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Mechanizing the Pivot Shift Test

  • Jelle P. van der List
  • Andrew D. PearleEmail author
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Abstract

The pivot shift test is a widely used test for anterior cruciate ligament (ACL) deficiency and has a high specificity. However, the test is subjective and has high interobserver variability. In order to overcome these disadvantages, we developed a mechanized pivot shift test. In this mechanized pivot shift, a modified continuous passive motion apparatus applies valgus force and internal rotation in human cadavers during the flexion–extension arc, while a navigation system tracks and quantifies the motion path. This standardized and mechanized setup was found to have an intraobserver test–retest reliability of 0.99. With this machine it was determined that ACL deficiency resulted in an 8.4 mm (mm) increase in lateral compartment anterior tibial translation (ATT) and that the difference between grade 0 pivot shift and grade ≥1 (positive) pivot shift has a threshold value of 6–7 mm. In addition, the roles of the lateral meniscus, iliotibial band, tibial slope, and tibial morphology were quantified as secondary stabilizers in knee stability. Using the mechanized pivot shift test, the different ACL reconstruction techniques and tibial tunnel placements were assessed and demonstrated that the double-bundle technique and anatomic single-bundle technique were better in restoring the lateral compartment ATT than the conventional technique. In knees that underwent radical meniscectomy, the double-bundle technique is favored over single-bundle techniques. In conclusion, using the mechanized pivot shift, the roles of several structures in the pivot shift were quantified. With the objectivity and high interobserver reliability, the mechanized pivot shift test assessed the role of several stabilizing structures in the knee.

Keywords

Anterior Cruciate Ligament Anterior Cruciate Ligament Reconstruction Pivot Shift Tibial Slope Pivot Shift Test 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Computer Assisted Surgery Center, Department of Orthopaedic SurgeryHospital for Special SurgeryNew YorkUSA

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