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Lou receives Best Research Abstract at the World Congress of Anaesthesiologists

Sunny Lou, MD, PhD, an instructor in anesthesiology at Washington University School of Medicine in St. Louis, was awarded first place in the Best Clinical Research Abstract competition at the World Congress of Anaesthesiologists meeting held in Singapore on March 3-7, 2024. Her talk and abstract, titled “External validation of a publicly available surgical transfusion risk prediction model: a multicenter perioperative outcomes group study,” highlights the importance of precisely estimating the risk of needing a blood transfusion during surgery. This is crucial because it helps doctors better prepare for surgery, with the goal of improving patient safety and using medical resources more effectively. Traditionally, doctors have estimated transfusion needs based on the type of surgery, but often, patient-specific details that could change the risk are not considered. Dr. Lou’s innovative work shifts the focus to include these personal health details by creating and testing a new, personalized surgical transfusion risk prediction algorithm named S-PATH.

Her findings could change the way doctors plan for surgeries by providing a more complete understanding of the likelihood of a patient needing a blood transfusion. This could improve the way blood type testing and antibody screening are done before surgery, making these processes more efficient.

“I’m honored to receive this award from the World Congress of Anaesthesiologists,” says Lou. “In this study, we found that S-PATH performed consistently well across a diverse cohort of 45 US hospitals. These results suggest that S-PATH might be broadly useful to help doctors decide which patients should have preoperative blood testing, which could help improve patient safety while reducing unnecessary tests.”

The recognition of Dr. Lou’s research at an international level underscores the importance of ongoing advancements in medical science, particularly in the field of perioperative care. By demonstrating the generalizability of the S-PATH algorithm, her work is paving the way for more tailored and potentially more effective approaches to patient care during surgery.