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Currently submitted to: Journal of Medical Internet Research

Date Submitted: Jun 1, 2026
Open Peer Review Period: Jun 2, 2026 - Jul 28, 2026
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Comparing Digital Health Interventions for Risk Factor Control in Secondary Stroke and TIA Prevention: A Systematic Review and Network Meta-analysis

  • Di Zhang; 
  • Ya-ting Yang; 
  • Zhi-pei Yang; 
  • Xia Lu; 
  • Xin-yu He; 
  • Lu Wang; 
  • De-hua Li

ABSTRACT

Background:

Background:

Patients who experience a stroke or transient ischemic attack (TIA) face a substantial risk of future events, making optimal management of risk factors essential for secondary prevention. Digital health interventions have demonstrated promise in enhancing the control of vascular risk factors among individuals with stroke or TIA; however, the relative efficacy of different intervention modalities in achieving risk factor control remains uncertain.

Objective:

Objective:

This study systematically assessed and compared the impact of various digital health interventions on the control of risk factors for secondary prevention among patients with stroke or TIA, aiming to determine the most effective intervention approach.

Methods:

Methods:

A comprehensive and systematic literature search was performed across PubMed, Cochrane Library, Embase, and Web of Science databases from January 2010 to January 2026. This review included randomized controlled trials (RCTs) evaluating distinct digital health modalities among patients who experienced a stroke or TIA. Systolic blood pressure (SBP) changes served as the primary outcome, whereas alterations in diastolic blood pressure (DBP), patient medication adherence, total cholesterol (TC), and low density lipoprotein cholesterol (LDL-C) constituted the secondary outcomes. Utilizing the RoB 2 tool, two independent reviewers evaluated the risk of bias, followed by a Bayesian random-effects network meta-analysis to synthesize both direct and indirect evidence. We ranked the interventions based on their cumulative ranking curve (SUCRA) values and appraised the certainty of evidence through the GRADE approach. Crucially, the study protocol was registered prospectively in the PROSPERO database (CRD420261367782).

Results:

Results:

A total of 25 RCTs involving 10,752 patients and six types of electronic health technologies were included. The results showed that, compared with usual care, combined digital technologies had a more pronounced benefit in reducing SBP (MD: −3.7, 95% CrI: −4.8 to −2.7; SUCRA: 71.95%); telephone follow-up demonstrated better effects on lowering DBP and LDL-C (MD: −2.4, 95% CrI: −3.7 to −1.2; SUCRA: 97.04%), (MD = −0.21, 95% CrI: −0.28 to −0.14; SUCRA = 55.95%). In addition, smartphone applications also showed certain advantages in improving medication adherence and reducing TC (MD = −0.39, 95% CrI: −0.71 to −0.068; SUCRA = 87.93%).

Conclusions:

Conclusions:

Different digital health interventions may provide distinct benefits for secondary prevention after stroke or transient ischemic attack. Combined digital technologies appeared to be more effective for reducing SBP, telephone follow-up for improving DBP and LDL-C, and smartphone applications for enhancing medication adherence and reducing TC. However, due to the limited evidence base and small study sample size, these outcomes should be treated conservatively. Future large-scale, high-quality trials are required to verify these determinations. Clinical Trial: The study protocol was registered prospectively in the PROSPERO database (CRD420261367782).


 Citation

Please cite as:

Zhang D, Yang Yt, Yang Zp, Lu X, He Xy, Wang L, Li Dh

Comparing Digital Health Interventions for Risk Factor Control in Secondary Stroke and TIA Prevention: A Systematic Review and Network Meta-analysis

JMIR Preprints. 01/06/2026:103256

DOI: 10.2196/preprints.103256

URL: https://preprints.jmir.org/preprint/103256

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