Effectiveness of Telemedicine for Reducing Cardiovascular Risk: A Systematic Review and Meta-Analysis

Cardiovascular diseases remain the most common cause of death in Europe, with substantial premature mortality under age 70. Public health policies emphasize primary prevention by identifying high-risk individuals and intervening on modifiable cardiovascular risk factors (CVRFs), including smoking, obesity, sedentary lifestyle, diabetes, hypertension, and hypercholesterolemia. Unlike fixed risk markers (age, sex, genetics), these factors can be modified through lifestyle and medical interventions. Telemedicine—via teleconsultation, tele-education, telemonitoring, or related modalities—offers a means to reach at-risk populations despite economic or geographic barriers and can support multidisciplinary strategies for risk reduction. However, uncertainty remains regarding the effectiveness of telemedicine-based interventions for mitigating chronic disease risk. The research question of this study was to determine whether telemedicine and e-health interventions are effective in reducing cardiovascular risk by improving key modifiable CVRFs (glycemic control, blood pressure, body weight, and physical activity).

Clinical practice guidelines recommend comprehensive, multidisciplinary interventions targeting multiple CVRFs and adapting to new technologies. Prior work indicates telemedicine can improve access and adherence, but studies show inconsistent effects due to heterogeneous intervention designs. Previous reviews have documented benefits of e-health/m-health on blood pressure control and metabolic parameters in some contexts, yet evidence remains mixed. This review synthesizes randomized controlled trials from 2017–2022 to clarify telemedicine’s effectiveness across major CVRFs.

Design: Systematic review and meta-analysis following PRISMA 2020 guidelines; protocol registered in PROSPERO (CRD42022365395). Information sources: PubMed, Scopus, CINAHL, and Web of Science searched between September and October 2022. Search strategy: ((Telemedicine OR Remote Consultation) AND (Heart Disease Risk Factors OR hypertension OR obesity OR overweight OR cholesterol OR Hypercholesterolemia OR diabetes mellitus OR smoking OR exercise OR sedentary behavior) AND (middle aged)). Inclusion criteria: (1) telemedicine/e-health interventions; (2) randomized clinical trials; (3) published 2017–2022; (4) general population (excluding ethnic minorities and populations with non-relevant health problems) and targeting CVRFs (diabetes, hypertension, obesity/overweight, hypercholesterolemia, tobacco use, exercise/sedentary lifestyle). Study selection: Duplicates removed using Rayyan; titles/abstracts screened; full texts assessed by two independent reviewers with a third resolving disagreements. Data extraction: Authors, year, country, population characteristics, intervention and control details, telemedicine type, follow-up duration (e.g., 3, 6, 12 months), and outcomes (HbA1c, blood pressure, body weight, and weekly minutes of moderate/vigorous physical activity). Quality assessment: PEDro scale (11 items; item 1 external validity not included in score); categories: Poor (0–3), Fair (4–5), Good (6–8), Excellent (>9). Meta-analysis: Random-effects model using mean and standard deviation of changes over time; if SD unavailable, 95% CI used. Results presented as forest plots with Hedge’s g and 95% CI, and p-values. Publication bias assessed by funnel plots with sensitivity analyses excluding low-quality studies.

