The patient-acceptable symptom state (PASS) is a level of wellbeing, which is measured by the patient. The aim of this study was to determine if the proportion of patients who achieved an acceptable level of function (PASS) after medial unicompartmental knee arthroplasty (UKA) was different based on the status of the anterior cruciate ligament (ACL) at the time of surgery. A total of 114 patients who underwent UKA for isolated medial osteoarthritis (OA) of the knee were included in the study. Their mean age was 65 years (SD 10). No patient underwent a bilateral procedure. Those who had undergone ACL reconstruction during the previous five years were excluded. The Knee injury Osteoarthritis Outcome Score Activities of Daily Living (KOOS ADL) function score was used as the primary outcome measure with a PASS of 87.5, as described for total knee arthroplasty (TKA). Patients completed all other KOOS subscales, Lysholm score, the Western Ontario and McMaster Universities Osteoarthritis Index, and the Veterans Rand 12-item health survey score. Failure was defined as conversion to TKA.Aims
Methods
The purpose of this study was to develop a personalized outcome prediction tool, to be used with knee arthroplasty patients, that predicts outcomes (lengths of stay (LOS), 90 day readmission, and one-year patient-reported outcome measures (PROMs) on an individual basis and allows for dynamic modifiable risk factors. Data were prospectively collected on all patients who underwent total or unicompartmental knee arthroplasty at a between July 2015 and June 2018. Cohort 1 (n = 5,958) was utilized to develop models for LOS and 90 day readmission. Cohort 2 (n = 2,391, surgery date 2015 to 2017) was utilized to develop models for one-year improvements in Knee Injury and Osteoarthritis Outcome Score (KOOS) pain score, KOOS function score, and KOOS quality of life (QOL) score. Model accuracies within the imputed data set were assessed through cross-validation with root mean square errors (RMSEs) and mean absolute errors (MAEs) for the LOS and PROMs models, and the index of prediction accuracy (IPA), and area under the curve (AUC) for the readmission models. Model accuracies in new patient data sets were assessed with AUC.Aims
Methods
