Effectiveness of Digital Interventions in Stroke Management: An Umbrella Review of Systematic Reviews

Huan X. Nguyen, Lutfan Lazuardi, Annisa Ristya Rahmanti, Mai Duy Ton, Minh Cong Tran, Farida Niken Astari Nugroho Hati, Hanifah Wulandari, Ichlasul Amalia, Dimas S.E.W. Sumunar, Rizaldy Taslim Pinzon

Citation

Huan X. Nguyen, Lutfan Lazuardi, Annisa Ristya Rahmanti, Mai Duy Ton, Minh Cong Tran, Farida Niken Astari Nugroho Hati, Hanifah Wulandari, Ichlasul Amalia, Dimas S.E.W. Sumunar, Rizaldy Taslim Pinzon. Effectiveness of Digital Interventions in Stroke Management: An Umbrella Review of Systematic Reviews. PROSPERO 2024 CRD42024583993 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024583993

Review question [1 change]

Review Questions:

– To summarize the evidence from systematic reviews on the effectiveness of digital interventions in stroke management.

– To identify the types of digital interventions that have been effective in stroke management.

– To identify gaps in the evidence base regarding digital interventions and stroke management.

The review will address the following specific questions:

Types of Digital Interventions:

– What types of digital interventions have been implemented for stroke management, and how are they categorized?

Methodological Frameworks:

– What are the methodological frameworks used to develop and implement these digital interventions for stroke management?

Adherence and Non-Adherence:

– What factors are associated with participants’ adherence to or non-adherence to these digital interventions?

Effects and Effectiveness:

– What are the effects and effectiveness of these digital interventions on various outcomes, including functional recovery, quality of life, cost-effectiveness, patient satisfaction, and healthcare utilization?

Searches

Sources:

PubMed, Cochrane Library, Embase, CINAHL, PsycINFO, Scopus, Web of Science, and Health Technology Assessment Database (HTA Database)

Manual search of reference lists of included reviews (if needed)

Search dates: The searches will be conducted from August to September, 2024

Publication date: All relevant publications available up to the end of the data extraction period will be included

Restriction: Only studies published in English will be included.

Search Update: The search strategy will be re-run prior to publication to ensure that the most recent studies are included in the review.

Types of study to be included

The study design that we are including is the peer-reviewed systematic reviews (SR) and systematic reviews with meta-analysis (SRMA) or a review following PRISMA guidelines.

Condition or domain being studied

This review focuses on systematic reviews and meta-analyses that evaluate digital interventions aimed at stroke management. The review will consider digital interventions across several key domains, including:

– Self-Management: Interventions designed to empower patients to manage their condition independently, such as mobile health apps, telemedicine, and online education platforms.

– Clinical Management: Interventions that support healthcare providers in diagnosing, treating, and monitoring stroke patients, such as predictive analytics, AI-driven imaging analysis, and remote monitoring tools.

– Rehabilitation: Interventions aimed at aiding recovery and improving functional outcomes post-stroke, including virtual reality therapy, AI-powered rehabilitation programs, and wearable technology.

– Preventive Management: Interventions focused on preventing stroke recurrence and managing risk factors, such as digital health coaching, lifestyle management apps, and continuous monitoring of health parameters.

Participants/population

Systematic reviews and meta-analyses that evaluate digital interventions aimed at stroke management.

Inclusion

– Adults (18 years and older) who have experienced a stroke.

– Patients with stroke, as defined by the American Heart Association (Sacco et al., 2013, Stroke), excluding transient ischemic attack (TIA).

– Any pathological type of stroke, including ischemic, venous, and intracerebral hemorrhage.

– Strokes of any cause, including but not limited to large vessel, thromboembolic, small vessel disease, etc.

– Any time since the stroke event will be considered.

Exclusion

– Studies focusing on subarachnoid hemorrhage, as the management pathways differ significantly from other types of stroke.

– Case reports, observational studies, qualitative studies, and studies without relevant data.

– Non-peer-reviewed articles, conference abstracts, and editorial pieces.

