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Predictive Accuracy of HeartMate 3 Risk Score After the Heart Transplant Allocation Change
Justin D Vincent1, Alyssa Ramsay2, David S Lambert1
1From the Department of Medicine, Washington University School of Medicine, Saint Louis, Missouri.
Insights
The HeartMate 3 risk score (HM3RS) needs updating. It did not accurately predict patient outcomes after left ventricular assist device implantation in a real-world setting.
Area of Science:
- Cardiology
- Medical Devices
- Outcomes Research
Background:
- The HeartMate 3 risk score (HM3RS) was developed to predict mortality after left ventricular assist device (LVAD) implantation.
- Validation in real-world populations, particularly after recent changes to heart transplant allocation, is lacking.
Purpose of the Study:
- To validate the HM3RS in a contemporary, real-world population.
- To assess the score's predictive accuracy for 1- and 2-year outcomes post-LVAD implantation.
Main Methods:
- Multicenter retrospective analysis of patients receiving HeartMate 3 LVAD.
- Evaluation of HM3RS performance in predicting 1- and 2-year mortality.
Main Results:
- The HM3RS did not accurately predict 1- and 2-year outcomes in the contemporary real-world cohort.
- The score's predictive utility appears diminished in the current clinical landscape.
Conclusions:
- The HM3RS requires revision to accurately reflect outcomes in the current era.
- A new risk prediction tool is needed for patients receiving HeartMate 3 LVADs.
Abstract:
The HeartMate 3 risk score (HM3RS) was developed from the Multicenter Study of MagLev Technology in Patients Undergoing Mechanical Circulatory Support Therapy with HeartMate 3 (MOMENTUM 3) clinical trial to predict 1 and 2 year mortality after left ventricular assist device implantation. However, it has not been validated in a real-world population, especially after the heart transplant allocation system change on October 18, 2018. In this multicenter retrospective analysis, we found that HM3RS did not predict 1 and 2 year outcomes in the contemporary era, highlighting the need to revise this risk prediction tool in the real-world setting.
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