Heart failure & cardiomyopathiesCohort study
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling
- Prospective cohort study
- multicentre
- proteomics-based machine learning prediction model
- independent test set
- Plasma proteomics profiling of 4986 proteins at enrolment
Authors' conclusion
This is the first study to demonstrate the ability of plasma proteomics to predict new-onset AF in HCM and identify dysregulated signalling pathways.
Study context
- Population
- Patients with hypertrophic cardiomyopathy (HCM)training set 193, test set 91
- Participants
- 284 patients
- Exposure
- Proteomics-based high-risk vs low-risk classification
- Outcome
- New-onset AF
- Follow-up
- Median 3.2 years [25-75 percentile: 1.8-5.2]
Main finding
As reported in the abstract
Prediction of new-onset AF (test set)
AUC of proteomics-based model in test set
0.89 (95% CI 0.78-0.99)
Patients developing atrial fibrillation (AF)
Thirty-seven (13%)
Observational data: associations, not effects.
Further findings
Pathway analysis
- Ras-MAPK pathway dysregulated in patients who developed incident AF
- False discovery rate (FDR) < 1.0 × 10-6
Original publication
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using plasma proteomics profiling. Europace. Published 23 October 2024. doi:10.1093/europace/euae267
Summarised from the published abstract; every number is checked against it