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.

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http://dx.doi.org/10.1111/aor.14163DOI Listing

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