Trial reportBMJ (Clinical research ed.)2024
Learning implementation of a guideline based decision support system to improve hypertension treatment in primary care in China: pragmatic cluster randomised controlled trial.
Trial report in BMJ (Clinical research ed.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 18 papers.
What it found
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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.
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.
Learning Implementation of Guideline-based Decision Support System for Hypertension Treatment (LIGHT): A Staged Cluster Randomized Trial
Secondary Prevention of Ischemic Stroke and Transient Ischemic Attack With an Intelligent System
Who cites it
18 citing papers in PubMed.
- Preliminary Application of Antihypertensive Gene Detection in the Treatment of Hypertension.Medical science monitor : international medical journal of experimental and clinical research · 2026Trial
- Clinical Decision Support System, Antihypertensive Treatment Intensification, and Blood Pressure Control: A Post Hoc Secondary Analysis of a Cluster Randomized Trial.JAMA network open · 2026Trial
- Pharmacogenomics-guided personalized therapy for hypertension: a multicenter randomized trial.Journal of hypertension · 2026Trial
- Review
- Acceptability of Hypertension Quality Indicators in Primary Care in South Africa: Exploratory Implementation Research.Healthcare (Basel, Switzerland) · 2026Article
- Cardiovascular-Kidney-Metabolic Syndrome: Development of anJMIR diabetes · 2026Article
- Cardiovascular disease prevention in China: challenges and opportunities in the artificial intelligence-enabled digital health era.Nature reviews. Cardiology · 2026Review
- The effects of multitype prompt engineering for large language models in hypertension treatment decisions.NPJ digital medicine · 2026Article
- Precision cardiovascular medicine with big data and AI.NPJ digital medicine · 2026Review
- Article
- Retrospective comparison of ChatGPT-4 treatment recommendations with real-world physician management in newly diagnosed hypertension: a single-centre study.Frontiers in cardiovascular medicine · 2026Article
- Article
- Continuous care in hypertension management: Effects on blood pressure control, quality of life, and nursing satisfaction.Medicine · 2025Observational
- Assessing physicians' experiences with a clinical decision support system in patient blood management programme: a cross-sectional observational study.BMC health services research · 2025Observational
- Network meta analysis of contributions by different healthcare practitioners in digital self care for hypertension.NPJ digital medicine · 2025Review
- Integrated care for people with multimorbidity into elective surgical pathways: mixed-methods co-design study.The British journal of surgery · 2025Article
- The Lancet Commission on rethinking coronary artery disease: moving from ischaemia to atheroma.Lancet (London, England) · 2025Review
- Global trends in the burden of ischemic heart disease based on the global burden of disease study 2021: the role of metabolic risk factors.BMC public health · 2025Article
Corrections and comments
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Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the effectiveness of a clinical decision support system (CDSS) in improving the use of guideline accordant antihypertensive treatment in primary care settings in China.
designPragmatic, open label, cluster randomised trial.
setting94 primary care practices in four urban regions of China between August 2019 and July 2022: Luoyang (central China), Jining (east China), and Shenzhen (south China, including two regions).
participants94 practices were randomised (46 to CDSS, 48 to usual care). 12 137 participants with hypertension who used up to two classes of antihypertensives and had a systolic blood pressure <180 mm Hg and diastolic blood pressure <110 mm Hg were included.
interventionsPrimary care practices were randomised to use an electronic health record based CDSS, which recommended a specific guideline accordant regimen for initiation, titration, or switching of antihypertensive (the intervention), or to use the same electronic health record without CDSS and provide treatment as usual (control).
main outcome measuresThe primary outcome was the proportion of hypertension related visits during which an appropriate (guideline accordant) treatment was provided. Secondary outcomes were the average reduction in systolic blood pressure and proportion of participants with controlled blood pressure (<140/90 mm Hg) at the last scheduled follow-up. Safety outcomes were patient reported antihypertensive treatment related events, including syncope, injurious fall, symptomatic hypotension or systolic blood pressure <90 mm Hg, and bradycardia.
results5755 participants with 23 113 visits in the intervention group and 6382 participants with 27 868 visits in the control group were included. Mean age was 61 (standard deviation 13) years and 42.5% were women. During a median 11.6 months of follow-up, the proportion of visits at which appropriate treatment was given was higher in the intervention group than in the control group (77.8% (17 975/23 113)
conclusionsUse of a CDSS in primary care in China improved the provision of guideline accordant antihypertensive treatment and led to a modest reduction in blood pressure. The CDSS offers a promising approach to delivering better care for hypertension, both safely and efficiently.
trial registrationClinicalTrials.gov NCT03636334.
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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.