Multilevel Modeling of Resection Accuracy: Insights from 10,144 Clinical Cases using A Contemporary Computer-Assisted Total Knee Arthroplasty System

4 pages•Published: October 26, 2019

Yifei Dai, Charlotte Bolch, Amaury Jung and Cyril Hamad

Abstract

This study applied an advanced statistical tool (multilevel modeling) to assess the accuracy of bony resection during total knee arthroplasty on 10144 cases performed using a modern CAOS system. An extensive list of factors was included for the modeling, including geographic region, inter-surgeon difference, surgeon’s adoption of the technology (learning or proficient phases), and historical progression of the CAOS application (software versions). The comprehensive analysis demonstrated that the CAOS system is an accurate and precise solution to assist the surgeons to achieve his/her surgical resection goals.

Keyphrases: big data analysis, computer assisted orthopedic surgery, multilevel modeling, total knee arthroplasty

In: Patrick Meere and Ferdinando Rodriguez Y Baena (editors). CAOS 2019. The 19th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, vol 3, pages 98-101.

Links:	https://easychair.org/publications/paper/2lgj
	https://doi.org/10.29007/d346

BibTeX entry

@inproceedings{CAOS2019:Multilevel_Modeling_Resection_Accuracy,
  author    = {Yifei Dai and Charlotte Bolch and Amaury Jung and Cyril Hamad},
  title     = {Multilevel Modeling of Resection Accuracy: Insights from 10,144 Clinical Cases using A Contemporary Computer-Assisted Total Knee Arthroplasty System},
  booktitle = {CAOS 2019. The 19th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery},
  editor    = {Patrick Meere and Ferdinando Rodriguez Y Baena},
  series    = {EPiC Series in Health Sciences},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-5305},
  url       = {/publications/paper/2lgj},
  doi       = {10.29007/d346},
  pages     = {98-101},
  year      = {2019}}

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