Accurate and Automated Multi-Center TCD Velocity Analysis Using Natural Language Processing [Abstract]

Abstract

Up to 10% of US children with sickle cell disease (SCD) develop abnormal transcranial Doppler (TCD) velocities, indicating abnormal cerebral vasculature and a high risk of stroke. Chronic red cell transfusions decrease stroke risk in patients with abnormal TCD. However, transfusions are resource-intensive and burdensome to patients, and they may not fully reverse existing damage. Prevention of TCD abnormalities is therefore ideal. The impact of real-world SCD care practices on TCD results is largely unknown due to an inability to detect TCD outcomes without labor-intensive manual review. We present a novel method for identification and interpretation of TCD results across multiple children’s hospitals.