Adverse Events During Submaximal Aerobic Exercise Testing in People With Subacute Stroke: A Scoping Review.

BACKGROUND AND PURPOSE: Concern for adverse cardiovascular events and limited guidance regarding how to conduct aerobic exercise (AEx) testing for individuals poststroke are key barriers to implementation by physical therapists in stroke rehabilitation. This study aimed to describe the nature and safety of submaximal AEx testing protocols for people with subacute stroke (PwSS) and the nature of comorbidity of PwSS who underwent submaximal AEx testing. METHODS: We conducted a scoping review and searched MEDLINE, EMBASE, PsycINFO, CINAHL, and SPORTDiscus from inception to October 29, 2020. Studies involving submaximal AEx testing with PwSS, reporting on participant comorbidity and on adverse events during testing, were eligible. Two reviewers independently conducted title and abstract and full-text screening. One reviewer extracted data; a second reviewer verified data. RESULTS: Thirteen studies involving 452 participants and 19 submaximal AEx testing protocols (10 field test, 7 incremental, and 2 constant load) were included. Hypertension (41%), diabetes (31%), and dyslipidemia (27%) were the most common comorbidities reported. No protocols resulted in a serious adverse event. The most common test termination criterion was a heart rate (HR) limit (9 protocols); a limit of 85% age-predicted maximal HR (APM-HR) most frequently reported. Average APM-HR achieved, computed using mean age and mean peak HR, ranged from 59% to 88% across 13 protocols. DISCUSSION AND CONCLUSION: Diverse submaximal AEx testing protocols with conservative test termination criteria can be safely implemented with PwSS. Results can inform clinical practice guidelines and address physical therapists' concerns with the occurrence of serious adverse events during submaximal AEx testing.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A430 ).

Mobile Technology-Based Interventions for Stroke Self-Management Support: Scoping Review.

BACKGROUND: There is growing interest in enhancing stroke self-management support using mobile health (mHealth) technology (eg, smartphones and apps). Despite this growing interest, "self-management support" is inconsistently defined and applied in the poststroke mHealth intervention literature, which limits efforts to synthesize and compare evidence. To address this gap in conceptual clarity, a scoping review was conducted. OBJECTIVE: The objectives were to (1) identify and describe the types of poststroke mHealth interventions evaluated using a randomized controlled trial design, (2) determine whether (and how) such interventions align with well-accepted conceptualizations of self-management support (the theory by Lorig and Holman and the Practical Reviews in Self-Management Support [PRISMS] taxonomy by Pearce and colleagues), and (3) identify the mHealth functions that facilitate self-management. METHODS: A scoping review was conducted according to the methodology by Arksey and O'Malley and Levac et al. In total, 7 databases were searched. Article screening and data extraction were performed by 2 reviewers. The data were analyzed using descriptive statistics and content analysis. RESULTS: A total of 29 studies (26 interventions) were included. The interventions addressed 7 focal areas (physical exercise, risk factor management, linguistic exercise, activities of daily living training, medication adherence, stroke education, and weight management), 5 types of mobile devices (mobile phones or smartphones, tablets, wearable sensors, wireless monitoring devices, and laptops), and 7 mHealth functions (educating, communicating, goal setting, monitoring, providing feedback, reminding, and motivating). Collectively, the interventions aligned well with the concept of self-management support. However, on an individual basis (per intervention), the alignment was less strong. CONCLUSIONS: On the basis of the results, it is recommended that future research on poststroke mHealth interventions be more theoretically driven, more multidisciplinary, and larger in scale.