Early detection of HVAD pump thrombosis based on technical analysis and power consumption measurements. Issue 6 (11th January 2022)

• Record Type: Journal Article
• Authors: Krysiński, Mateusz; Gawlikowski, Maciej; Biełka, Agnieszka; Krysińska, Małgorzata; Małyszek‐Tumidajewicz, Justyna; Copik, Izabela; Pacholewicz, Jerzy; Zembala, Marian; Zembala, Michał
• Is Part Of: Artificial organs. Volume 46:Issue 6(2022)
• Page Start: 1142
• Page End: 1148
• Publication Date: 2022-01-11
• Subjects: early detection -- early event detection -- HVAD pump -- left ventricular assisting device -- pump thrombosis; Artificial organs -- Periodicals; 617.956
• DOI: 10.1111/aor.14163
• Languages: English
• ISSNs: 0160-564X

Abstract

Abstract: Background: Continuous‐flow left ventricular assist devices (LVADs) have been extensively used in a strategy of bridge to orthotopic heart transplant and destination therapy. The usage of LVAD, however, is not free from limitations such as device‐related adverse events, including pump thrombosis (PT). We aimed to develop an algorithm of early PT detection based on the maintenance parameters monitored by the implanted device. Methods: We analyzed log files of 101 patients implanted with HeartWare pump (HVAD) with 18 PT events among them. For signal processing, we used the open‐high‐low‐close format transformation and typical price (TP) technical analysis indicator. Model parameters were tuned with 5‐fold cross‐validation, and the final performance was measured on a separate group of patients. Results: Our algorithm achieved 100% sensitivity and 100% specificity of indications. In the final evaluation, alarms preceded the clinical acknowledgement of events by 2 days and 20 h on average. In the worst‐case scenario, an alarm was raised 1 day and 8 h prior to the event. Conclusions: The proposed algorithm could be installed to work directly with the device controller and provide clinicians with automatic readings analysis, raising an alarm when there is a high probability of thromboembolism. Early event detection could enable better thrombosis management and improve prognosis in patients implanted with HVAD. Abstract : Patient's characteristics are gathered over 2 days. For every consecutive datapoint, an alarm is triggered if the specified probability threshold is reached. Algorithm achieved 100% sensitivity and 100% specificity in cross‐validation and on the test group. It could be installed to work directly with the device controller and provide clinicians with automatic readings analysis.