- Study selection and characteristics: Of 763 records, 415 screened after deduplication and automation filters; 178 assessed for eligibility; 28 RCTs included. Countries included the US, Australia, UK, Canada, Spain, Malaysia, Belgium, Iran, South Korea, Germany, Turkey, France, China, and Taiwan. Total participants: 5,460 adults (18–75 years). Conditions: diabetes (n=13), hypertension (n=6), overweight/obesity (n=7), sedentary lifestyle (n=2). Intervention duration: 1 month to 2 years. - Methodological quality (PEDro): Most studies rated Good; 3 Excellent [20,24,37]; 1 Poor [41]; 1 Fair [45]. - Diabetes (HbA1c): Ten studies included in meta-analysis. Significant small mean effect size: g = −0.432 (95% CI: −0.522 to −0.341; p < 0.001). Subgroup excluding studies without participant blinding: moderate effect g = −0.538 (95% CI: −0.987 to −0.089; p = 0.019). Individual trials reported HbA1c reductions up to −0.51% (95% CI: −0.73 to −0.30; p < 0.001) and progressive reductions up to −0.87% at 12 months in some designs. - Hypertension (blood pressure): Significant moderate effect on systolic BP: g = −0.775 (95% CI: −0.887 to −0.663; p < 0.001) and small effect on diastolic BP: g = −0.447 (95% CI: −0.572 to −0.321; p < 0.001). Subgroup excluding non-blinded studies: systolic BP g = −0.733 (95% CI: −1.252 to −0.213; p = 0.006). Individual trials observed systolic reductions around −8.9 to −10.1 mmHg and diastolic reductions around −7.0 mmHg in some interventions. - Overweight/obesity (body weight): Significant moderate mean effect size: g = −0.628 (95% CI: −0.739 to −0.517; p < 0.001). Subgroup analyses: excluding non-blinded studies g = −0.728 (95% CI: −1.196 to −0.261; p = 0.002); excluding inadequate follow-up g = −0.957 (95% CI: −1.512 to −0.401; p = 0.001). Several trials showed short-term (3-month) significant weight loss (e.g., −1.79 to −7.30 kg) with some persistence at 12 months in select studies. - Sedentarism (physical activity): Two studies; neither showed statistically significant changes; meta-analysis not feasible due to outcome reporting. - Publication bias: Funnel plots suggested expected bias due to some lower-quality studies. Excluding low-quality studies yielded more symmetrical distributions. - Overall: Telemedicine showed beneficial effects across glycemic control, blood pressure, and body weight, with effect sizes ranging from small to moderate, and no consistent effect on sedentary behavior due to limited data.

The review addressed whether telemedicine can reduce cardiovascular risk by improving modifiable risk factors. Findings indicate telemedicine interventions yield small to moderate improvements in HbA1c, systolic and diastolic blood pressure, and body weight, aligning with mechanisms such as enhanced adherence to treatment, self-monitoring, and ongoing support. Even modest reductions (e.g., 2 mmHg systolic or 1 mmHg diastolic) are associated with meaningful reductions in vascular mortality risk, underscoring clinical relevance. The results support telemedicine as a complementary strategy within primary care to reach at-risk populations, improve chronic disease management, reduce costs, and increase access, particularly where geographic or resource barriers exist. Heterogeneity in intervention design likely contributes to variable effects across studies; nonetheless, subgroup analyses suggest that higher methodological rigor (e.g., blinding, adequate follow-up) is associated with larger effect sizes. While diabetes trials generally showed small HbA1c improvements, sustained reductions may translate into lower cardiovascular risk over time. Weight-loss and blood pressure benefits further support telemedicine’s role in comprehensive risk reduction programs.

Telemedicine-based interventions are clinically relevant for managing cardiovascular risk factors, demonstrating improvements in long-term risk factor control and body composition by enhancing adherence and enabling continuous communication with healthcare professionals irrespective of geography. Implementation should prioritize interventions validated in clinical trials, ensuring appropriate infrastructure. Telemedicine can expand access, especially in low-income or resource-limited settings, and should be integrated into routine care as part of multidisciplinary strategies to reduce cardiovascular risk. Future research should standardize intervention protocols, optimize engagement for sustained effects, and expand high-quality RCTs targeting physical activity and lipid management to clarify telemedicine’s impact across all CVRFs.

- High heterogeneity in telemedicine intervention designs (modalities, intensity, components, follow-up) limits replicability and comparability. - Potential publication bias, as only published articles were included; intervention protocols and unpublished null results may be underrepresented. - Limited and heterogeneous reporting for physical activity outcomes precluded meta-analysis for sedentarism. - Some included studies had lower methodological quality (e.g., lack of blinding, inadequate follow-up), which may influence effect estimates; however, sensitivity analyses generally supported robustness when lower-quality studies were excluded.