RESUMO
Advanced stage heart failure patients can benefit from the unloading effects of an implantable left ventricular assist device. Despite best clinical practice, LVADs are associated with adverse events, such as pump thrombosis (PT). An adaptive algorithm alerting when an individual's appropriate levels in pump power uptake are exceeded, such as in the case of PT, can improve therapy of patients implanted with a centrifugal LVAD. We retrospectively studied 75 patients implanted with a centrifugal LVAD in a single center. A previously optimized adaptive pump power-tracking algorithm was compared to clinical best practice and clinically available constant threshold algorithms. Algorithm performances were analyzed in a PT group (n = 16 patients with 30 PT events) and a thoroughly selected control group (n = 59 patients, 34.7 patient years of LVAD data). Comparison of the adaptive power-tracking algorithm with the best performing constant threshold algorithm resulted in sensitivity of 83.3% vs. 86.7% and specificity of 98.9% vs. 95.3%, respectively. The power-tracking algorithm produced one false positive detection every 11.6 patient years and early warnings with a median of 3.6 days prior to PT diagnosis. In conclusion, a retrospective single-center validation study with real-world patient data demonstrated advantageous application of a power-tracking algorithm into LVAD systems and clinical practice.
RESUMO
Logfiles from the HeartWare HVAD System provide operational pump trend data to aid in patient management. Pump thrombosis is commonly associated with increases in the logfile power that may precede the clinical presentation. A Power Tracking algorithm was developed to detect significant deviations in pump power that may be associated with pump thrombus (PT). The Power Tracking algorithm was applied retrospectively to logfiles captured in the ENDURANCE, ENDURANCE Supplemental, and LATERAL clinical trials. From a combined dataset of 896 patients, available logfiles with suspected PT (n = 70 events in 60 patients) and available logfiles from patients without adverse events (AEs) (n = 106 patients, consisting of 27.4 patient-years of monitoring) were organized into two cohorts. The Power Tracking algorithm detected PT cases on or before the recorded AE date with a sensitivity of 85.7%, with detection occurring an average of 3.9 days before clinical presentation. The algorithm averaged one false alarm for every 6.85 patient-years of monitoring from logfiles without AEs. The favorable performance of the Power Tracking algorithm may enable earlier detection of pump thrombosis and allow early medical management versus surgical intervention.
