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用于早期识别离心式血流泵血栓形成的左心室辅助装置固有数据跟踪算法的验证

Validation of Intrinsic Left Ventricular Assist Device Data Tracking Algorithm for Early Recognition of Centrifugal Flow Pump Thrombosis.

作者信息

Gross Christoph, Dimitrov Kamen, Riebandt Julia, Wiedemann Dominik, Laufer Günther, Schima Heinrich, Moscato Francesco, Brown Michael C, Kadrolkar Abhijit, Stadler Robert W, Zimpfer Daniel, Schlöglhofer Thomas

机构信息

Department of Cardiac Surgery, Medical University of Vienna, 1090 Vienna, Austria.

Ludwig Boltzmann Institute for Cardiovascular Research, 1020 Vienna, Austria.

出版信息

Life (Basel). 2022 Apr 9;12(4):563. doi: 10.3390/life12040563.

Abstract

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 ( = 16 patients with 30 PT events) and a thoroughly selected control group ( = 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.

摘要

晚期心力衰竭患者可受益于植入式左心室辅助装置的卸载作用。尽管有最佳临床实践,但左心室辅助装置仍与不良事件相关,如泵血栓形成(PT)。一种自适应算法,当个体的泵功率摄取超过适当水平时发出警报,如在PT情况下,可改善植入离心式左心室辅助装置患者的治疗。我们回顾性研究了在单一中心植入离心式左心室辅助装置的75例患者。将先前优化的自适应泵功率跟踪算法与临床最佳实践和临床上可用的恒定阈值算法进行比较。在PT组(16例患者发生30次PT事件)和精心挑选的对照组(59例患者,有34.7患者年的左心室辅助装置数据)中分析算法性能。将自适应功率跟踪算法与性能最佳的恒定阈值算法进行比较,灵敏度分别为83.3%对86.7%,特异性分别为98.9%对95.3%。功率跟踪算法每11.6患者年产生一次假阳性检测,并在PT诊断前中位数3.6天发出早期预警。总之,一项使用真实世界患者数据的回顾性单中心验证研究证明了功率跟踪算法在左心室辅助装置系统和临床实践中的有益应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42dc/9027619/d60159f2859b/life-12-00563-g0A1.jpg

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