Prevention of thrombus formation in blood pump by mechanical circular orbital excitation of impeller in magnetically levitated centrifugal pump

BACKGROUND

Mechanical circulatory support devices, such as left ventricular assist devices, have recently been used in patients with heart failure as destination therapy but the formation of thrombus in blood pumps remains a critical problem. In this study, we propose a mechanical antithrombogenic method by impeller excitation using a magnetically levitated (Maglev) centrifugal pump. Previous studies have shown that one-directional excitation prevents thrombus; however, it is effective in only one direction. In this study, we aimed to obtain a better effect by vibrating it in a circular orbit to induce uniform changes in the shear-rate field entirely around the impeller.

METHODS

The blood coagulation time was compared using porcine blood. (1) The flow rate was set to 1 L/min, and applied excitation was at a frequency of 280 Hz and amplitude of 3 μm. (2) Moreover, the effect was compared by varying the frequency, amplitude, and direction of the excitation. In this experiment, the flow rate was set to 0.3 L/min.

RESULTS

(1) The thrombus formation time was 77 min without excitation and 133 min with excitation, which was 1.7 times longer. (2) The results showed no difference between (280 Hz, 3 μm) and (50 Hz, 16 μm) circular orbital excitations, and no directional difference, with thrombus formation of 2.5 times longer under all conditions than that without excitation.

CONCLUSION

In the case of simple reciprocating excitation, the time was approximately 1.2 times longer. This indicated that the circular orbital excitation is more effective.

Evaluating medical device adverse event signals using a likelihood ratio test method

Signal detection methods have been used extensively in post-market surveillance to identify elevated risks of adverse events. However, these statistical methods have not been widely used in detecting AE signals for medical devices. In this paper, we focused on the use of a likelihood ratio test (LRT)-based method in identifying adverse event (AE) signals associated with left ventricular assist devices (LVADs) using Medical Device Reporting (MDR) data. Among 110,927 adverse event entries identified in MDR data for LVADs, the LRT method detected 18 AE signals which included seven bleeding-related AEs such as hemolysis, thrombosis, hematuria, thrombus, blood loss, and hemorrhage. The LRT method was also applied to longitudinal data from 2007 to 2019 where a monotone alpha-spending function was used to ensure the control of type I error at each look and overall for trend analysis. Furthermore, the LRT method was compared to proportional reporting ratios (PRRs), Bayesian confidence propagation neural network (BCPNN), and simplified Bayes methods and found to be the most conservative method when examining the total number of detected signals, given its ability to control type-I error and the false discovery rate.

Application of a likelihood ratio test based method for safety signal detection to left ventricular assist devices

Effective post-market safety surveillance of medical devices is critical for public health. However, many current statistical methods for safety signal detection do not control for type I error when assessing multiple device and adverse event (AE) combinations. This can result in increased false signals, underscoring the need for more robust statistical methods. Moreover, the duration of medical device use can be an important factor to consider in safety surveillance. In this study, we adapted a likelihood ratio test (LRT) based method, which was initially developed and applied to drugs, to identify safety signals for left ventricular assist devices (LVAD). Among patients with chronic, advanced left ventricular failure, we analyzed AE data for HeartWare and HeartMate II patients during a two-year period and further incorporated person-years (henceforth exposure-time). The novel modified LRT and conventional Z-test with p-values adjusted by the Benjamini-Hochberg (BH) procedure were used to explore safety signals by comparing HeartWare and HeartMate II patients in the presence of multiple adverse events. Both methods identified greater incidence of stroke among HeartWare as compared to HeartMate II patients without exposure-time (p = .025 for LRT and p = .027 for Z-test with BH) and with exposure-time (p = .002 for LRT and p = .005 for Z-test with BH). By using improved statistical methods for safety signal detection, potential safety issues can be identified and addressed in a more timely manner to enhance public safety.