EP128 One-month pain recovery patterns after total knee arthroplasty: two distinct patient groups identified by an unsupervised learning algorithm

<h3></h3> <b>Please confirm that an ethics committee approval has been applied for or granted</b>: Yes: I’m uploading the Ethics Committee Approval as a PDF file with this abstract submission <h3>Background and Aims</h3> While much research exists on patterns of pain scores in the perioperative period, much less data exists on longer term follow-up of pain scores, especially after total knee arthroplasty (TKA). Re-using data from a published prospective study capturing patients‘ pain scores recorded over 29 days post-TKA, we aimed to assess whether unsupervised machine learning can discern distinct postoperative recovery patterns. <h3>Methods</h3> This study was approved by an Institutional Review Board as it re-used data from a published study that prospectively enrolled 103 patients undergoing primary TKA (2020-2021) at a single university hospital. Patients recorded daily numeric rating scale pain scores at morning, lunchtime, evening, and nighttime for 29 days. A K-Means clustering algorithm (unsupervised) was applied to identify distinct pain recovery patterns after which the identified recovery groups were compared based on available patient and surgical characteristics. <h3>Results</h3> Two clusters of patients with distinct recovery patterns were discovered: patients in Cluster 1 (versus Cluster 2) had higher pain levels throughout the recovery period (figure 1); Cluster 1 also represented patients that were more likely female and with higher Knee Society Scores (KSS) at both week 1 and 4 post-TKA, as well as a higher KSS Functional Score at week 1. (table 1) <h3>Conclusions</h3> Machine learning algorithms applied to longitudinal pain level data have identified two distinct postoperative recovery patterns after TKA. Notably, patients who experienced higher pain levels early postoperatively exhibited consistently higher pain levels later within the first month of recovery.