Reduced postoperative morbidity in computer-navigated total knee arthroplasty: A retrospective comparison of 225,123 cases. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Total knee arthroplasty (TKA) is one of the most common elective surgical procedures in the United States, with more than 650,000 performed annually. Computer navigation technology has recently been introduced to assist surgeons with planning, performing, and assessing TKA bone cuts. The aim of this study is to assess postoperative complication rates after TKA performed using computer navigation assistance versus conventional methods. METHODS: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database was queried for unilateral TKA cases from 2008 to 2016. The presence of the CPT modifier for use of computer navigation was used to separate cases of computer-navigated TKA from conventional TKA. Multivariate and propensity-matched logistic regression analyses were performed to control for demographics and comorbidities. RESULTS: There were 225,123 TKA cases included; 219,880 were conventional TKA (97.7%) and 5,243 were navigated (2.3%). Propensity matching identified 4,811 case pairs. Analysis demonstrated no significant differences in operative time, length of stay, reoperation, or readmission, and no differences in rates of post-op mortality at 30 days postoperatively. Compared to conventional cases, navigated cases were at lower risk of serious medical morbidity (18% lower, p = 0.009) within the first 30 days postoperatively. CONCLUSION: After controlling for multiple known risk factors, navigated TKA patients demonstrated lower risk for medical morbidity, predominantly driven by lower risk for blood transfusion. Given these findings, computer-navigation is a safe surgical technique in TKA.

publication date

  • April 27, 2021

Research

keywords

  • Arthroplasty, Replacement, Knee
  • Blood Transfusion
  • Postoperative Complications
  • Reoperation
  • Surgery, Computer-Assisted

Identity

Scopus Document Identifier

  • 85108741981

Digital Object Identifier (DOI)

  • 10.1016/j.knee.2020.12.015

PubMed ID

  • 33930702

Additional Document Info

volume

  • 30