

A novel protein risk score created to predict the probability of death in people with heart failure (HF) has shown satisfactory calibration and may assist doctors in better stratifying mortality risk in these patients. Annals of Internal Medicine published the score.
Heart failure is a complex clinical illness that is associated with a high mortality rate. Current risk classification techniques are restricted in their ability to represent the molecular complexity of the HF condition while also demonstrating therapeutic value. Although high-throughput proteomics has the potential to improve risk prediction, its use in clinical practice to assist the management of patients with heart failure is dependent on validation and proof of clinical benefit.
Using a community-based cohort of 7,289 plasma proteins from 1,351 patients with heart condition, researchers from the National Institutes of Health developed and validated a protein risk score to stratify mortality risk in people with heart failure.
For the protein risk score, 38 distinct proteins were chosen from the development cohort. When compared to the clinical model, the protein risk score revealed better calibration, reclassified mortality risk, particularly at the extremes of the risk distribution, and demonstrated improved clinical value.
These findings, according to the researchers, anticipate the clinical relevance of large-scale proteomic assays for precision risk prediction in HF. This tool may assist doctors in identifying candidates for quick drug titration or patients with advanced HF who are at high risk of severe outcomes and should be considered for mechanical circulatory support or transplantation.
For more information: Development and Validation of a Protein Risk Score for Mortality in Heart Failure, Annals of Internal Medicine
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