High Intensity Exercise for Walking Competency in Individuals with Stroke: A Systematic Review and Meta-Analysis.

OBJECTIVE: To assess the effects of high intensity exercise on walking competency in individuals with stroke. DATA SOURCES: A systematic electronic searching of the PubMed, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL (EBSCOhost), and SPORTSDiscus (EBSCOhost) was initially performed up to June 25, 2019. STUDY SELECTION: Randomized controlled trials or clinical controlled trials comparing any walking or gait parameters of the high intensity exercise to lower intensity exercise or usual physical activities were included. The risk of bias of included studies was assessed by the Cochrane risk of bias tool. The quality of evidence was assessed using GRADE (Grading of Recommendations, Assessment, Development and Evaluation) system. DATA EXTRACTION: Data were extracted by 2 independent coders. The mean and standard deviation of the baseline and endpoint scores after training for walking distance, comfortable gait speed, gait analysis (cadence, stride length, and the gait symmetry), cost of walking, Berg Balance Scale , Time Up&Go (TUG) Test and adverse events were extracted. DATA SYNTHESIS: A total of 22 (n = 952) studies were included. Standardized mean difference (SMD), weighted mean difference (WMD), and odds ratios (ORs) were used to compute effect size and subgroup analysis was conducted to test the consistency of results with different characteristics of exercise and time since stroke. Sensitivity analysis was used to assess the robustness of the results, which revealed significant differences on walking distance (SMD = .32, 95% CI, .17-.46, P < .01, I2 = 39%; WMD = 21.76 m), comfortable gait speed (SMD = .28, 95% CI, .06-.49, P = .01, I2 = 47%; WMD = .04 m/s), stride length (SMD = .51, 95% CI, .13-.88, P < .01, I2 = 0%; WMD = .12 m) and TUG (SMD = -.36, 95% CI, -.72 to .01, P = .05, I2 = 9%; WMD = -1.89 s) in favor of high intensity exercise versus control group. No significant differences were found between the high intensity exercise and control group in adverse events, including falls (OR = 1.40, 95% CI, .69-2.85, P = .35, I2 = 11%), pain (OR = 3.34, 95% CI, .82-13.51, P = .09, I2 = 0%), and skin injuries (OR = 1.08, 95% CI, .30-3.90, P = .90, I2 = 0%). CONCLUSIONS: This systematic review suggests that high intensity exercise could be safe and more potent stimulus in enhancing walking competency in stroke survivors, with a capacity to improve walking distance, comfortable gait speed, stride length, and TUG compared with low to moderate intensity exercise or usual physical activities.

Strong convergence of an extragradient-type algorithm for the multiple-sets split equality problem.

This paper introduces a new extragradient-type method to solve the multiple-sets split equality problem (MSSEP). Under some suitable conditions, the strong convergence of an algorithm can be verified in the infinite-dimensional Hilbert spaces. Moreover, several numerical results are given to show the effectiveness of our algorithm.

Convergence analysis of an iterative algorithm for the extended regularized nonconvex variational inequalities.

In this paper, we suggest and analyze a new system of extended regularized nonconvex variational inequalities and prove the equivalence between the aforesaid system and a fixed point problem. We introduce a new perturbed projection iterative algorithm with mixed errors to find the solution of the system of extended regularized nonconvex variational inequalities. Furthermore, under moderate assumptions, we research the convergence analysis of the suggested iterative algorithm.