Intervention(s), exposure(s)

Any digital interventions (e.g., telemedicine, internet, mobile apps, wearable technology, virtual reality, AI, machine learning, digital twins) used in stroke management.

Comparator(s)/control

Comparators may include standard care, non-digital interventions, or alternative digital interventions.

Context

The review will include studies conducted in various settings such as:

– Clinical Settings: Including hospitals (inpatients and outpatients), rehabilitation centers, and specialist stroke clinics.

– Primary Care: Studies based in primary care settings, where ongoing stroke management and prevention are coordinated by general practitioners and primary care teams.

– Community-Based Settings: Research focused on community health programs and services, which aim to improve access to stroke management and support recovery within the community.

– Self-Management: Studies that involve patients using digital interventions independently at home, such as mobile apps, telemedicine platforms, and remote monitoring tools.

The review is conducted in any geographical location, including high-income, middle-income, and low-income countries.

Main outcome(s)

Primary outcomes include functional recovery, quality of life, and adherence to treatment.

Measures of effect

The measures of effect depend on whether or not we come across any meta-analysis in our included studies. For the primary outcomes in the umbrella review:

Functional Recovery:

Measure of Effect: Summarized odds ratios (OR), relative risks (RR), or other effect sizes reported in the included meta-analyses and systematic reviews.

Quality of Life:

Measure of Effect: Reported effect sizes, such as mean differences (MD) or standardized mean differences (SMD), as provided by the included reviews. Where available, pre- and post-intervention changes or control and intervention groups will be described based on the data reported in the systematic reviews.

Adherence to Treatment:

Measure of Effect: Reported as summarized proportions, relative risks (RR), or odds ratios (OR) comparing adherence rates, as presented in the systematic reviews and meta-analyses.

Additional outcome(s)

Secondary outcomes include cost-effectiveness, patient satisfaction, and healthcare utilization.

Data extraction (selection and coding) [1 change]

Study selection

– Two independent reviewers will apply the eligibility criteria and select studies for inclusion in the systematic review. Both reviewers will independently screen titles and abstracts for initial inclusion.

– Any disagreements between the reviewers regarding study inclusion will be resolved through discussion. If consensus cannot be reached, a third reviewer will be consulted to make the final decision.

– The initial screening of studies will be conducted using EndNote for reference management along with manual rechecking of the articles retrieved.

Data extraction

– Data will be extracted by two reviewers independently, with a third reviewer checking the extracted data for accuracy and consistency. This third reviewer will also resolve any discrepancies that arise between the first two reviewers.

– Extracted data will be conducted using EPPI reviewer tool and recorded in an Excel spreadsheet.

– Data extracted from the included studies will include:

Study characteristics: Corresponding author(s), year, country, and funding.

Study Design and Methodology: Type of study, setting, duration, and any relevant methodological details.

Participant Characteristics: Age, gender, stroke type, and other relevant clinical characteristics.

Intervention Details: Type of digital intervention, duration, and frequency of use.

Outcomes: Data on primary and secondary outcomes, including functional recovery, quality of life, adherence to treatment, cost-effectiveness, patient satisfaction, and healthcare utilization.

Measures of Effect: Reported effect sizes (e.g., odds ratios, mean differences), confidence intervals, and statistical significance if available.

Additional Information: Any reported data on adherence, implementation fidelity, and participant feedback.

Risk of bias (quality) assessment

– The methodological quality and risk of bias of the included systematic reviews and meta-analyses will be assessed using A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2), which is a comprehensive tool designed to evaluate the quality of systematic reviews.

– Two independent reviewers will conduct the risk of bias assessment using the AMSTAR-2 tool. Any disagreements between the two reviewers regarding the risk of bias assessments will be resolved through discussion. If a consensus cannot be reached, a third reviewer will be consulted to provide a final decision.

Strategy for data synthesis [1 change]

Strategy for Data Synthesis:

– The selected articles will be manually reviewed, and relevant information will be extracted, synthesized, and summarized in a tabular format.

