well as for patients suffering from a variety of diseases.

Keywords: MARKER-HF; heart failure; mortality; risk score.