Evidence map›Paper›PMID 34906924›Full record

Trial reportJMIR mHealth and uHealth2022

Effects on Adherence to a Mobile App-Based Self-management Digital Therapeutics Among Patients With Coronary Heart Disease: Pilot Randomized Controlled Trial.

Yuxi Li, Yanjun Gong, Bo Zheng, Fangfang Fan, Tieci Yi, Yimei Zheng, Pengkang He, Jin Fang, Jia Jia, Qin Zhu and 2 more

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03565978 (Evaluation of a Cardiac Care Solution for Post-Hospital Management in Primary and Secondary Care of Patients Diagnosed With Coronary Artery Disease), which is not on this map. Cited by 45 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 8 pooled it
8.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT03565978 nacompletednot on this map

Evaluation of a Cardiac Care Solution for Post-Hospital Management in Primary and Secondary Care of Patients Diagnosed With Coronary Artery Disease

TypeinterventionalSponsorPeking University First HospitalRan2016 to 2018Enrolled300ConditionsST Segment Elevation Myocardial Infarction, Non-ST Segment Elevation Myocardial Infarction, Unstable AnginaArmsBAMA solution
3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 8 syntheses or guidelines pooled it, 52 citations in OpenAlex.

  1. Smartphone application-based interventions for cardiometabolic risk factor management: A systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
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  6. Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Yuxi LiDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0003-1556-598X
Yanjun GongDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0003-1281-1073
Bo ZhengDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0003-4562-3183
Fangfang FanDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0001-8351-4821
Tieci YiDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0001-9080-7745
Yimei ZhengDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-2497-2758
Pengkang HeDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0003-2680-8457
Jin FangDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-7115-4862
Jia JiaDepartment of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0003-1609-4227
Qin ZhuStragety & New Business Development of Philips Greater China, Shanghai, China.ORCID 0000-0003-1765-4636
Jie Jiang *Department of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-4077-0056
Yong Huo *Department of Cardiology, Peking University First Hospital, Beijing, China.ORCID 0000-0002-5407-8773
Peking University · CNPhilips (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe adherence to secondary prevention treatment in patients with coronary heart disease (CHD) is low. Digital therapeutics (DTx) refers to an emerging branch of medicine that delivers medical interventions directly to patients using evidence-based, clinically evaluated, technology-based software algorithms or apps to facilitate disease management, which may be an efficient tool to optimize adherence.

objectiveThis paper aims to investigate the effect of mobile app-based self-management DTx on long-term use of secondary prevention medications in patients with CHD in China.

methodsThis pilot study was a parallel-designed, open-labeled, single-center, randomized controlled trial. Hospitalized patients with CHD admitted to Peking University First Hospital between April 2016 and June 2017 were randomized before discharge on a 1:1 ratio. The intervention group received regular follow-up combined with DTx, which is a self-management mobile app already installed on an Android 5 (Mi Pad 1, Xiaomi Corporation) tablet. Structured data from the hospital informatics system were integrated automatically, and medication, lifestyle intervention plan, follow-up protocol, and patient education materials were also provided according to the diagnosis. Participants could use DTx for self-management at home. The control group was under conventional hospital-based follow-up care. Patients were followed up for 1 year, and the primary end point was the percentage of all guideline-recommended medications at 12 months. The secondary end points included the percentage adhered to standard secondary prevention medications at 6 months, the control rate of lipid profile, and blood pressure at 6 months and 1 year.

resultsAmong 300 randomized patients with CHD, 290 (96.7%) were included in the final analysis, including 49.3% (143/290) and 50.7% (147/290) of patients from the intervention and control groups, respectively. Baseline characteristics were similar between the 2 groups. There was a statistically significant improvement in the percentage of all guideline-recommended medications at 12 months in the intervention group compared with the control group (relative risk [RR] 1.34, 95% CI 1.12-1.61; P=.001), and there was no interaction with baseline characteristics. The intervention group had a significantly higher proportion of patients achieving blood pressure under control (systolic blood pressure <140 mm Hg and diastolic blood pressure <90 mm Hg) and low-density lipoprotein cholesterol <1.8 mmol/L (RR 1.45, 95% CI 1.22-1.72; P<.001 and RR 1.40, 95% CI 1.11-1.75; P=.004, respectively) at 12 months. Furthermore, on logistic regression, the intervention group had a lower risk of withdrawing from guideline-recommended medications (odds ratio 0.46, 95% CI 0.27-0.78; P=.004).

conclusionsAmong patients with CHD, using a mobile app-based self-management DTx in addition to traditional care resulted in a significant improvement in guideline-recommended medication adherence at 12 months. The results of the trial will be applicable to primary care centers, especially in rural areas with less medical resources.

trial registrationClinicalTrials.gov NCT03565978; https://clinicaltrials.gov/ct2/show/NCT03565978.

Indexed as

Coronary DiseaseMobile ApplicationsSelf-ManagementHumansMedication AdherencePilot Projectsadherencecoronary heart diseasedigital therapeuticsmobile appmobile phonesecondary preventionself-management

Identifiers

PMID34906924
PMCPMC8889473
OpenAlexW4200597057

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.