A new study using artificial intelligence (AI) to better understand and predict pain in patients after knee replacement surgery has received top honors at the 50th Annual Meeting of the American Society of Regional Anesthesia and Pain Medicine (ASRA).
The research, led by the Pain Prevention Research Center at the Hospital for Special Surgery (HSS), was awarded one of the “Best of Meeting” titles, recognizing it as one of the top three scientific presentations among hundreds.
Each year, over a million people in the United States undergo total knee replacement surgery. While the procedure often improves mobility and quality of life, many patients experience severe pain after the operation. Understanding which patients are most at risk could help doctors personalize care and improve recovery.
Dr. Alexandra Sideris, director of the Pain Prevention Research Center at HSS, emphasized the importance of this work. “It is an honor to be recognized by such a respected organization,” she said. “This award reflects our team’s commitment to advancing patient care through innovation.”
To conduct the study, the research team used machine learning—a type of AI that can analyze large amounts of data and recognize patterns. They studied data from 17,200 patients who had knee replacement surgery at HSS between April 2021 and October 2024.
The goal was to group patients based on their pain experiences, figure out what predicts severe pain, and identify patients who might need extra pain management after surgery.
First, the researchers used an unsupervised AI method to sort patients into two pain “archetypes,” or patterns. One group experienced severe and hard-to-control pain after surgery. The other group had relatively well-managed pain. This classification helps doctors understand how pain levels can differ significantly between patients.
Next, the team applied supervised machine learning to pinpoint which factors predicted severe pain. They found that younger patients, those with more physical or mental health problems, individuals with a higher body mass index (BMI), and those who were already using opioid or nerve pain medications before surgery were more likely to experience worse pain afterward.
Dr. Justin Chew, the clinical fellow at HSS who presented the findings at the ASRA meeting, said the study shows how AI can be used to improve care. “Our analysis helps identify which patients are most at risk so that doctors can plan ahead with customized pain management strategies,” he explained.
Dr. Sideris added that future research will go beyond just the early days after surgery. Ongoing studies will follow patients for longer periods to track how pain changes over time and test which treatments work best before, during, and after surgery to help those at higher risk.
By using AI to better predict and manage post-surgery pain, the team at HSS hopes to make recovery smoother and more comfortable for the growing number of patients undergoing knee replacements. This study is a strong example of how technology and personalized care can come together to improve medical outcomes.
If you care about pain, please read studies about how to manage gout with a low-purine diet, and a guide to eating right for arthritis.
For more health information, please see recent studies about the link between processed foods and chronic diseases, and avoid these 8 foods to ease arthritis pain.
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