Predicting Outcome of Total Knee Arthroplasty by Cluster Analysis of Patient-Reported Outcome Measures

Total knee arthroplasties (TKAs) exhibit an 8 to 30% risk of suboptimal outcomes, resulting in persistent symptoms, individual morbidity, and revision surgery, prompting a contemporary focus on risk reduction and outcome improvement. This study introduces hierarchical cluster analysis as a way of preoperatively assessing the likelihood of success/failure of TKA based on several patient-reported outcome measures, which have been analyzed both intact and with component questions as individual variables.