Abstract
Introduction: Therapeutic anticoagulation during atrial fibrillation (AF) ablation reduces the risk of cerebral thromboembolism during ablation. Heparin dosing strategies vary and can result in sub-therapeutic anticoagulation. Hypothesis: We hypothesize that a heparin dosing algorithm will improve maintenance of guideline-based therapeutic activated clotting times (ACT) during AF ablation. Methods: Starting from published guidance on heparin dosing during AF ablation, an artificial intelligence algorithm based on a decision tree and other mathematical considerations was developed. The algorithm launches directly from the electronic medical record and captures deidentified data for future improvements. The rules were modified over several months to establish the tested algorithm. The strategy utilized heparin boluses and an infusion. Dosing was adapted based on an individual patient’s response to the first heparin bolus. Goal ACT was 300-350 s. Outcomes from a month prior to algorithm introduction were compared to those from one month using the developed algorithm. The measured outcomes included time from first bolus to therapeutic ACT (>300 s), number of heparin boluses to achieve goal ACT, time in left atrium below therapeutic ACT, and ACT value when below goal in left atrium. Results: Data from seventeen pre-algorithm procedures were compared to fourteen procedures completed using the dosing algorithm. Compared to procedures using typical dosing, procedures using the dosing algorithm reached goal ACT faster (16.1 ± 5.3 min compared to 26.2 ± 14.5 min, p = 0.02) with fewer heparin boluses (1.1 ± 0.3 boluses compared to 1.6 ± 0.9 boluses, p = 0.04). The ACT did drift below goal in some cases (n = 4 using algorithm and n = 5 using typical dosing). The time below goal was not different between dosing strategies (16.5 ± 8.7 min for algorithm compared to 22.4 ± 7.9 min for typical dosing). However, when the ACT drifted below goal with the dosing algorithm, it was significantly closer to goal than with typical dosing (295 ± 3 s compared to 268 ± 21 s, p = 0.02). Conclusion: An artificial intelligence algorithm based on a decision tree and adaptation to individual patient kinetics may improve maintenance of guideline based therapeutic ACT during AF ablation.
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