Patient-Specific Pain Model for Identifying Patients at Risk Following TKA

Abstract

Remote patient monitoring provides clinicians with visibility to patients’ recovery beyond what can be achieved with in clinic visits alone. Patients’ pain management is an important aspect of recovery following total knee arthroplasty (TKA), and one that is increasingly tracked remotely through digital applications. Its timely assessment may provide clinicians with a way to detect postoperative complications. We proposed a patient-specific model that predicts the probability of remotely collected pain scores for TKA patients along a 90-day recovery period, aimed at detecting patients with anomalous pain scores, and enable appropriate interventions by clinicians in a timely manner. We fitted and validated the model with a set of 4,782 remotely collected pain scores for 84 patients that underwent unilateral primary TKA.