The Diastolic Dominance Index (AUC 0.83-0.87) combined with pump power achieved >90% accuracy for detecting aortic insufficiency in HeartMate 3 devices at 5,000 and 6,000 rpm pump speeds.
Does the Diastolic Dominance Index accurately detect aortic insufficiency in simulated HeartMate 3 profiles compared to established Doppler markers?
The Diastolic Dominance Index, especially when combined with pump power, provides a speed-robust and accurate method for grading aortic insufficiency during HeartMate 3 support in a simulated model.
Absolute Event Rate: 0% vs 0%
Aortic insufficiency (AI) is a progressive complication of continuous-flow left ventricular assist device support and remains inconsistently graded during HeartMate 3 (HM3) therapy. Using a closed-loop cardiovascular simulation, we analyzed 2,312 physiologically screened HM3 profiles at pump speeds of 5,000 and 6,000 rpm to evaluate Doppler-based approaches for AI detection, defined by regurgitant fraction of greater than or equal to 30%. Established Doppler markers, including systolic-to-diastolic ratio (S/D), diastolic acceleration, and diastolic flow fraction (DFF), were compared with a derived Diastolic Dominance Index (DDI), which integrates systolic attenuation and diastolic predominance into a single metric. Systolic-to-diastolic ratio demonstrated strong discrimination (area under the receiver-operating characteristic curve AUC: 0.93 at 5,000 RPM; 0.86 at 6,000 RPM). Diastolic Dominance Index showed comparable performance (AUC: 0.87 and 0.83) and exhibited more stable discrimination across pump speeds, while providing a zero-centered index in which positive values indicate AI severity. Pump power alone was nondiagnostic, but in cases near the DDI decision boundary, it improved classification, achieving an AUC of 0.93 at 6,000 RPM. Simple rule-based combinations of DDI and power achieved greater than 90% accuracy at both speeds. By unifying established Doppler features into a single physiologic index and pairing it with an energetic adjudicator, this framework enables speed-robust, reproducible, and clinically interpretable AI grading during HM3 support. https://links.lww.com/ASAIO/B917
Persaud et al. (Fri,) reported a other. The Diastolic Dominance Index (AUC 0.83-0.87) combined with pump power achieved >90% accuracy for detecting aortic insufficiency in HeartMate 3 devices at 5,000 and 6,000 rpm pump speeds.