(238) AI-Driven Management of Submassive PE Advances Beyond Initial Approach for AI-Driven Diagnosis

Introduction: Pulmonary embolism is a critical condition with high morbidity and mortality. Early diagnosis and prompt intervention are crucial. Traditional diagnostic methods often involve time-consuming imaging and interpretation, delaying treatment. Leveraging artificial intelligence to streamline the diagnosis and management pathway can significantly enhance patient outcomes. The AI technology for identifying pulmonary embolus on CT scans, initially developed in 2019, laid the groundwork for automated diagnostic capabilities. However, this case report goes significantly beyond mere identification.

Description: 88M with PMH HTN, PAD, COPD, HLD, BPH who presented to ED with pre-syncope and RLE pain. Initial CT scan revealed an extensive bilateral PE with R heart strain. At the conclusion of the scan, an AI generated algorithm immediately notified the interventional cardiologist of the extensive bilateral PE and RV strain which sent a cascade of events into play. This novel approach integrated the AI diagnostic tool directly with the EMR, enabling real-time decision making and streamlining the workflow from diagnosis to treatment. The integration facilitated an immediate cardiology consultation and flagged transfer protocols, thus reducing the time from detection to intervention. The patient was immediately transferred to a facility in which he could receive surgical intervention. Unlike the initial AI application, which focused solely on detection, this approach includes an automated system that triggers cardiology consultation. This ensures that specialists are promptly involved, providing expert oversight without delay. The system provided cardiologists with a comprehensive report, including AI-interpreted imaging findings and clinical parameters, enhancing diagnostic accuracy and treatment planning.

Discussion: This novel approach enhances and expands AI utility by integrating it into a comprehensive care pathway. The seamless coordination between diagnosis, consultation, and transfer, driven by AI, represents a significant innovation in critical care management. This holistic approach not only improves diagnostic accuracy and efficiency but also ensures timely and appropriate intervention, ultimately improving patient outcomes, specifically in cases of large pulmonary emboli.