HSS machine-learning tool identifies factors linked with worse outcomes after hip arthroscopy

Written by Alan Condon | February 03, 2020 | Print  |

A machine-learning algorithm recognized predictive factors linked with worse outcomes for patients undergoing arthroscopic surgery to treat femoroacetabular impingement of the hip.

Spearheaded by Benedict Nwachukwu, MD, orthopedic surgeons from New York City-based Hospital for Special Surgery, highlighted the findings in a Jan. 31 paper in the American Journal of Sports Medicine.

Anxiety and depression, length of symptoms for more than two years before surgery, high preoperative scores on patient-reported outcome surveys and receiving preoperative steroid injections were identified as factors that significantly predicted worse patient outcomes.

Researchers also noted two variables that predicted achieving better results: running and being female.

The algorithm was created using EHR data for 898 patients with FAI who underwent hip arthroscopy at Rush University Medical Center in Chicago.

The findings highlight the importance of screenings for anxiety and depression, according to Dr. Nwachukwu, and the symptom duration finding should encourage more payers to cover hip surgery sooner, rather than prolong conservative treatment for patients.

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