risk score to predict the chances of death for persons with heart failure. Heart failure is a complex clinical syndrome with high mortality rates, the researchers said.
Current risk approaches that capture the biological complexity of the heart failure and show clinical utility are limited, they said.
High-throughput proteomics — a technique for large-scale protein characterisation — could improve risk prediction, but its use in clinical practice to guide the management of patients with heart failure depends on evidence of clinical benefit.
The researchers from the National Institutes of Health in the US developed and validated the protein risk score to stratify mortality risk in persons with heart failure using a community-based group of 7,289 plasma proteins in 1,351 patients with heart failure.
In the research, published in the journal Annals of Internal Medicine, 38 unique proteins were selected for the risk score.
The protein risk score reclassified mortality risk and showed greater clinical utility compared with the clinical model, the researchers said.
These findings foreshadow the clinical utility of large-scale proteomic assays for precision risk prediction in heart failure, they said.
The researchers said this tool may help clinicians select patients with advanced heart failure, at particularly high risk for adverse outcomes, that should be considered for mechanical circulatory support or transplantation.