Trajectories of Pain and Function Outcomes up to 5 to 8 Years Following Total Knee Arthroplasty

Quantifying Physical Resilience after Knee or Hip Surgery in Older Australian Women Based on Long-Term Physical Functioning Trajectories

INTRODUCTION

To improve outcomes after knee or hip surgery, better insight is needed in long-term recovery patterns in the context of ageing-related decline. We examined long-term trajectories of physical functioning (PF) in older women with and without hip and knee surgery and described profiles of cases with higher and lower resilience after surgery.

METHODS

This observational study used data from 10,434 women (73-79 years) who completed survey 2 of the Australian Longitudinal Study on Women's Health. Data were used from surveys 2 (1999) to 6 (2011). Covariable-adjusted linear mixed models were run to examine the surgery-by-time (-12 to +12 years) interaction in association with PF (SF-36 subscale). The differences between observed and expected PF were calculated, with positive/negative values reflecting higher/lower resilience, respectively.

RESULTS

Women with hip surgery (n = 982) had lower PF than those without surgery (n = 8,117) (p < 0.001). Among hip surgery patients, the decline was more rapid pre-surgery than post-surgery (Δslope = -0.7, p < 0.001). Women with knee surgery (n = 1,144) had lower PF than those without surgery (n = 7,971), but with a slower rate of decline (p = 0.01). Among knee surgery patients, the rate of decline was similar pre- and post-surgery (Δslope = -0.3, p = 0.25). Both in hip and knee patients, women with higher resilience had fewer comorbidities and symptoms and were more often physically active and independent in daily activities than those with lower resilience (all p < 0.05).

CONCLUSION

Compared with women without surgery, PF was lower and declined more rapidly around the time of hip surgery, but not for knee surgery. Women with better long-term recovery after surgery had fewer health problems and were more independent around the time of surgery.

Using Two Predictive Models to Capture Two Types of Poor Outcomes in Knee Arthroplasty: A Multisite Longitudinal Cohort Study

OBJECTIVE

Poor outcome after knee arthroplasty (KA), a common major surgery worldwide, reportedly occurs in approximately 20% of patients. These patients demonstrate minimal improvement, at least moderate knee pain, and difficulty performing many routine daily activities. The purposes of our study were to comprehensively determine poor outcome risk after KA and to identify predictors of poor outcome.

METHODS

Data from 565 participants with KA in the Osteoarthritis Initiative and the Multicenter Osteoarthritis studies were used. Previously validated latent class analyses (LCAs) of good versus poor outcome trajectories of Western Ontario and McMaster Universities Arthritis Index (WOMAC) Pain and Disability were generated to describe minimal improvement and poor final outcome. The modified Escobar RAND appropriateness system was used to generate classifications of appropriate, inconclusive, and rarely appropriate. Multivariable prediction models included LCA-based good versus poor outcome, modified Escobar classifications, and evidence-driven preoperative prognostic variables.

RESULTS

Modified Escobar appropriateness classifications were nonsignificant predictors of WOMAC Pain good versus poor outcomes, indicating the methods provide independent outcome estimates. For WOMAC Pain and WOMAC Disability, approximately 34% and 45% of participants, respectively, had a high probability of either minimal improvement via "rarely appropriate" classifications or poor outcome via LCA. In multivariable prediction models, greater contralateral knee pain consistently predicted poor outcome (eg, odds ratio 1.21, 95% confidence interval 1.10-1.33).

CONCLUSION

Appropriateness criteria and LCA estimates provided combined poor outcome estimates that were approximately double the commonly reported poor outcome of 20%. Rates of poor outcome could be reduced if clinicians screened patients using appropriateness criteria and LCA predictors before surgery to optimize outcome.

Severe Postoperative Pain in Total Knee Arthroplasty Patients: Risk Factors, Insights and Implications for Pain Management via a Digital Health Approach

Up to 25% of patients undergoing knee arthroplasty report chronic pain postoperatively. Early identification of high-risk individuals can enhance pain management strategies. This retrospective analysis investigates the incidence of severe postoperative pain and its associated risk factors among 740 patients who underwent total knee arthroplasty. Utilizing a digital application, patients provided comprehensive data encompassing pre- and postoperative pain levels, analgesic usage, and completed a chronic pain risk assessment. Participants were categorized into two distinct groups based on their pain status at three months post-op: Group D+ (14%), characterized by pain scores exceeding 40/100 and/or the utilization of level 2 or 3 analgesics, and Group D- (86%), who did not meet these criteria. An analysis of pain trajectories within these groups revealed a non-linear progression, with specific patterns emerging amongst those predisposed to chronic pain. Notably, patients with a trajectory towards chronic pain exhibited a plateau in pain intensity approximately three weeks post-surgery. Significant preoperative risk factors were identified, including elevated initial pain levels, the presence of comorbidities, pain in other body areas, heightened joint sensitivity and stiffness. This study highlights the utility of digital platforms in enhancing patient care, particularly through the continuous monitoring of pain. Such an approach facilitates the early identification of potential complications and enables timely interventions.