Voice-assisted artificial intelligence in cardiovascular disease management: a systematic review and meta-analysis protocol

Clinical Snapshot

Key Findings

• P Value: Not applicable - protocol paper

• Effect Size: Not applicable - protocol paper

• Primary Outcome: Cardiovascular-related mortality (planned outcome, no results available)

• Nnt Or Sensitivity: Not applicable - protocol paper

• Confidence Interval: Not applicable - protocol paper

Clinical Application

Implementation would depend on technology literacy, device availability, and integration with existing healthcare systems Relevant to Australian digital health initiatives and My Health Record integration; would need consideration of TGA regulations for medical device software and PBS funding for digital therapeutics Patients with established cardiovascular disease requiring self-management support, particularly those comfortable with voice technology

Abstract

INTRODUCTION: Cardiovascular disease (CVD) remains a leading cause of global morbidity and mortality, with self-management playing a pivotal role in improving outcomes. Voice-assisted artificial intelligence (AI) technologies such as virtual assistants and voice-controlled applications have emerged as innovative tools for healthcare delivery. While the technologies show promise in areas like primary prevention and chronic disease management, their effectiveness in supporting self-management for patients with CVD remains underexplored. This study aims to evaluate the impact of voice-assisted AI technologies on CVD self-management, specifically focusing on cardiovascular-related mortality, health-related quality of life (HRQoL) and adherence to lifestyle modifications. METHODS AND ANALYSIS: A systematic review and meta-analysis will be conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. A comprehensive search will be performed across databases such as MEDLINE, Scopus, Embase and Cochrane Central Register of Controlled Trials (CENTRAL), from 2010 to 2025. The review will include randomised controlled trials (RCTs), non-RCTs and observational studies that evaluate voice-assisted AI interventions (eg, voice-controlled fitness apps, smart health assistants) aimed at CVD self-management. The primary outcome will be cardiovascular-related mortality. Secondary outcomes will include HRQoL, clinical outcomes (eg, high blood pressure), lipid profiles (eg, cholesterol and glucose levels) and lifestyle modifications (eg, dietary habits and levels of physical activity). Data management and analysis will be conducted using Comprehensive Meta-Analysis software V.2.0. The methodological quality of the included studies will be assessed using the Cochrane Risk of Bias tool for RCTs and the Newcastle-Ottawa Scale for observational studies. The meta-analysis will use random-effects models, with heterogeneity assessed using Q and I² statistics. Subgroup analyses and meta-regression will be conducted to explore potential sources of heterogeneity. ETHICS AND DISSEMINATION: No formal ethical assessment is required, as this study involves analysis of publicly available secondary data. Findings will be disseminated through publications in peer-reviewed scientific journals, conference presentations and media coverage to inform healthcare providers, policymakers and patients. PROSPERO REGISTRATION NUMBER: CRD42024568702.

References

1. 1.Issaka, A., Maddison, R., Lamaro Haintz, G., & Shariful Islam, S. M. (2026). Voice-assisted artificial intelligence in cardiovascular disease management: a systematic review and meta-analysis protocol. BMJ Open. https://doi.org/10.1136/bmjopen-2025-102059