Articles of Interest: Interactive Chest Pain Tools, CMR Imaging Biomarkers, and RBM20

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Abstract image of an artificial neural network creating a heart

Interactive Tool for New Chest Pain Guidelines

You may have read one of our earlier posts about the new 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain. If not, you can find it here. The guideline plays a vital role in chest pain evaluation; however, it can be cumbersome to review each time an unfamiliar situation arises. Thankfully, the Journal of the American College of Cardiology (JACC) has published an interactive tool to help you efficiently “determine patient risk (low, intermediate, high) and appropriate subsequent testing in patients presenting with chest pain”.

Improving Clinical Adoption of CMR Imaging Biomarkers Using Machine Learning

Seraphim et al recently published an article in JACC on the prognostic value of pulmonary transit time (PTT) and indexed pulmonary blood volume (PBV) for major adverse non-fatal cardiac events (MACE). Previous research has demonstrated that PTT and PBV are correlated with various disease states and prognostic biomarkers. However, challenges in acquisition and analysis of PTT and PBV have prevented wide-scale clinical adoption. In this study, Seraphim et al demonstrate that a fully automated machine learning approach can be used to estimate PTT and PBV in line. Furthermore, using data from 985 patients, the study shows that PTT and PBV are predictive of MACE but not all-cause mortality.

This study is a great example of how machine learning algorithms could help increase adoption of new prognostic biomarkers in clinical decision making.

Read the full article here

These biomarkers may offer additional insights into cardiopulmonary function beyond conventional predictors including ejection fraction.

Discovery of New Genetic Association Between RBM20 and Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is responsible for most sudden cardiac deaths (SCDs) of adolescents and young adults. While we know that HCM is caused by genetic variants in cardiac sarcomere protein genes 60% of the time, no genes have been identified for the remaining population. This month in the Canadian Journal of Cardiology, Dai et al showed that gene-encoding RNSA binding motif protein 20 (RBM20), a causal gene for dilated cardiomyopathy, is associated with a SCA and may also have a causal relationship with hypertrophic cardiomyopathy.

This work furthers our knowledge of the genetic origins of HCM and also elucidates the increased risk of SCA for patients with RBM20 variants. Early identification and adequate surveillance of these patients for life-threatening arrhythmias could be considered in future management strategies.

Read the full article here

There was a higher prevalence of [sudden cardiac arrest] SCA and resuscitation (6.7% vs 0.9%, P = 0.001).
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