Using a postoperative pain trajectory to predict pain at 1 year after total knee arthroplasty

The pain trajectory is an early detection/prediction method for chronic postsurgical pain (CPSP). It is unclear whether a pain trajectory can predict CPSP in patients who have undergone a total knee arthroplasty (TKA). Here we investigated (1) whether CPSP can be predicted in TKA patients, and (2) the values that can be used to predict CPSP.

We studied 211 postoperative TKA patients. We calculated the pain trajectory (pain curve slope and intercept) using the patients' self-reported pain intensity values at 1, 3, 5, and 7 days post-TKA. Using structural equation modeling (SEM), we performed a multiple regression analysis to investigate appropriate prediction models for the pain trajectory. Classification and regression tree (CHAID) methodology was used to calculate values to predict CPSP by a decision tree model. CPSP (dependent variable) was defined as >30 mm on a visual analog scale for pain intensity at 1 year post-TKA. The predictor variables were pain curve slope, intercept, age, sex, body mass index, and preoperative pain intensity.

The pain trajectory was the best fit among the models to predict pain intensity at 1 year post-TKA. When the pain curve slope (pain trajectory) was greater than 2.8, the probability of CPSP at 1 year post-TKA was 33.3%.

Our results suggest that the pain trajectory could be applied to post-TKA patients and used to calculate clinical values to predict CPSP. Our findings also indicate the possibility that patients with a positive pain curve slope in the first postoperative week may need early intervention to avoid CPSP.