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Orthopaedic Proceedings
Vol. 101-B, Issue SUPP_11 | Pages 19 - 19
1 Oct 2019
Berend KR Lombardi AV Crawford DA Hurst JM Morris MJ
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Introduction. A smartphone-based care platform allows a customizable educational and exercise interface with patients, allowing many to recover after surgery without the need for formal physical therapy (PT). Furthermore, advances in wearable technology to monitor physical activity (PA) provides patients and physicians quantifiable metrics of the patient's recovery. The purpose of this study is to determine the feasibility of a smartphone-based exercise educational platform after primary knee arthroplasty as well as identifying factors that may predict the need for formal physical therapy. Methods. This study is part of a multi-institution, prospective study of patients after primary total knee arthroplasty (TKA) and partial knee arthroplasty (PKA) enrolled in a smartphone with smartwatch-based episode of care platform that recorded multimodal PA (steps, kcal, stairs). Postoperatively, all patients initially followed the smartphone-based exercise program. At the surgeon's discretion, patients were prescribed therapy if needed. The outcome of this study was the need for PT outside the app-based exercise program as well as time to return to preoperative step count. Variables assessed were preoperative weekly step counts (steps/day), weekly postoperative activity level (weekly step count compared to preoperative level), compliance with the exercise program (>75% completion) and patient demographic data including gender, age, BMI and narcotic use. One hundred eighty-eight patients were included in analysis: 45 PKA (24%) and 143 TKA (76%). Step count data was available on 135 patients and physical therapy data on 174. Results. Overall educational compliance was 91% and exercise compliance 34%. By 4-weeks postop, 45.6% of patients reached or exceeded their preoperative step count, including 60% of PKA and 41% of TKA (p=0.05). There was no significant difference in reaching step count based on gender (p=0.7), BMI <40kg/m2 (p=0.9) or age <65-years old (p=0.67). Sixty-three percent of patients that were compliant with the exercise program reached the step count compared to 40% of patients that weren't complaint (p=0.01). One hundred thirty-three patients (76.4%) completed the app-based exercise program without the need for PT, which included 81.4% of PKA patients and 75% of TKA patients (p=0.38). Weekly compliance with the exercise program (>75%) was significantly associated with not needing PT (p<0.001). Other factors that were significantly associated with the need for PT were a high physical activity level in postoperative week 1 (p<0.001) and a low physical activity level in postoperative week 2 (p=0.002). Conclusion. A high percentage of patients after primary knee arthroplasty were able to successfully complete the smartphone-based exercise program without the need for PT. Compliance with the exercise program was an important predictor of success. Postoperative activity level may also indicate the need for therapy as patients who were very active in the first postoperative week and then saw a decline in activity in the second week were more likely to be prescribed PT. With this platform, surgeons can monitor a patient's exercise compliance and postoperative activity level allowing many to recover at home, while being able to identify those within the first few weeks who may need structured physical therapy. For figures, tables, or references, please contact authors directly


The Bone & Joint Journal
Vol. 102-B, Issue 6 Supple A | Pages 129 - 137
1 Jun 2020
Knowlton CB Lundberg HJ Wimmer MA Jacobs JJ

Aims

A retrospective longitudinal study was conducted to compare directly volumetric wear of retrieved polyethylene inserts to predicted volumetric wear modelled from individual gait mechanics of total knee arthroplasty (TKA) patients.

Methods

In total, 11 retrieved polyethylene tibial inserts were matched with gait analysis testing performed on those patients. Volumetric wear on the articular surfaces was measured using a laser coordinate measure machine and autonomous reconstruction. Knee kinematics and kinetics from individual gait trials drove computational models to calculate medial and lateral tibiofemoral contact paths and forces. Sliding distance along the contact path, normal forces and implantation time were used as inputs to Archard’s equation of wear to predict volumetric wear from gait mechanics. Measured and modelled wear were compared for each component.