AI improves stroke care and reduces patient risks in major study

The system, which analyses medical scans and provides treatment recommendations, was associated with better outcomes compared with standard approaches to stroke care. Researchers said the tool offers a more efficient and scalable method for improving treatment, particularly in resource-constrained healthcare systems.

The findings are based on more than 21,000 patients treated across 77 hospitals in China. Patients supported by the AI-driven clinical decision support system experienced fewer new vascular events, including stroke recurrence, heart attack, or related death, over follow-up periods of up to 12 months.

At three months, new vascular events occurred in 2.9% of patients using the system, compared with 3.9% in those receiving usual care, representing a 26% reduction. The benefit persisted at 12 months, with rates of 4% in the intervention group versus 5.5% in the control group.

Patients receiving AI-supported treatment also showed improved performance on key stroke care quality measures, although no significant differences were observed in disability, mortality, or bleeding outcomes between the groups.

Researchers noted limitations, including the study design, which randomised hospitals rather than individual patients, and potential differences in follow-up care. However, they highlighted the system’s ease of integration into hospital workflows and its potential to strengthen stroke care delivery and long-term prevention strategies.

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