Early Identification of Patient Satisfaction Two Years After Total Knee Arthroplasty.

BACKGROUND: There are numerous reports of poor satisfaction after total knee arthroplasty (TKA), yet there is little known about when to use evidence-based models of care to improve patient outcomes. OBJECTIVE: This study aimed to characterize longitudinal changes in patient-reported satisfaction after TKA and to identify factors for early identification of poor satisfaction. METHODS: For a cohort of primary TKA surgeries (n = 86), patient-reported outcomes were captured one week before TKA and 6 weeks, 12 weeks, 6 months, and 1 and 2 years after TKA. "Satisfied" versus "not fully satisfied" patients were defined using a binary response (≥90 vs <90) from a 100-point scale. Wilcoxon signed-rank tests identified changes in satisfaction between follow-up times, and longitudinal analyses examined demographic and questionnaire factors associated with satisfaction. RESULTS: Improvements in satisfaction occurred within the first 6 months after TKA (P ≤ 0.01). Preoperative patient-reported outcome measures alone were not predictive of satisfaction. Key factors that improved longitudinal satisfaction included higher Oxford Knee Scores (odds ratio (OR) = 2.1, P < .001), general health (EQ-VAS, OR = 1.3, P = .03), and less visual analog scale pain (VAS; OR = 1.7, P < .001). Differences in these factors between satisfied and not fully satisfied patients were identified as early as 6 weeks after surgery. CONCLUSION: Visibly different satisfaction profiles were captured among satisfied and not fully satisfied patient responses, with differences in patient-perceived joint function, general health, and pain severity occurring as early as 6 weeks after surgery. This study provides metrics to support early identification of patients at risk of poor TKA satisfaction, enabling clinicians to apply timely targeted treatment and support interventions, with the aim of improving patient outcomes.

Gait biomechanics phenotypes among total knee arthroplasty candidates by machine learning cluster analysis.

Knee osteoarthritis patient phenotyping is relevant to developing targeted treatments and assessing the treatment efficacy of total knee arthroplasty (TKA). This study aimed to identify clusters among TKA candidates based on demographic and knee mechanic features during gait, and compare gait changes between clusters postoperatively. TKA patients underwent 3D gait analysis 1-week pre (n = 134) and 1-year post-TKA (n = 105). Principal component analysis was applied to frontal and sagittal knee angle and moment waveforms, extracting major patterns of variability. Age, sex, body mass index, gait speed, and frontal and sagittal pre-TKA angle and moment PC scores previously identified as relevant to TKA outcomes were standardized (mean = 0, SD = 1, [134 × 15]). Multidimensional scaling and machine learning-based hierarchical clustering were applied. Final clusters were validated by examining intercluster differences pre-TKA and gait feature changes (PostPCscore - PrePCscore ) by k-way Χ2 and ANOVA tests. Four TKA candidate phenotypes yielded optimum clustering metrics, interpreted as higher and lower functioning clusters that were predominantly male and female. Higher functioning clusters pre-TKA (clusters 1 and 4) had more dynamic sagittal flexion moment (p < 0.001) and frontal plane adduction moment (p < 0.001) loading/un-loading patterns during stance. Post-TKA, higher functioning clusters demonstrated less knee mechanic improvements during gait (flexion angle p < 0.001; flexion moment p < 0.001). TKA candidates can be characterized by four clusters, predominately separated by sex and knee joint biomechanics. Post-TKA knee kinematics and kinetics improvements were cluster-specific; lower functioning clusters experienced more improvement. Cluster-based patient profiling may aid in triaging and developing OA management and surgical strategies meeting group-level function needs.

Individual Gait Features Are Associated with Clinical Improvement After Total Knee Arthroplasty.

BACKGROUND: Over 20% of patients do not report clinically relevant pain relief or functional improvements after total knee arthroplasty (TKA). The aim of this study was to investigate the effect of demographics, pre-TKA knee-joint biomechanics, and postoperative changes in knee biomechanics on meaningful improvements in self-reported pain and function after TKA. METHODS: Forty-six patients underwent 3-dimensional gait analysis and completed the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire before and 1 year after TKA. Response to treatment in terms of pain relief and functional improvement ("pain and function responders") was defined as improvements in WOMAC scores that met minimal clinically important difference thresholds in the pain and function domains. Differences between responder and non-responder demographics, severity of the osteoarthritis as seen radiographically, and knee kinematics and kinetics before TKA were explored using the t test and Mann-Whitney U test. Correlations and regression models were used to examine demographics, baseline knee kinematics and kinetics, and post-TKA kinematic and kinetic improvements associated with being a pain responder and a function responder separately. Analyses were conducted using a hypothesis-driving approach. RESULTS: Of the 46 patients, 34 were pain responders and 36 were function responders. Preoperatively, both responder groups had a higher radiographic severity (Kellgren-Lawrence) grade (p = 0.03) and pain responders were more symptomatic according to their WOMAC score (p < 0.04). Less preoperative stance-phase flexion-extension angle range (p ≤ 0.03), lower preoperative stance-phase adduction (varus) angle magnitude (p = 0.01), and less postoperative reduction in the adduction angle magnitude (p ≤ 0.009) were independently associated with more self-reported improvement in pain and function. CONCLUSIONS: Patients with a higher radiographic severity grade, with specific frontal and sagittal knee kinematic patterns during gait before TKA, and who demonstrated less reduction in frontal plane angles during gait after TKA had greater self-reported pain and function score improvements after standard TKA. Gait analysis may aid preoperative identification of kinematic subgroups associated with self-reported improvements after TKA, and provide evidence that may inform triaging, surgical planning, and expectation management strategies. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.