M. Luz Sánchez-Sánchez

Pilot randomized controlled trial to assess a physical therapy program on upper extremity function to counteract inactivity in chronic stroke

Background: In chronic stroke, feasible physical therapy (PT) programs are needed to promote function throughout life. Objective: This randomized controlled pilot trial investigated the feasibility and effect of a PT program composed of strengthening exercises with elastic bands and bimanual functional training, with clearly defined doses based on the rate of perceived exertion (Borg scale), to counteract inactivity in chronic stroke. Methods: Fifteen subjects > 6 month post-stroke were randomized to three-month of UE function training (UE group), or to lower extremity function training (LE group). At baseline (T0), post-intervention (T1) and three-month follow-up (T2) assessment included the Fugl-Meyer Assessment scale (FMA), Wolf Motor Function test (WMFT), grip strength, and muscle tone. Feasibility was also evaluated. Results: The mixed-model ANOVAs revealed a significant interaction between the time and group factors for FMA (p < .001) and WMFT (p = .009). The UE group improved upper extremity function and motor recovery significantly more than the LE group. There was no significant interaction between treatment group and change in grip strength over time (p = .217). No between-group differences (p > .05) were found in muscle tone. In the UE group, the attendance rate was ≥85% for 71.4% of subjects and 85.7% showed high satisfaction. No adverse events were recorded. After treatment, adherence to the program was higher in the UE group. Conclusions: The suggested PT program may be useful to improve the paretic UE function and motor recovery in chronic stroke. Moreover, it may be helpful to facilitate lifelong active involvement of stroke subjects in exercise.

Tackling frailty and functional decline: Background of the action group A3 of the European innovation partnership for active and healthy ageing

Ageing populations represent a challenge to the sustainability of current healthcare systems. The need to balance these demographic changes with gains in healthy life years and quality of life (QoL) constitutes an additional challenge. Aware of this, the European Commission (EC) launched the European Innovation Partnership on Active and Healthy Ageing (EIPonAHA) in 2012. The EIPonAHA is an interdisciplinary and cross-sector initiative involving more than 3000 partners with two specific objectives: to increase the healthy life expectancy of Europeans by two years by 2020, while increasing their QoL. The initiatives of the EIPonAHA have been organized according to six thematic action groups (AGs), with the A3 group targeting areas relating to the prevention of functional decline and frailty. In addition to the good practices of partners, there are several on-going collaborative works. The involvement of the EC includes support through an elaborated research programme in which the Consumers, Health, Agriculture and Food Executive Agency (CHAFEA) and the Directorate-General for Communications Networks, Content and Technology (DG CONNECT) are the main funding bodies. Screening approaches and preventive interventions constitute most of the initiatives within the A3 AG. Partners are distributed across five sub-groups according to good practices: i) cognitive decline, ii) food and nutrition, iii) physical activity, iv) caregivers, and v) frailty and functional decline. Regular updates of the progression of both good practices and collaborative works are presented in A3 AG meetings. The 2017 meeting in Valencia, Spain, showcased in this paper, provides an up-to-date overview of the current status of A3 activities.

A new methodology for Functional Principal Component Analysis from scarce data. Application to stroke rehabilitation

Functional Principal Component Analysis (FPCA) is an increasingly used methodology for analysis of biomedical data. This methodology aims to obtain Functional Principal Components (FPCs) from Functional Data (time dependent functions). However, in biomedical data, the most common scenario of this analysis is from discrete time values. Standard procedures for FPCA require obtaining the functional data from these discrete values before extracting the FPCs. The problem appears when there are missing values in a non-negligible sample of subjects, especially at the beginning or the end of the study, because this approach can compromise the analysis due to the need to extrapolate or dismiss subjects with missing values. In this paper, we present an alternative methodology extracting the FPCs directly from the sampled data, avoiding the need to have functional data before extracting them. We demonstrate the feasibility of our approach from real data obtained from the analysis of balance recovery after stroke. Finally, we demonstrate that FPCA can obtain differences between groups when these differences are more related to the dynamics of the process than data values at given points.