Daniel L Riddle1, Xiangrong Kong, William A Jiranek. 1. Department of Physical Therapy and Orthopaedic Surgery, Virginia Commonwealth University, Medical College of Virginia Campus, Richmond, VA 23298-0224, USA.
Abstract
OBJECTIVE: There is little evidence to guide physicians when discussing future likelihood of knee arthroplasty with patients who have symptomatic knee osteoarthritis. Data from Osteoarthritis Initiative (OAI) was used to determine the incidence of and predictors for knee arthroplasty. METHODS: OAI data were collected on a sample of 778 persons aged 45 to 79 years with symptomatic knee osteoarthritis. An extensive set of measurements were obtained at baseline and persons were followed for 2 years to identify who underwent knee arthroplasty. Random forest analysis was used to identify optimal variables that discriminate among those who did and those who did not undergo knee arthroplasty. RESULTS: The two year incidence of knee arthroplasty in the cohort was 3.7% (95%CI, 2.6%, 5.3%). Because of the low number of knee arthroplasty procedures, the predictor analysis was preliminary in nature. The analysis identified several variables that could be used to assist in identifying patients at future risk for knee arthroplasty. CONCLUSION: For persons at high risk of knee arthroplasty, the two year incidence of knee arthroplasty is very low. The most powerful predictors were those that accounted for disease severity and functional loss. These data could assist physicians in advising patients with knee osteoarthritis on future surgical care.
OBJECTIVE: There is little evidence to guide physicians when discussing future likelihood of knee arthroplasty with patients who have symptomatic knee osteoarthritis. Data from Osteoarthritis Initiative (OAI) was used to determine the incidence of and predictors for knee arthroplasty. METHODS: OAI data were collected on a sample of 778 persons aged 45 to 79 years with symptomatic knee osteoarthritis. An extensive set of measurements were obtained at baseline and persons were followed for 2 years to identify who underwent knee arthroplasty. Random forest analysis was used to identify optimal variables that discriminate among those who did and those who did not undergo knee arthroplasty. RESULTS: The two year incidence of knee arthroplasty in the cohort was 3.7% (95%CI, 2.6%, 5.3%). Because of the low number of knee arthroplasty procedures, the predictor analysis was preliminary in nature. The analysis identified several variables that could be used to assist in identifying patients at future risk for knee arthroplasty. CONCLUSION: For persons at high risk of knee arthroplasty, the two year incidence of knee arthroplasty is very low. The most powerful predictors were those that accounted for disease severity and functional loss. These data could assist physicians in advising patients with knee osteoarthritis on future surgical care.
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