Effect of personal activity intelligence (PAI) monitoring in the maintenance phase of cardiac rehabilitation: a mixed methods evaluation

eHealth for maintenance cardiovascular rehabilitation: a systematic review and meta-analysis

AIMS

To provide a quantitative analysis of eHealth-supported interventions on health outcomes in cardiovascular rehabilitation (CR) maintenance (phase III) in patients with coronary artery disease (CAD) and to identify effective behavioural change techniques (BCTs).

METHODS AND RESULTS

A systematic review was conducted (PubMed, CINAHL, MEDLINE, and Web of Science) to summarize and synthesize the effects of eHealth in phase III maintenance on health outcomes including physical activity (PA) and exercise capacity, quality of life (QoL), mental health, self-efficacy, clinical variables, and events/rehospitalization. A meta-analysis following the Cochrane Collaboration guidelines using Review Manager (RevMan5.4) was performed. Analyses were conducted differentiating between short-term (≤6 months) and medium/long-term effects (>6 months). Effective behavioural change techniques were defined based on the described intervention and coded according to the BCT handbook. Fourteen eligible studies (1497 patients) were included. eHealth significantly promoted PA (SMD = 0.35; 95%CI 0.02-0.70; P = 0.04) and exercise capacity after 6 months (SMD = 0.29; 95%CI 0.05-0.52; P = 0.02) compared with usual care. Quality of life was higher with eHealth compared with care as usual (SMD = 0.17; 95%CI 0.02-0.32; P = 0.02). Systolic blood pressure decreased after 6 months with eHealth compared with care as usual (SMD = -0.20; 95%CI -0.40-0.00; P = 0.046). There was substantial heterogeneity in the adapted BCTs and type of intervention. Mapping of BCTs revealed that self-monitoring of behaviour and/or goal setting as well as feedback on behaviour were most frequently included.

CONCLUSION

eHealth in phase III CR is effective in stimulating PA and improving exercise capacity in patients with CAD while increasing QoL and decreasing systolic blood pressure. Currently, data of eHealth effects on morbidity, mortality, and clinical outcomes are scarce and should be investigated in future studies.

REGISTRATION

PROSPERO: CRD42020203578.

Role of wearable devices in cardiac telerehabilitation: A scoping review

BACKGROUND

Cardiac rehabilitation (CR) is an evidence-based comprehensive program that includes exercise training, health education, physical activity promotion, and extensive counseling for the management of cardiovascular risk factors. Wearable devices monitor certain physiological functions, providing biometric data such as heart rate, movement, sleep, ECG analysis, blood pressure, energy expenditure, and numerous other parameters. Recent evidence supports wearable devices as a likely relevant component in cardiovascular risk assessment and disease prevention. The purpose of this scoping review is to better understand the role of wearable devices in home-based CR (HBCR) and to characterize the evidence regarding the incorporation of wearable devices in HBCR programs and cardiovascular outcomes.

METHODS & FINDINGS

We created a search strategy for multiple databases, including PubMed, Embase (Elsevier), CINAHL (Ebsco), Cochrane CENTRAL (Wiley), and Scopus (Elsevier). Studies were included if the patients were eligible for CR per Medicare guidelines and >18 years of age and if some type of wearable device was utilized during HBCR. Our search yielded 57 studies meeting all criteria. The studies were classified into 4 groups: patients with coronary heart disease (CHD) without heart failure (HF); patients with HF; patients with heart valve repair or replacement; and patients with exposure to center-based CR. In three groups, there was an upward trend toward improvement in quality of life (QOL) and peak VO2, less sedentary time, and an increase in daily step count in the intervention groups compared to control groups.

CONCLUSIONS

HBCR using wearable devices can be a comparable alternative or adjunct to center-based CR for patients with CHD and HF. More studies are needed to draw conclusions about the comparability of HBCR to center-based CR in patients with heart valve repair or replacement.

Benefits, Facilitators, and Barriers of Alternative Models of Cardiac Rehabilitation: A QUALITATIVE SYSTEMATIC REVIEW

PURPOSE

Cardiac rehabilitation (CR) improves health outcomes and quality of life for patients with cardiovascular disease, yet only a quarter of eligible patients enroll. A myriad of CR models that use either an alternative location (ie, home-based) and/or an alternative exercise have been developed to overcome known attendance and physical limitation barriers; however, patient experiences with these models have not been systematically reviewed. Our aim is to review patient experiences with these models of CR.

REVIEW METHODS

We conducted a systematic review and thematic analysis of qualitative studies published between 2009 and January of 2022 from CINAHL, PubMed, Web of Science, and PsycINFO.

SUMMARY

Twenty-five studies were included, representing the perspectives of 487 individuals who participated in an alternative model of CR. Exercises included walking, tai chi, yoga, aquatic exercise, exergaming, chair-based exercises, aerobics, physical activity trackers, and individualized exercise plans. Nineteen of 25 studies used home-based models and two used live video. Twelve studies included patients with heart failure. Patient perspectives comprised three central themes: exercise benefits, exercise facilitators, and participation barriers. Some thematic categories were reported variably by particular model/study design (eg, home-based) than by others. All alternative models of CR were found to be physically, psychologically, and/or socially beneficial to patients. Participants described facilitators and barriers that were influential in the decision to initiate or continue exercise. These patient insights are critical for innovative delivery of CR that is appealing, accommodates physical limitations, and broadens access to improve health equity.

