Data from the first US comprehensive single-centre experience at St Bernard’s Medical Center and Arrhythmia Research Group (Jonesboro, USA), presented at a late-breaking session at the AF Symposium 2024 (1–3 February, Boston, USA) shows that left atrial appendage occlusion (LAAO) procedures planned by means of FEops HEARTguide result in significantly improved procedural efficiency.
The 178 patient US single-centre evaluation, led by Devi Nair aimed to assess the safety, efficiency and accuracy of FEops HEARTguide predictive pre-planning based on cardiac computed tomography (CT) imaging for both the Watchman FLX (Boston Scientific) and Amplatzer Amulet (Abbott) device.
“This is the first-ever comprehensive clinical evaluation in the USA proving that artificial intelligence (AI)-enabled predictive pre-planning significantly improves LAAO procedural efficiency for both the Watchman FLX and the Amulet device. Our results confirm that the accuracy of device sizing and positioning for LAAO procedures is significantly better when using FEops HEARTguide as compared to standard CT-based planning. Our real-world evidence reinforces the excellent results from the landmark PREDICT-LAA trial”, said Nair.
In terms of procedural efficiency, the evaluation results revealed that in 97% cases a single LAAO device was successfully implanted with a single transseptal puncture. The average procedure time was 21 minutes compared to 55 minutes in the control group, the average fluoroscopy time was 4 minutes compared to 17 minutes and average contrast used during the procedure was 20ml compared to 80ml.
“This real world evidence clearly reinforces the value of our pioneering digital twin strategy to alter the course of heart disease,” said Matthieu De Beule, co-founder and CEO of FEops. “We are extremely proud of the results of this comprehensive evaluation and I am very grateful for the visionary drive of Dr Devi Nair and the entire FEops team for making this happen. Together we continue to advance how physicians access therapy options for patients at risk of stroke due to atrial fibrillation. The results support us in our mission to continue to spearhead AI-enabled predictive solutions that help treating the right heart disease patients with the right technology at the right time.”