– A narrative synthesis will be conducted to provide a comprehensive overview of the findings from the included reviews. The results will be presented in both tables and figures, emphasizing the effectiveness of various types of digital interventions on stroke management outcomes, including functional recovery, quality of life, adherence to treatment, and patient engagement.

– Additionally, the narrative synthesis will highlight key themes, methodological frameworks, and factors influencing participant adherence and non-adherence to these interventions.

Evidence Gap Map

An evidence gap map will be created to visually represent the availability and strength of evidence across different types of digital interventions and outcomes. This will highlight areas with robust evidence as well as gaps where further research is needed.

Components to Include:

– Types of Digital Interventions and Outcome Categories:

The map will categorize digital interventions (e.g., telemedicine, mobile health apps, wearable technology, virtual reality, AI, digital twins) and align them with primary and secondary outcomes such as functional recovery, quality of life, adherence to treatment, cost-effectiveness, patient satisfaction, and healthcare utilization.

– Quality and Strength of Evidence:

The map will reflect the quality and strength of the evidence, differentiating between high, moderate, and low-quality studies, based on the methodological rigor and consistency of findings reported in the included systematic reviews.

– Context and Setting:

The evidence will be categorized based on the context and setting in which the digital interventions were studied, including clinical settings (e.g., hospitals, rehabilitation centers), primary care, community-based settings, and home-based self-management.

– Geographical Distribution:

The map will identify the geographical distribution of studies, highlighting regions (e.g., high-income, middle-income, low-income countries) where evidence is concentrated or lacking.

– Time Since Stroke:

The evidence will be organized by the timing of interventions relative to the stroke event (e.g., acute phase, subacute phase, chronic phase), to determine which phases of stroke care are well-researched and where gaps remain.

Analysis of subgroups or subsets [1 change]

There is no sub-set analysis planned

Contact details for further information

Annisa Ristya Rahmanti

annisaristya@ugm.ac.id

Organisational affiliation of the review

Universitas Gadjah Mada | Middlesex University London

https://hpm.fk.ugm.ac.id/ | https://cs.mdx.ac.uk/

Review team members and their organisational affiliations

Professor Huan X. Nguyen. Middlesex University London
Dr Lutfan Lazuardi. Universitas Gadjah Mada
Dr Annisa Ristya Rahmanti. Universitas Gadjah Mada
Dr Mai Duy Ton. VNU University of Medicine and Pharmacy
Dr Minh Cong Tran. Nuffield Department of Clinical Neuroscience, University of Oxford
Dr Farida Niken Astari Nugroho Hati. UGM Academic Hospital, Universitas Gadjah Mada
Miss Hanifah Wulandari. Universitas Gadjah Mada
Miss Ichlasul Amalia. Universitas Gadjah Mada
Mr Dimas S.E.W. Sumunar. Universitas Gadjah Mada
Dr Rizaldy Taslim Pinzon. Neurology Department, Bethesda Hospital

Type and method of review

Review of reviews, Systematic review

Anticipated or actual start date

28 August 2024

Anticipated completion date

31 December 2024

Funding sources/sponsors

Funded by the Academy of Medical Sciences, 2024-2025

Grant number(s)
State the funder, grant or award number and the date of award

Project Number NGR1\1961

Conflicts of interest

Language

English

Country

England, Indonesia, Vietnam

Stage of review

Review Ongoing

Subject index terms status

Subject indexing assigned by CRD

Subject index terms

MeSH headings have not been applied to this record

Date of registration in PROSPERO

10 September 2024

Date of first submission

27 August 2024

Stage of review at time of this submission

Stage	Started	Completed
Preliminary searches	Yes	No
Piloting of the study selection process	Yes	No
Formal screening of search results against eligibility criteria	No	No
Data extraction	No	No
Risk of bias (quality) assessment	No	No
Data analysis	No	No

The record owner confirms that the information they have supplied for this submission is accurate and complete and they understand that deliberate provision of inaccurate information or omission of data may be construed as scientific misconduct.

The record owner confirms that they will update the status of the review when it is completed and will add publication details in due course.

Versions

10 September 2024

Source:

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=583993