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A research utilizing synthetic intelligence to categorise affected person ache archetypes and establish threat for extreme ache after knee substitute has earned a Better of Assembly award on the fiftieth Annual Assembly of the American Society of Regional Anesthesia and Ache Medication (ASRA). The distinction, which acknowledges excellence in scientific analysis, is awarded to a few of the highest 10 highest-scoring abstracts chosen by the ASRA Analysis Committee.
“It’s an honor to have one of many prime skilled organizations within the discipline of regional anesthesia and ache medication spotlight the collaborative work of our division’s Ache Prevention Analysis Heart,” mentioned Alexandra Sideris, Ph.D., director of the Ache Prevention Analysis Heart at HSS. “The award displays our dedication to improvements in affected person care and underscores the larger scientific group’s acknowledgment of our efforts.”
A couple of million folks bear knee substitute surgical procedure every year in the USA, and people numbers proceed to rise, Dr. Sideris notes.
“There’s a want to higher perceive sufferers’ particular person ache trajectories, and one of the thrilling approaches is to leverage synthetic intelligence. With our enormous affected person database at HSS, machine studying can analyze components equivalent to age, gender, BMI, and presurgical ache ranges to foretell which sufferers are at larger threat of extreme ache after surgical procedure,” she mentioned.
Armed with this info, the care workforce can tailor personalised ache administration plans to fulfill sufferers’ wants.
The HSS researchers had a number of objectives: make the most of machine studying to establish ache archetypes following whole knee substitute; decide essential options for predicting ache outcomes; and classify sufferers prone to extreme ache within the instant postoperative interval. The retrospective research included 17,200 sufferers who had whole knee replacements at HSS from April 1, 2021, to October 31, 2024.
“Utilizing unsupervised machine studying, we recognized two distinct ache archetypes in sufferers who underwent whole knee substitute, which corresponded to those that skilled extreme, troublesome to regulate ache after surgical procedure and people whose ache was comparatively properly managed,” defined Justin Chew, MD, Ph.D., a scientific fellow at HSS who introduced the research on the ASRA assembly on Could 1.
“We then utilized supervised machine studying to find out essentially the most vital predictive components for extreme ache. In our research, threat components included youthful age, larger bodily/psychological impairment, increased BMI, and preoperative opioid or gabapentinoid use.”
Dr. Sideris notes that ongoing and future research at HSS will proceed to leverage AI with the aim of enhancing affected person outcomes. Whereas the research targeted on the instant postoperative interval, she mentioned further research will observe sufferers’ ache trajectory and restoration over longer durations of time to find out which methods docs can make use of earlier than surgical procedure, intraoperatively and within the instant postoperative interval to handle ache in high-risk sufferers.
Extra info:
Classification and stratification of affected person ache archetypes following whole knee arthroplasty: a machine studying method (2025)
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Hospital for Particular Surgical procedure
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AI efficiently identifies threat components linked to extra extreme ache after knee substitute (2025, Could 2)
retrieved 2 Could 2025
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