Effects of eHealth Interventions on Quality of Life and Psychological Outcomes in Cardiac Surgery Patients: Systematic Review and Meta-analysis

The Effects of mHealth Interventions on Quality of Life, Anxiety, and Depression in Patients With Coronary Heart Disease: Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Coronary heart disease (CHD) is the leading cause of death globally. In addition, 20% to 40% of the patients with CHD have comorbid mental health issues such as anxiety or depression, affecting the prognosis and quality of life (QoL). Mobile health (mHealth) interventions have been developed and are widely used; however, the evidence for the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD is currently ambiguous.

OBJECTIVE

In this study, we aimed to assess the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD.

METHODS

We searched the Cochrane Library, PubMed, Embase, CINAHL, Web of Science, China National Knowledge Infrastructure, and Wanfang databases from inception to August 12, 2023. Eligible studies were randomized controlled trials that involved patients with CHD who received mHealth interventions and that reported on QoL, anxiety, or depression outcomes. We used the Cochrane risk-of-bias tool for randomized trials to evaluate the risk of bias in the studies, ensuring a rigorous and methodologically sound analysis. Review Manager (desktop version 5.4; The Cochrane Collaboration) and Stata MP (version 17.0; StataCorp LLC) were used to conduct the meta-analysis. The effect size was calculated using the standardized mean difference (SMD) and its 95% CI.

RESULTS

The meta-analysis included 23 studies (5406 participants in total) and showed that mHealth interventions significantly improved QoL in patients with CHD (SMD 0.49, 95% CI 0.25-0.72; Z=4.07; P<.001) as well as relieved their anxiety (SMD -0.46, 95% CI -0.83 to -0.08; Z=2.38; P=.02) and depression (SMD -0.34, 95% CI -0.56 to -0.12; Z=3.00; P=.003) compared to usual care. The subgroup analyses indicated a significant effect favoring the mHealth intervention on reducing anxiety and depressive symptoms compared to usual care, especially when (1) the intervention duration was ≥6 months (P=.04 and P=.001), (2) the mHealth intervention was a simple one (only 1 mHealth intervention was used) (P=.01 and P<.001), (3) it was implemented during the COVID-19 pandemic (P=.04 and P=.01), (4) it was implemented in low- or middle-income countries (P=.01 and P=.02), (5) the intervention focused on mental health (P=.01 and P=.007), and (6) adherence rates were high (≥90%; P=.03 and P=.002). In addition, comparing mHealth interventions to usual care, there was an improvement in QoL when (1) the mHealth intervention was a simple one (P<.001), (2) it was implemented in low- or middle-income countries (P<.001), and (3) the intervention focused on mental health (P<.001).

CONCLUSIONS

On the basis of the existing evidence, mHealth interventions might be effective in improving QoL and reducing anxiety and depression in patients with CHD. However, large sample, high-quality, and rigorously designed randomized controlled trials are needed to provide further evidence.

TRIAL REGISTRATION

PROSPERO CRD42022383858; https://tinyurl.com/3ea2npxf.

Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis

BACKGROUND

Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of eHealth tools provides new prospects for the management of long-term anticoagulants. However, there is no comprehensive summary of the application of eHealth tools in anticoagulation management after CVR.

OBJECTIVE

Our objective is to clarify the current state, trends, benefits, and challenges of using eHealth tools in the anticoagulation management of patients after CVR and provide future directions and recommendations for development in this field.

METHODS

This scoping review follows the 5-step framework developed by Arksey and O'Malley. We searched 5 databases such as PubMed, MEDLINE, Web of Science, CINAHL, and Embase using keywords such as "eHealth," "anticoagulation," and "valve replacement." We included papers on the practical application of eHealth tools and excluded papers describing the underlying mechanisms for developing eHealth tools. The search time ranged from the database inception to March 1, 2023. The study findings were reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Additionally, VOSviewer (version 1.6.18) was used to construct visualization maps of countries, institutions, authors, and keywords to investigate the internal relations of included literature and to explore research hotspots and frontiers.

RESULTS

This study included 25 studies that fulfilled the criteria. There were 27,050 participants in total, with the sample size of the included studies ranging from 49 to 13,219. The eHealth tools mainly include computer-based support systems, electronic health records, telemedicine platforms, and mobile apps. Compared to traditional anticoagulation management, eHealth tools can improve time in therapeutic range and life satisfaction. However, there is no significant impact observed in terms of economic benefits and anticoagulation-related complications. Bibliometric analysis suggests the potential for increased collaboration and opportunities among countries and academic institutions. Italy had the widest cooperative relationships. Machine learning and artificial intelligence are the popular research directions in anticoagulation management.

CONCLUSIONS

eHealth tools exhibit promise for clinical applications in anticoagulation management after CVR, with the potential to enhance postoperative rehabilitation. Further high-quality research is needed to explore the economic benefits of eHealth tools in long-term anticoagulant therapy and the potential to reduce the occurrence of adverse events.

Effects of technology-assisted rehabilitation for patients with hip arthroplasty: A meta-analysis

BACKGROUND

To investigate the efficacy of technology-assisted rehabilitation compared to that of usual care programs after total hip arthroplasty (THA) through randomized controlled trials (RCTs).

METHODS

The Medline (PubMed), Cochrane Library, Embase and Web of Science databases were searched for RCTs regarding the efficacy of technology-assisted rehabilitation following THA. Data were analyzed using Stata 12.0 software.

RESULTS

Eleven RCTs involving 1327 patients were included in the meta-analysis. The pooled effect size showed that compared to usual care, telerehabilitation significantly improved the Harris score (standardized mean difference [SMD] 0.74, 95% confidence interval [CI] 0.58 to 0.90) and functional independence measure (FIM) score (SMD 1.26, 95% CI 0.48 to 2.03). In addition, video-based therapy could significantly improve walk test results (SMD 0.43, 95% CI 0.11 to 0.75).

CONCLUSION

The findings suggest that technology-assisted rehabilitation, especially telerehabilitation, have been shown to improve the physical function of patients following THA compared to conventional rehabilitation. More robust studies are needed to validate the long-term efficacy and safety of innovative technology-assisted training strategies.