Using Personal Activity Intelligence With Patients in a Clinic Setting

BACKGROUND

Personal Activity Intelligence (PAI) is a novel heart-rate-based metric used to assess cardiorespiratory fitness and quantify physical activity.

OBJECTIVE

The aim of this study was to examine the feasibility, acceptability, and effectiveness of PAI with patients in a clinic setting.

METHODS

Patients (n = 25) from 2 clinics underwent 12 weeks of heart-rate-monitored physical activity interfaced with aPAI Health phone app. We used a pre-post design with the Physical Activity Vital Sign and the International Physical Activity Questionnaire. Feasibility, acceptability, and PAI measures were used to evaluate the objectives.

RESULTS

Twenty-two patients (88%) completed the study. There were significant improvements in International Physical Activity Questionnaire metabolic equivalent task minutes per week ( P = .046) and a decrease in sitting hours ( P = .0001). The Physical Activity Vital Sign activity increase in minutes per week was not significant ( P = .214). Patients achieved a mean PAI score of 116 ± 81.1 and 100 or greater 71% of the days. Most patients (81%) expressed satisfaction with PAI.

CONCLUSIONS

Personal Activity Intelligence is feasible, acceptable, and effective when used with patients in a clinic setting.

Temporal changes in personal activity intelligence and the risk of incident dementia and dementia related mortality: A prospective cohort study (HUNT)

BACKGROUND

The Personal Activity Intelligence (PAI) translates heart rate during daily activity into a weekly score. Obtaining a weekly PAI score ≥100 is associated with reduced risk of premature morbidity and mortality from cardiovascular diseases. Here, we determined whether changes in PAI score are associated with changes in risk of incident dementia and dementia-related mortality.

METHODS

We conducted a prospective cohort study of 29,826 healthy individuals. Using data from the Trøndelag Health-Study (HUNT), PAI was estimated 10 years apart (HUNT1 1984-86 and HUNT2 1995-97). Adjusted hazard-ratios (aHR) and 95%-confidence intervals (CI) for incidence of and death from dementia were related to changes in PAI using Cox regression analyses.

FINDINGS

During a median follow-up time of 24.5 years (interquartile range [IQR]: 24.1-25.0) for dementia incidence and 23.6 years (IQR: 20.8-24.2) for dementia-related mortality, there were 1998 incident cases and 1033 dementia-related deaths. Individuals who increased their PAI score over time or maintained a high PAI score at both assessments had reduced risk of dementia incidence and dementia-related mortality. Compared with persistently inactive individuals (0 weekly PAI) at both time points, the aHRs for those with a PAI score ≥100 at both occasions were 0.75 (95% CI: 0.58-0.97) for incident dementia, and 0.62 (95% CI: 0.43-0.91) for dementia-related mortality. Using PAI score <100 at both assessments as the reference cohort, those who increased from <100 at HUNT1 to ≥100 at HUNT2 had aHR of 0.83 (95% CI: 0.72-0.96) for incident dementia, and gained 2.8 (95% CI: 1.3-4.2, P<0.0001) dementia-free years. For dementia-related mortality, the corresponding aHR was 0.74 (95% CI: 0.59-0.92) and years of life gained were 2.4 (95% CI: 1.0-3.8, P=0.001).

INTERPRETATION

Maintaining a high weekly PAI score and increases in PAI scores over time were associated with a reduced risk of incident dementia and dementia-related mortality. Our findings extend the scientific evidence regarding the protective role of PA for dementia prevention, and suggest that PAI may be a valuable tool in guiding research-based PA recommendations.

FUNDING

The Norwegian Research Council, the Liaison Committee between the Central Norway Regional Health Authority and Norwegian University of Science and Technology (NTNU), Trondheim, Norway.

Personal Activity Intelligence e-Health Program in People with Type 2 Diabetes: A Pilot Randomized Controlled Trial

INTRODUCTION

Innovative strategies are needed to enable people with type 2 diabetes (T2D) to self-manage physical activity (PA). Personal Activity Intelligence (PAI) is a new metric that uses the heart rate response to PA to inform the user as to whether they are doing enough PA to reduce the risk of premature mortality. The PAI score reflects PA over the previous 7 d with the goal to maintain a score ≥100. The aim of this study was to investigate the feasibility, acceptability, and efficacy of the PAI e-Health Program in people with T2D.

METHODS

Thirty participants with T2D who were not meeting PA guidelines were randomly assigned to 12 wk of either 1) PAI e-Health Program or 2) PA attention control. The PAI e-Health Program consisted of receiving a wrist-worn heart rate monitor and an app with the PAI metric, and attending 4 × 2 h·wk-1 sessions of exercise and counseling. Feasibility and acceptability of the program were evaluated by achievement of a PAI score ≥100 and participant feedback. Efficacy was determined from changes in glycemic control, cardiorespiratory fitness, exercise capacity (time-on-test), body composition, sleep time, and health-related quality of life.

RESULTS

Program participants in the PAI e-Health Program had a mean ± SD PAI score of 119.7 ± 60.6 and achieved ≥100 PAI on 56.4% of the days. The majority of participants (80%) intended to continue to use PAI monitoring. Compared with control, the PAI group significantly improved their exercise capacity (mean difference, 95% confidence interval) (63 s, 17.9-108.0 s), sleep time (67.2 min, 7.2-127.1 min), total percent body fat (-1.3%, -2.6% to -0.1%), and gynoid fat percent (-1.5%, -2.6 to -0.5).

CONCLUSIONS

The PAI e-Health Program is feasible, acceptable, and efficacious in people with T2D.