Predicting post-operative functional ability from pre-operative measures in ACL injured individuals

Research output: Contribution to journalJournal articleResearchpeer-review

PURPOSE: This study aimed to quantify the relationship between objective and subjective measures of functional ability and determine if measures in the deficient (ACLd) state were correlated to, and capable of predicting a patient's objective and subjective measures in the reconstructed (ACLr) state.

METHODS: Twenty ACL injured participants completed hop and side cut movements prior to and 10 months post-reconstruction. Their subjective measures (Tegner, Lysholm, IKDC, KOOS, and KNEEs) were related to objective measures of functional ability (peak knee flexion, peak knee extensor moment, stiffness, knee joint center excursion (KJCE), and knee joint center boundary). Correlations were used to determine relationships between variables whereas regressions were used to identify ACLd score's predictive ability of an ACLr score.

RESULTS: Relationships between objective and subjective measures were task and ACL status dependent with KJCE and stiffness most commonly being related to subjective scores. The greatest correlation was between knee stiffness and Tegner in the ACLr group during the side cut (r = 0.69). Peak knee flexion angle (adj. R2 = 0.4 - 0.66) was the best objective predictor between ACLd and ACLr states while KOOS-ADL had the strongest correlations (r = 0.70 - 0.77) and Tegner had the greatest predictive power (Odds Ratio: 1.46 -1.86) between states in both tasks.

CONCLUSION: Objective measures show a wide range of correlation to subjective measures with some being quite strong. Furthermore, objective measures in the ACLd state are more correlated and more often capable of predicting ACLr scores than the subjective measures of functional ability. This article is protected by copyright. All rights reserved.

Original languageEnglish
JournalScandinavian Journal of Medicine & Science in Sports
Issue number1
Pages (from-to)166-173
Number of pages8
Publication statusPublished - 2020

ID: 227012945