Clinical Outcomes and Predictors of Long-Term Survival in Patients With and Without Previously Known Extracardiac Sarcoidosis Using Machine Learning: A Swedish Multicenter Study

Background Cardiac involvement can be an initial manifestation in sarcoidosis. However, little is known about the association between various clinical phenotypes of cardiac sarcoidosis (CS) and outcomes. We aimed to analyze the relation of different clinical manifestations with outcomes of CS and to...

Full description

Saved in:
Bibliographic Details
Published in:Journal of the American Heart Association 2023-08, Vol.12 (15), p.e029481-e029481
Main Authors: Bobbio, Emanuele, Eldhagen, Per, Polte, Christian L, Hjalmarsson, Clara, Karason, Kristjan, Rawshani, Araz, Darlington, Pernilla, Kullberg, Susanna, Sörensson, Peder, Bergh, Niklas, Bollano, Entela
Format: Article
Language:English
Subjects:
Cardiac and Cardiovascular Systems
cardiac sarcoidosis
Cardiomyopathies
endomyocardial biopsy
epidemiology
heart failure
Humans
inflammatory heart disease
Kardiologi
Left
machine learning
Medicin och hälsovetenskap
Original Research
Retrospective Studies
Right
right ventricular function
Sarcoidosis
Stroke Volume
Sweden
Ventricular Dysfunction
Ventricular Function
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Background Cardiac involvement can be an initial manifestation in sarcoidosis. However, little is known about the association between various clinical phenotypes of cardiac sarcoidosis (CS) and outcomes. We aimed to analyze the relation of different clinical manifestations with outcomes of CS and to investigate the relative importance of clinical features influencing overall survival. Methods and Results A retrospective cohort of 141 patients with CS enrolled at 2 Swedish university hospitals was studied. Presentation, imaging studies, and outcomes of de novo CS and previously known extracardiac sarcoidosis were compared. Survival free of primary composite outcome (ventricular arrhythmias, heart transplantation, or death) was assessed. Machine learning algorithm was used to study the relative importance of clinical features in predicting outcome. Sixty-two patients with de novo CS and 79 with previously known extracardiac sarcoidosis were included. De novo CS showed more advanced New York Heart Association class ( =0.02), higher circulating levels of NT-proBNP (N-terminal pro-B-type natriuretic peptide) (
ISSN:2047-9980
2047-9980
DOI:10.1161/JAHA.123.029481