Three-dimensional gait analysis can shed new light on walking in patients with haemophilia

Abstract

In patients with haemophilia (PWH) (from Greek "blood love"), the long-term consequences of repeated haemarthrosis include cartilage damage and irreversible arthropathy, resulting in severe impairments in locomotion. Quantifying the extent of joint damage is therefore important in order to prevent disease progression and compare the efficacy of treatment strategies. Musculoskeletal impairments in PWH may stem from structural and functional abnormalities, which have traditionally been evaluated radiologically or clinically. However, these examinations are performed in a supine position (i.e., non-weight-bearing condition). We therefore suggest three-dimensional gait analysis (3DGA) as an innovative approach designed to focus on the functional component of the joint during the act of walking. This is of the utmost importance, as pain induced by weight-bearing activities influences the functional performance of the arthropathic joints significantly. This review endeavors to improve our knowledge of the biomechanical consequences of multiple arthropathies on gait pattern in adult patients with haemophilia using 3DGA. In PWH with arthropathy, the more the joint function was altered, the more the metabolic energy was consumed. 3DGA analysis could highlight the effect of an orthopedic disorder in PWH during walking. Indeed, mechanical and metabolic impairments were correlated to the progressive loss of active mobility into the joints.

Figures

Figure 1

The infrared cameras (a) are positioned so that at least two visualize each reflective marker at any given time. From the reflective markers movements we can calculate the 3D trajectories of the body segments (b). The images are then processed to derive the graphs of the kinematics, that is, the joint range of movement of each lower limb joint (c). A force platform located under the treadmill (b) records the patient's ground reaction forces. The joint moments and powers, that is, kinetic data, (d) are derived from force platform measurements and kinematic data. Energy expenditure is measured indirectly based on the rate of oxygen consumption by the patient using an ergospirometer (e). Finally, the mechanical work is calculated as the work performed by muscles to raise and accelerate the center of body mass (external mechanical work) and to move the body segments relative to the center of body mass (internal mechanical work) (f).

Figure 2

Inverted pendulum model of gait, showing how the center of body mass (CoM) rises during the single support and falls during the double support.

Figure 3

Net metabolic cost in 31 patients with haemophilia as a function of spontaneous walking speed. The severity of joint impairment is arbitrarily classified as “mild” (green symbol, uni/bilateral ankle arthropathy, n = 10), “moderate” (pink symbol, uni/bilateral ankle arthropathy + unilateral knee arthropathy/total knee replacement, n = 10), and “severe” (brown symbol, at least bilateral knee arthropathy/total knee replacement, n = 11).

Figure 4

Net metabolic cost in 31 patients with haemophilia as a function of the total ROM at ankles, knees, and hips levels. The dynamic ROM of the hip, knee, and ankle was calculated as follows: ankle: A3-A2 (A3-maximum plantar flexion at pushoff; A2-maximum dorsiflexion in stance); knee: K4-K3 (K4-maximum flexion in swing; K3-maximum extension at preswing); hip: H2-H1 (H2-maximum extension in stance; H1-flexion at initial contact). The ROM of lower limb joints were calculated for both sides and then summed. r = Pearson product moment correlation.