RESUMO
Foot drop during the swing phase of gait and at initial foot contact is a current kinematic abnormality that can occur following an upper motor neuron (UMN) lesion. Functional electrical stimulation (FES) of the common peroneal nerve through an assistive device is often used in neuro-rehabilitation to help patients regain mobility. Although there are FES-specific guideline recommendations, it remains a challenge for clinicians to appropriately select patients eligible for the daily use of FES devices, as very few health insurance systems cover its cost in Europe. In Luxembourg, since 2018, successfully completing an FES clinical pathway called CHECGAIT is a prerequisite to receiving financial coverage for FES devices from the national health fund (Caisse Nationale de Santé-CNS). This study describes the structure and steps of CHECGAIT and reports our experience with a cohort of 100 patients enrolled over a three-year period. The clinical and gait outcomes of all patients were retrospectively quantified, and a specific analysis was performed to highlight differences between patients with and without an FES device prescription at the end of a CHECGAIT. Several significant gait differences were found between these groups. These results and CHECGAIT may help clinicians to better select patients who can most benefit from this technology in their daily lives. In addition, CHECGAIT could provide significant savings to public health systems by avoiding unnecessary deliveries of FES devices.
RESUMO
BACKGROUND: Assessment of metabolic energy expenditure in post-stroke patients using accelerometers is clinically important. However, understanding of the best placement of accelerometers on the body and methods for calculating activity counts are limited. METHODS: Thirty hemiparetic post-stroke patients participated in this cross-sectional study. Four triaxial accelerometers were attached to the hemiplegic and contralateral sides of the waist and ankles during various activities: lying, sitting, standing, stepping in place, and walking on a treadmill (1-5 kmh-1). Activity counts and metabolic energy expenditure of the patients were recorded simultaneously. Simple linear regression analyses were performed between the activity counts and energy expenditure. Activities were classified according to their intensity, using the definition of energetic sedentary behavior of post-stroke patients and a low fitness level group. RESULTS: The best estimate of energy expenditure was obtained when the accelerometer was worn on the contralateral ankle and the activity counts was calculated using the vertical and anteroposterior axes (R2=0.812). Six classes of activity intensity (sedentary: ≤1.5 METs, very light: 1.51-1.79, light: 1.80-2.59, moderate: 2.60-3.39, hard: 3.40-4.39, and very hard: ≥4.40) and corresponding activity counts cut-off points are presented. CONCLUSION: A triaxial accelerometer worn on the contralateral ankle and a method of calculating activity counts that includes at least the vertical and anteroposterior axes are recommended for estimating metabolic energy expenditure in post-stroke patients. The new activity counts cut-off points provide a significant advance in the interpretation of post-stroke monitoring in patients outside the hospital or rehabilitation center.
