Literature DB >> 30528677

The Learning Curve by Operative Time for Soft Tissue Balancing in Total Knee Arthroplasty Using Electronic Sensor Technology.

Akshay Lakra1, Nana O Sarpong1, Emma L Jennings1, Matthew J Grosso1, H John Cooper1, Roshan P Shah1, Jeffrey A Geller1.   

Abstract

BACKGROUND: Electronic sensor devices can provide an objective assessment of soft tissue balancing in total knee arthroplasty (TKA) which may potentially decrease postoperative pain. We aim to quantify the learning curve for operative time (OT) for this technology.
METHODS: Consecutive TKA cases balanced with an electronic sensor balancing device by one senior surgeon from 2013 to 2017 were included in this study. The OT (in minutes) was analyzed using the cumulative sum analysis to evaluate the learning curve for this technology. Further analysis was done by splitting the 287 patients into 7 cohorts, 41 patients each.
RESULTS: Two hundred eighty-seven patients balanced with sensor technology were available for analysis. The cumulative sum OT learning curve estimated that this technology's learning curve was 41 cases. This curve consisted of 2 phases: phase 1 which includes the first 41 cases and phase 2 which includes the remaining 246 patients. The mean OT for the first and last sensor-assisted cohorts was 120.4 and 108.9 minutes (P = .021). The mean OT for the first sensor-assisted cohort and the control cohort was 120.4 versus 109 minutes (P = .023). The mean OT for the last sensor-assisted cohort and the control cohort was 108.9 versus 109 minutes (P = .94).
CONCLUSION: Our findings suggest that it takes approximately 41 cases of sensor-assisted TKA cases to achieve OTs identical to manually balanced TKA cases. This is a relatively shallow learning curve for the sensor technology, and allows arthroplasty surgeons to objectively achieve soft tissue balancing without adding OT to the surgery.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  learning curve; orthoSensors; smart tibial tray; soft tissue balance; total knee arthroplasty

Mesh:

Year:  2018        PMID: 30528677     DOI: 10.1016/j.arth.2018.11.014

Source DB:  PubMed          Journal:  J Arthroplasty        ISSN: 0883-5403            Impact factor:   4.757


  6 in total

Review 1.  What Is the Learning Curve for New Technologies in Total Joint Arthroplasty? A Review.

Authors:  Nana O Sarpong; Carl L Herndon; Michael B Held; Alexander L Neuwirth; Thomas R Hickernell; Jeffrey A Geller; H John Cooper; Roshan P Shah
Journal:  Curr Rev Musculoskelet Med       Date:  2020-12

2.  Smart sensor implant technology in total knee arthroplasty.

Authors:  Karthikeyan P Iyengar; Benjamin Thomas Vincent Gowers; Vijay Kumar Jain; Raju S Ahluwalia; Rajesh Botchu; Raju Vaishya
Journal:  J Clin Orthop Trauma       Date:  2021-09-22

3.  The application of machine learning to balance a total knee arthroplasty.

Authors:  Matthias A Verstraete; Ryan E Moore; Martin Roche; Michael A Conditt
Journal:  Bone Jt Open       Date:  2020-06-11

4.  How to Quantitatively Balance a Total Knee? A Surgical Algorithm to Assure Balance and Control Alignment.

Authors:  Ryan E Moore; Michael A Conditt; Martin W Roche; Matthias A Verstraete
Journal:  Sensors (Basel)       Date:  2021-01-20       Impact factor: 3.576

Review 5.  Sensor-Assisted Total Knee Arthroplasty: A Narrative Review.

Authors:  Cheol Hee Park; Sang Jun Song
Journal:  Clin Orthop Surg       Date:  2021-02-15

6.  Accuracy of soft tissue balancing in total knee arthroplasty using surgeon-defined assessment versus a gap-balancer or electronic sensor.

Authors:  Ran Zhao; Yanqing Liu; Hua Tian
Journal:  J Orthop Surg Res       Date:  2021-05-08       Impact factor: 2.359

  6 in total

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