Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling.

ABSTRACT:

Aims

Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), increasing symptom burden and stroke risk. We aimed to construct a plasma proteomics-based model to predict new-onset AF in patients with HCM and determine dysregulated signalling pathways.

Methods and results

In this prospective, multi-centre cohort study, we conducted plasma proteomics profiling of 4986 proteins at enrolment. We developed a proteomics-based machine learning model to predict new-onset AF using samples from one institution (training set) and tested its predictive ability using independent samples from another institution (test set). We performed a survival analysis to compare the risk of new-onset AF among high- and low-risk groups in

SUBMITTER: Lumish HS 

PROVIDER: S-EPMC11542585 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature