HELSINKI, Finland — A recent randomized trial demonstrated that an AI-based clinical decision support system significantly aided doctors in treating acute ischemic stroke, resulting in a notable decrease in recurrent vascular events.
This AI system combined clinician feedback with data from hospital records and imaging studies involving over 20,000 patients across China, assisting in patient management regarding stroke causes and secondary prevention strategies.
Li Zhang, MD, from Beijing Tiantan Hospital and the study chair, remarked on the trial’s promising implications for the future role of AI in stroke care. “This study illustrates that integrating AI for prompt, evidence-driven guidance can enhance our treatment approaches for acute strokes, resulting in improved patient outcomes,” he stated.
AI’s Role in Stroke Management
According to Zhang, accurate and swift decision-making is vital in acute stroke management. AI tools capable of automated imaging analysis and guideline-based treatment recommendations show potential for standardizing care and enhancing patient outcomes. The GOLDEN BRIDGE II trial aimed to validate this hypothesis in a real-world, multi-center context.
Conducted between January 2021 and June 2023 across 77 hospitals in China, the cluster-randomized trial evaluated the use of the AI system versus conventional care. The AI provided real-time recommendations for secondary prevention based on automated MRI lesion detection, classification of stroke types, and analysis of lesion characteristics.
The trial enlisted 21,603 patients, with a median age of 67 years and 35% of participants being women. The primary measurement focused on new vascular events—comprising ischemic or hemorrhagic strokes, heart attacks, or vascular mortality—within three months post-stroke.
Promising Findings and Future Considerations
Results indicated that patients utilizing the AI system experienced significantly fewer recurrent vascular incidents at all evaluated intervals. Specifically, rates were 2.9% in the intervention group versus 3.9% in the control group after three months, and similar trends were observed at six and twelve months.
Additionally, patients benefiting from the AI tool exhibited lower overall mortality at the six-month and twelve-month marks and achieved a higher composite quality score for acute ischemic stroke care. Nonetheless, the cluster-randomized design could present variations in care among hospitals, potentially impacting outcomes.
Challenges and Areas for Future Research
Commenting on the study’s findings, experts emphasized the need for replication in Western contexts, as the research relied on Chinese stroke guidelines, which differ significantly from those in Europe and North America. They called for additional investigations to clarify how AI improved clinical practices, whether through imaging or adherence to guidelines.
Future advancements in AI, particularly in large language models, may enhance real-time interactions with healthcare professionals, facilitating a better integration of technology into clinical settings. Experts stressed the importance of regularly updating algorithms to reflect evolving clinical practices without compromising patient safety.
