Predicting Mobility Limitations in Patients With Total Knee Arthroplasty in the Inpatient Setting

Eleanor Shu Xian Chew, Seng Jin Yeo, Terry Haines, Julian Thumboo, Ross Allan Clark, Hwei Chi Chong, Cheryl Lian Li Poon, Felicia Jie Ting Seah, Darren Keng Jin Tay, Nee Hee Pang, Celia Ia Choo Tan, Yong Hao Pua

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Objective: To develop a prediction model for postoperative day 3 mobility limitations in patients undergoing total knee arthroplasty (TKA). Design: Prospective cohort study. Setting: Inpatients in a tertiary care hospital. Participants: A sample of patients (N=2300) who underwent primary TKA in 2016-2017. Interventions: Not applicable. Main Outcome Measure: Candidate predictors included demographic variables and preoperative clinical and psychosocial measures. The outcome of interest was mobility limitations on post-TKA day 3, and this was determined a priori by an ordinal mobility outcome hierarchy based on the type of the gait aids prescribed and the level of physiotherapist assistance provided. To develop the model, we fitted a multivariable proportional odds regression model with bootstrap internal validation. We used a model approximation approach to create a simplified model that approximated predictions from the full model with 95% accuracy. Results: On post-TKA day 3, 11% of patients required both walkers and therapist assistance to ambulate safely. Our prediction model had a concordance index of 0.72 (95% confidence interval, 0.68-0.75) when evaluating these patients. In the simplified model, predictors of greater mobility limitations included older age, greater walking aid support required preoperatively, less preoperative knee flexion range of movement, low-volume surgeon, contralateral knee pain, higher body mass index, non-Chinese race, and greater self-reported walking limitations preoperatively. Conclusion: We have developed a prediction model to identify patients who are at risk for mobility limitations in the inpatient setting. When used preoperatively as part of a shared-decision making process, it can potentially influence rehabilitation strategies and facilitate discharge planning.

Original languageEnglish
Pages (from-to)2106-2112
Number of pages7
JournalArchives of Physical Medicine and Rehabilitation
Issue number11
Publication statusPublished - Nov 2019


  • Knee
  • Models
  • Prognosis
  • Rehabilitation
  • Risk
  • Statistical

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