Prediction of mild anatomical leg length discrepancy based on gait kinematics and linear regression model

Highlights

• Hip flexion and adduction were positively correlated with leg length discrepancy.

• Lower limb kinematics during gait can be used as a screening tool to predict LLD.

• The model developed might prevent unnecessary x-rays and optimize rehabilitation.

• Gait kinematics might be affected by femur and tibia discrepancy in different ways.

Abstract

Backgound

Leg length discrepancy (LLD) can be related to different pathologies, due to an inadequate distribution of mechanical loads, as well as gait kinematics asymmetries resulted from LLD.

Research question

To validate a model to predict anatomical LLD (ALLD) based on gait kinematics.

Methods

Gait of 39 participants with different lower limb pathologies and mild discrepancy were collected. Pelvic, hip, knee and ankle kinematics were measured with a 3D motion analysis system and ALLD, femur discrepancy (FD) and tibia discrepancy (TD) were measured by a computerized digital radiograph. Three multiple linear regression models were used to identify the ability of kinematic variables to predict ALLD (model 1), FD (model 2) and TD (model 3).

Results

Difference between peak knee and hip flexion of the long and short lower limb was selected by models 1 (p < 0.001) and 2 (p < 0.001). Hip adduction was selected as a predictor only by model 1 (p = 0.05). Peak pelvic obliquity and ankle dorsiflexion were not selected by any model and model 3 did not retain any dependent variable (p > 0.05). Regression models predicted mild ALLD with moderate accuracy based on hip and knee kinematics during gait, but not ankle strategies. Excessive hip flexion of the longer limb possibly occurs to reduce the limb to equalize the LLD, and discrepancies of the femur and tibia affects gait cycle in a different way.

Significance

This study showed that kinematic variables during gait could be used as a screening tool to identify patients with ALLD, reducing unnecessary x-ray exposure and assisting rehabilitation programs.

Introduction

Leg length discrepancy (LLD) is present in 4% to 90% of the population in the world depending on the criterion of clinical significance adopted by researchers [1,2]. It can be classified as anatomical (ALLD), when the difference between limbs can be directly measured on tibias, femurs or both, or functional discrepancies (FLLD), identified on postural analysis such as an excessive pelvic obliquity, excessive knee flexion or excessive ankle eversion on a standing position [3]. Both ALLD and FLLD have been related to different pathologies, such as knee and hip osteoarthritis, due to an inadequate distribution of mechanical loads [4,5], as well as gait kinematics asymmetries resulted from LLD have been related to plantar fasciitis [6], low back pain [7], and anterior knee pain [8].

The length of the lower limb can be measured by multiple methods. The most popular in clinical practice is the tape-measure technique, consisting of the distance between anterior superior iliac spine (ASIS) and the tip of the medial malleolus of each limb while lying in a supine position, and calculating the absolute difference between both, and radiographic studies are considered the gold standards for measuring leg length, but they expose patients to ionizing radiation [9].

Asymmetries in human gait kinematics have been associated to ALLD magnitude [4]. Pelvic elevation and hip adduction of the longer leg in single limb support phase of gait are kinematic features found in patients with different ALLD magnitudes [10,11]. Alterations of flexion of the hip, knee and ankle on the sagittal plane were found in some studies [10,12], but not in others [13,14]. The inconsistency of results may be related to the different level of leg discrepancy among studies and the presence of real or simulated discrepancy.

So, the identification of the kinematic features able to predict mild ALLD in subjects with lower limb pain would help health care providers to minimize the x-ray exposure and to improve rehabilitation of individuals by addressing both the anatomic discrepancy and the functional disorders resulted from ALLD. Biomechanical gait analysis is a valid and reliable tool to estimate tissue overloads and is already used to guide the selection of several treatment approaches in many clinical settings [15]. Thus, this study aimed at validating a multiple linear regression model to predict ALLD based on lower limb kinematics data during gait. The results of this study would contribute to increase the applicability of gait analysis in orthopedic facilities.