NEW YORK, Feb. 3, 2020 /PRNewswire/ — A machine-learning algorithm developed by an orthopedic surgeon at Hospital for Special Surgery (HSS) and his colleagues identified predictive factors associated with worse outcomes for patients with femoroacetabular impingement (FAI) of the hip who had arthroscopic surgery to treat it. FAI is a condition in which the ball and socket of the hip joint do not fit together properly and can ultimately cause pain and the need for a surgical repair.
“These findings are important from several perspectives. First of all, they demonstrate the value of integrating a machine-learning tool into clinical practice,” says first author Benedict Nwachukwu MD, MBA, a sports medicine surgeon and co-director of clinical research for the Sports Medicine Institute at HSS in New York City. “From a clinical perspective, our results reinforce that we should be screening for anxiety and depression. The symptom duration finding should encourage more payers and insurance companies to cover hip surgery for patients sooner, rather than keep them in prolonged conservative treatment. Finally, the risk associated with the use of preoperative injections is a novel finding that has not been reported very often in the literature.”
