2017 ISAKOS Biennial Congress ePoster #1805

 

Patient and Injury Characteristics do not Accurately Predict Risk of Below-Normal Quality of Life Following Multiple-Ligament Knee Injury and Reconstruction

Brett A. Fritsch, MBBS BSc(Med), FRACS, FAOrthA, Hunters Hill, NSW AUSTRALIA
Corey Scholes, PhD, Crows Nest, NSW AUSTRALIA
Martin Sebastian Di Nallo, MD, East Gresford, NSW AUSTRALIA
Laurant Kang, Chatswood, NSW AUSTRALIA
Myles R. J. Coolican, FRACS, Sydney, NSW AUSTRALIA
David A. Parker, MBBS, BMedSc, FRACS, Sydney, NSW AUSTRALIA

Sydney Orthopaedic Research Institute, Chatswood, NSW, AUSTRALIA

FDA Status Not Applicable

Summary

Clinical and patient-reported outcomes of a large series of multiple-ligament knee injuries with and without surgical reconstruction.

Abstract

Background

Multiligament knee injury (MLKI) are rare but serious injuries that present management challenges and often lead to long term functional deficits. Although the results of numerous case series’ have been reported, most suffer from small numbers, poor followup, and lack of definitive conclusions about outcomes. The objectives of this study are to i) describe patients demographics and injury patterns in a large cohort of MLKIs and ii) determine the relationship between these variables and patient reported outcomes.

Materials & Methods:
All patients treated for multi-ligament knee injuries in one practice group from 1989-2015 were identified from a prospective clinical registry. Inclusion criteria for review were age greater than 16, complete rupture of 2 or more major knee ligaments, and minimum 1 year follow-up. Patients were excluded if they had any prior known injury or problems with the affected knee. Injury and treatment details were collected retrospectively for cases prior to 2002, and prospectively thereafter. Subjective outcomes scores (KOOS) were obtained at a minimum of one year following definitive treatment. Patients results were compared and normalised to population data, and defined as “below normal” if they fell under <1 standard deviation of the average for age and gender. Stepwise binary logistic regression was used to test for differences in patient and injury characteristics between those classed as normal and below normal for KOOS Quality of Life subscale.

Results

A cohort of 184 patients (72.3% male; 32.6+12.1yrs; median follow-up 2yrs, IQR 1 - 4) with confirmed MLKI was included for evaluation, with 149 undergoing surgical intervention (81%). Injuries to one cruciate ligament combined with a lateral structure were the most common injury pattern (28.3%), followed by bicruciate and medial injuries (24.3%). Associated injuries were observed in many patients, including fractures (10.2%), meniscal injury (10.7%), nerve injury (13%) and vascular injury (4%). A total of 94 patients (64 male; 32.6yrs; 43.9months) provided KOOS responses at a minimum of 1 year of follow-up. The proportion of patients that provided below-normal results ranged from 28.7% (KOOS-ADL) to 59.6% (KOOS – Quality of Life). However, logistic regression was unable to clearly identify patient and injury characteristics predictive of increased risk of below-normal classification (R2 = 4.9%).

Conclusions

This study represents one of the largest cohorts of MLKI reported, and provides a detailed analysis of injury patterns, patient demographics and outcomes. After at least one year of follow-up, the majority of patients reported a pain free functional knee that allowed them to perform their daily activities, and remained within population normal ranges. Despite potentially devastating MLK injuries, patients commonly report ultimately good functional outcomes, with the actual outcome not clearly predicted by demographics and injury characteristics. This study provides valuable information about the characteristics of these patients and their injuries, and the overall outcomes, but the continued lack of clear predictions for outcomes on an individual level illustrates the need for ongoing study of all variables that may influence the outcome of these injuries.