Effectiveness of a Cardiovascular Management System on Triple Risk Factor Control in High-Risk Older Adults: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality in China. Although the National Basic Public Health Services Program provides annual health checkups for older adults, postscreening management of CVD risk factors such as hypertension, dyslipidemia, and diabetes is often inadequate. The CardioCare system is a digital cardiovascular management platform that integrates risk prediction, personalized health interventions, and continuous engagement to address these gaps. Objective: This trial aims to evaluate the effectiveness of the CardioCare system in improving triple risk factor control (simultaneous control of blood pressure, lipids, and glycemia) at 12 months among high-risk adults. Secondary objectives include assessing changes in estimated 10-year CVD risk, individual clinical parameters, medication adherence, lifestyle modification, system engagement, usability, satisfaction, and cost-effectiveness. Methods: This is a single-center, parallel-group, superiority randomized controlled trial with a 1:1 allocation ratio. A total of 300 adults aged ≥50 years with an estimated 10-year CVD risk of >10% and no previous CVD diagnosis will be recruited from the Health Management Center of the First Affiliated Hospital of Sun Yat-sen University in Guangzhou, China. Participants will be randomized to receive either the CardioCare system intervention or minimal usual care for 12 months. The intervention includes risk stratification and communication, weekly personalized SMS text messages or WeChat messages, and cardiologist oversight. The primary outcome is the proportion of participants achieving triple risk factor control at 12 months. Secondary outcomes include clinical, behavioral, usability, and economic measures. Analyses will follow the intention-to-treat principle, with multiple imputation for missing data. Results: This trial was funded on October 28, 2024. Recruitment is scheduled to begin in January 2026 and conclude in April 2026, with follow-up completed by June 2027. Data analysis will commence in mid-2027, and the main findings are expected to be published by the end of 2027. As of manuscript submission, recruitment has not yet started. Conclusions: This trial will provide robust evidence on the clinical effectiveness and cost-effectiveness of the CardioCare system in managing multiple cardiovascular risk factors among high-risk adults. The findings will inform the potential for scaling this intervention within health checkup centers and integrating it into national chronic disease management strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.062 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".