Cardiolyse Risk of Heart Disorders score predicts heart failure outcomes in the MyoVasc study
Researchers at the University Medical Center of the Johannes Gutenberg University Mainz analysed Holter ECGs from 953 people in the MyoVasc heart failure cohort with Cardiolyse. Of 180 markers, the Risk of Heart Disorders (RoHD) score was the most predictive for worsening of heart failure and all-cause death — and it added information beyond NT-proBNP and the MAGGIC risk score.
Why this study matters
Markers derived from Holter ECGs are known to be associated with clinical outcomes in heart failure. What has been less clear is how much they add when compared with established tools such as the blood marker NT-proBNP or the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score.
The study set out to find the most predictive marker from cloud-based Holter ECG analysis and to test how well it predicts clinical outcomes in people with heart failure.
How the study was done
The work used data from MyoVasc (NCT04064450), a prospective cohort study on heart failure. Participants underwent a highly standardised five-hour examination that included a Holter ECG recording.
- Holter ECG data from 953 participants, 522 of them with symptomatic heart failure
- ECG analysis performed by the cloud-based Cardiolyse platform (Helsinki, Finland)
- 180 ECG markers analysed; elastic-net Cox regression selected the most predictive one for worsening of heart failure and all-cause death
- Links to cardiac structure and function tested with linear regression, adjusted for sex, age, medication and comorbidities
- The selected marker compared with NT-proBNP and the MAGGIC score in multivariable Cox regression models
What the researchers found
Of the 180 markers, the composite parameter Risk of Heart Disorders proved the most predictive for both outcomes. People above the 95th percentile of RoHD had a clearly higher cumulative incidence of worsening heart failure over four years of follow-up.
Linked to heart structure and function
RoHD was related to all three dimensions of cardiac function — systolic, diastolic and strain — and to cardiac structure. A higher score went with lower ejection fraction, impaired strain and diastolic function, and larger, heavier left ventricles.
For worsening of heart failure, RoHD alone reached a C-index of 0.768, compared with 0.766 for NT-proBNP and 0.745 for the MAGGIC score. Combining RoHD with NT-proBNP gave the highest discrimination for both outcomes.
The researchers’ conclusion
“The ECG composite parameter ‘Risk of Heart Disorders’ computed by cardiac analytics platform Cardiolyse is related to the presence of cardiac structural and functional changes in individuals with HF. RoHD carries independent information from established markers NT-proBNP and the MAGGIC risk score for the prediction of clinical outcome in individuals with HF.”
Carstens D.C. et al., University Medical Center Mainz
What it means for Cardiolyse users
RoHD is calculated from the same ECG signal as the rest of the Cardiolyse analysis — no extra test and no extra hardware. This independent study shows that the score reflects real structural and functional changes in the heart and carries prognostic information that complements established heart failure markers.
The score supports, and does not replace, the assessment of a qualified healthcare professional.
About the study. “Clinical relevance of the ‘Risk of Heart Disorders’ Score from a cloud-based analysis of Holter ECG data (Cardiolyse™) for development and progression of heart failure.” Daniel C. Carstens, Noémie Bélanger, Silav Zeid, Konstantin Kontohow-Beckers, Anna Kerber, Fawad Kazemi-Asrar, David Velmeden, Felix Müller, Marc W. Heidorn, Karl J. Lackner, Tommaso Gori, Thomas Münzel, Jürgen H. Prochaska, Wilfried Dinh, Vincent ten Cate and Philipp S. Wild. Poster presented at the D-A-CH Dreiländertreffen Herzinsuffizienz.
The MyoVasc study is funded by the German Center for Cardiovascular Research (DZHK) and the Center for Translational Vascular Biology (CTVB) of the University Medical Center Mainz, with parts of the project funded by Bayer AG and the BMBF. The funding partners did not influence the analyses or the interpretation of the results.
