Prior Lumbar Spinal Arthrodesis Increases Risk of Prosthetic-Related Complication in Total Hip Arthroplasty

J Arthroplasty. 2016 Sep;31(9 Suppl):227-232.e1. doi: 10.1016/j.arth.2016.02.069. Epub 2016 Mar 15.

Abstract

Background: Degenerative hip disorders often coexist with degenerative changes of the lumbar spine. Limited data on this patient population suggest inferior functional improvement and pain relief after surgical management. The purpose of this study is to compare the rates of prosthetic-related complication after primary total hip arthroplasty (THA) in patients with and without prior lumbar spine arthrodesis (SA).

Methods: Medicare patients (n = 811,601) undergoing primary THA were identified and grouped by length of prior SA (no fusion, 1-2 levels fused [S-SAHA], and ≥3 levels fused [L-SAHA]).

Results: Compared with controls, patients with prior SA had significantly higher rates of complications including dislocation (control: 2.36%; S-SAHA: 4.26%; and L-SAHA: 7.51%), revision (control: 3.43%, S-SAHA: 5.55%, and L-SAHA: 7.77%), loosening (control: 1.33%, S-SAHA: 2.10%, and L-SAHA: 3.04%), and any prosthetic-related complication (control: 7.33%, S-SAHA: 11.15% [relative risk: 1.52], and L-SAHA: 14.16% [relative risk: 1.93]) within 24 months (P < .001).

Conclusion: The interplay of coexisting degenerative hip and spine disease deserves further attention of both arthroplasty and spine surgeons.

Keywords: complication; dislocation; hip arthroplasty; lumbar spine fusion; revision hip arthroplasty.

MeSH terms

  • Adult
  • Aged
  • Arthroplasty, Replacement, Hip / adverse effects*
  • Arthroplasty, Replacement, Hip / statistics & numerical data
  • Female
  • Hip Prosthesis / adverse effects*
  • Humans
  • Lumbar Vertebrae / surgery*
  • Male
  • Middle Aged
  • Postoperative Complications / epidemiology
  • Postoperative Complications / etiology*
  • Reoperation / statistics & numerical data
  • Retrospective Studies
  • Risk
  • Spinal Fusion / adverse effects*
  • Spinal Fusion / statistics & numerical data
  • United States / epidemiology