Feeling Better After TKA: Reference chart for remotely collected pain scores

Abstract

Remote patient monitoring, using wearable devices and connected patient engagement platforms has the potential to improve timely clinical decisions. Data collected from multiple patients, including using the remote engagement platforms themselves, can be used to produce evidence-based reference to support clinical decisions. While some normative references for functional measure currently exist for total knee arthroplasty (TKA), these are still lacking for VAS pain scores. Therefore, VAS pain scores on a 10-point Likert scale were analyzed for 66 patients, each reporting at least five scores in the 180 days following surgery. These were used to produce a normative recovery model for total knee arthroplasty patients. A nonlinear mixed effects model was fitted, whereby the response variable is assumed to be distributed following a beta-binomial distribution. The population mean trend showed a with wide dispersion in the first few days following surgery, showing scores ranging throughout the 10-point scale. After the first week, the expected pain score steadily decreases, resulting in a score no higher than one in 50% of the population beyond 90 days after surgery. The fitted model allows referencing individual patient's pain scores at different stages of recovery, against the model’s predicted distribution. This approach can support early detection of patients that significantly deviate from the reference model and be a useful integration into clinical decision support software tools.