Outcome measures for clinical care

Whether an individual patient is in rehabilitation as an inpatient or outpatient or participating in a clinical trial, sensitive and reliable outcome measures help determine the success of an intervention for walking.

Physiological measures

Walking speed over 10 m or 50 ft, 2- or 6-min walking distance and heart rate change from rest, a timed stand up and walk task, and measures of impairment such as the Berg balance scale, Fugl-Meyer motor assessment, and ASIA motor score provide quick and reliable measures relevant to walking after stroke or SCI (Steffen et al., 2002; Duncan et al., 2003b). These measures may be more sensitive to changes during a subacute intervention compared to a treatment in chronically disabled subjects. The Multiple Sclerosis Functional Composite scale includes a 25-foot timed walk that, with its other two measures, has proven valuable for clinical trials (Kalkers et al., 2000). Serial monitoring of walking speed can serve as both a measure and an incentive for progress during formal rehabilitation and for practice at home. Scales for spasticity, such as the Ashworth scale, are of no value as an outcome measure. Resistance to movement tested at a single joint while supine cannot be correlated with hypertonicity and impaired motor control during walking.

Time spent walking can be measured using an accelerometer that records activity (Coleman et al., 1999; Zhang et al., 2003). With well-designed software, accelerometers placed on the trunk, each thigh, and under each foot reveal both temporal aspects of the gait cycle and acceleration forces at key points in the step cycle, such as at toe off and initial swing. Figure 3.3 shows the step cycle from one foot accelerometer obtained using a commercial device, the Intelligent Device for Energy Expenditure and Physical Activity (IDEEA) system (MiniSun, Fresno, CA). Table 3.3 was calculated from gait cycle data recording from bilateral foot and thigh accelerometers.

Functional neuroimaging may serve to reveal the nodes of the supraspinal networks that are engaged over the course of a training intervention. For example, near-infrared spectroscopy has assessed changes in M1S1 and premotor cortex that contribute to improved motor control during walking on a treadmill (Miyai et al., 2003). Using an ankle dorsiflexion fMRI activation paradigm, changes over time of gait training can be shown after SCI, stroke, and in children after hemispherectomy for epilepsy (Dobkin, 2000b; Dobkin et al., 2004; de Bode et al., 2005). These techniques may provide insight into the optimal duration of an intervention and the effects of medications on cortical representational plasticity. Ankle dorsiflexion or other active and passive leg movements may also be of value in discerning the completeness of a SCI and in determining the functional effects of a subcortical or spinal neural repair strategy.

Functional measures

The locomotor score (0-7) of the Functional Independence Measure (FIM) and of the Barthel Index (dependent, need help, independent) offer insight into the need for assistance and thus the burden of care related to walking. A measure such as the Walking Index for SCI (WISCI) takes into account the physical help, braces and assistive devices needed and reflects, in part, functional limitations (Ditunno and Ditunno, 2001). In the SCILT trial, the locomotor FIM and the WISCI correlated with lower extremity strength and walking speed. The Stroke Impact Scale and the physical activity portion of the SF-36 for any neurological disease may reveal how patients assess themselves for mobility tasks in everyday activities, which reflects health-related quality of life (Ware and Sherbourne, 1992; Vickrey et al., 1995, 2000; Duncan et al., 2003a).

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