AI Study Wins Top Honor at ASRA Meeting, Identifying Key Risk Factors for Severe Post-Knee Replacement Pain

A study conducted by researchers at Hospital for Special Surgery (HSS) has earned a Best of Meeting award at the 50th Annual Meeting of the American Society of Regional Anesthesia and Pain Medicine (ASRA). This honor, which highlights excellence in scientific research, was bestowed upon one of the top 10 highest-scoring abstracts selected by the ASRA Research Committee. The study leverages artificial intelligence (AI) to identify patient pain archetypes and predict the risk of severe pain following total knee replacement surgery. Alexandra Sideris, PhD, director of the Pain Prevention Research Center at HSS, expressed her gratitude for the recognition, emphasizing the importance of innovative approaches to patient care. "It is an honor to have our work acknowledged by such a respected organization. Our study not only advances our understanding of pain management but also highlights the potential of AI in healthcare." Total knee replacement is a common surgical procedure with over one million people undergoing it annually in the United States, and this number is expected to increase. Dr. Sideris noted the critical need to understand individual pain trajectories to optimize patient care. By utilizing HSS’s extensive patient database, the research team employed machine learning to analyze various patient characteristics, including age, gender, body mass index (BMI), and preoperative pain levels, to predict postoperative pain intensity. The primary objectives of the study were to use machine learning to classify pain outcomes after total knee replacement, determine significant predictive factors, and identify patients at risk of severe postoperative pain. The retrospective analysis included data from 17,200 patients who had total knee replacements at HSS between April 1, 2021, and October 31, 2024. Justin Chew, MD, PhD, a clinical fellow at HSS, presented the findings at the ASRA meeting on May 1. Using unsupervised machine learning, the researchers identified two distinct pain archetypes: patients who experienced severe, difficult-to-control pain and those with relatively well-managed pain. Subsequently, supervised machine learning was applied to pinpoint the most crucial factors that predicted severe pain. These risk factors included younger age, higher levels of physical and mental impairment, higher BMI, and the use of opioids or gabapentinoids before surgery. Dr. Sideris highlighted that the study's findings could significantly impact clinical practice. "Armed with this information, healthcare providers can develop personalized pain management plans to better support high-risk patients," she said. Future research at HSS aims to extend these findings to longer-term pain trajectories and recovery, exploring strategies to optimize pain management before, during, and after surgery. The institution's commitment to leveraging AI for patient care extends beyond this study. HSS is actively conducting ongoing and new research to enhance musculoskeletal health through advancements in prevention, treatment, and recovery. Founded in 1863, HSS has a rich history of excellence, consistently ranking at the top in orthopedics and related fields. It is recognized as the world’s leading academic medical center focused on musculoskeletal health and has been nationally ranked No. 1 in orthopedics for 15 consecutive years. The hospital also boasts the lowest readmission rates in the nation for orthopedic procedures and among the lowest infection and complication rates. HSS's multidisciplinary approach includes a robust Research Institute with 20 laboratories and 300 staff members dedicated to advancing musculoskeletal health. Additionally, over 200 clinical investigators are working to improve patient outcomes through innovative prevention, diagnosis, and treatment methods. The HSS Innovation Institute plays a crucial role in realizing the potential of new drugs, therapeutics, and devices, while the HSS Education Institute leads the way in disseminating knowledge and best practices to a global audience. This groundbreaking study further solidifies HSS’s position as a leader in the integration of AI and machine learning in healthcare, providing valuable insights that can be applied to enhance the quality of care and improve patient outcomes. Industry insiders commend the research for its practical implications, noting that the ability to predict and manage postoperative pain more effectively could lead to significant improvements in patient satisfaction and recovery times.