An interventional study of web application with AI chat and usual clinic care follows the national prevention and management guidelines for major cardiovascular risk factors in AI Chatbot and Cardiovascular (CV) Risk, sponsored by Cairo University. Not yet recruiting. Open to participants aged 40 Years to 75 Years. Per ClinicalTrials.gov, last updated 2026-11-04.
Sponsored by Cairo University · Not applicable, Interventional, and Prevention
To determine the effect of a web-based application with an integrated AI chat module on 10-year cardiovascular risk score (intervention) versus usual clinic care (control) after 3 months from baseline score.
Cardiovascular diseases (CVDs), such as coronary heart disease, stroke, and peripheral vascular disease, are still among the primary causes of early mortality and long-term disability across the globe, with an estimated 17.9 million deaths and over 422 million affected individuals reported each year . The literature data showed that CVD risk factors are common in Arab countries' populations . In Egypt, coronary heart disease deaths account for 32.40% of total deaths, making Egypt the 15th highest country with coronary heart disease deaths in the world, according to the latest WHO data. Physical inactivity, consumption of high-fat foods, elevated blood pressure, tobacco use, diabetes, obesity, and lipid disorders are key contributors to the increased incidence of coronary heart disease.
Significant developments in internet and mobile technologies over the past decade offer promising opportunities to alleviate the burden of cardiovascular diseases and expand access to healthcare services.
Digital health interventions (DHIs) are technology-driven tools designed to enhance patient care and health outcomes in a safe and efficient manner. These may include smartphone apps or automated email programs. Studies by Whittaker and Wieland show that DHIs can help lower cardiovascular risk factors, supporting outcomes like smoking cessation and weight reduction and Widmer's meta-analysis found that DHIs reduced rehospitalization rates and improved cardiovascular risk score.
Natural language processing (NLP) and large language model (LLM) technologies hold significant potential for enhancing patients' access to medical knowledge. Advanced AI chatbots-such as ChatGPT-are examples of pre-trained LLMs that can engage in human-like conversations and generate coherent, contextually appropriate responses. A growing number of individuals are turning to AI chatbots instead of conventional search methods drawn by their capacity to provide personalized interactions and immediate, customized responses.
Digital interventions can improve risk factor control but evidence for AI-chat integrated web applications on predicted 10-year CV risk is limited. This RCT will compare a web application + AI chat intervention against usual clinic care on cardiovascular risk support, so that our research question is "Among adults with cardiovascular risk factors attending Kasr- Alainy family medicine clinics, does using a web application with AI chat support lead to a greater reduction in predicted 10-year cardiovascular risk compared to usual care?".
Cairo University is the lead sponsor of 4,929 studies on the registry; 1,450 are open to participants now.
Of its 37 completed or terminated interventional studies of FDA-regulated products, 5 (14%) have results posted.
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Exclusion Criteria:
The intervention group will receive the usual clinic care and will be offered to use the app with AI chat for 3 months after explaining the purpose of the study. -An informed written consent will be taken from each participant • Web app features: User account with secure login, baseline profile (age, sex, BP, lipids, smoking, diabetes, medications) Automated calculation of 10-year cardio vascular disease risk (ASCVDR) will be done using The American College of Cardiology (ACC)/American Heart Association (AHA) Risk Estimator of ASCVD \[12\]. * Educational modules (short, evidence-based content in Arabic) * Integrated AI chat An AI-powered chatbot is integrated into the web application to provide interactive health education and respond to user inquiries regarding cardiovascular risk, lifestyle modification, dietary advices and prevention strategies. The chatbot is connected to a large language model API, enabling natural language conversations and is accessible to participants 24 hours
Other: web application with AI chat · Other: usual clinic care follows the national prevention and management guidelines for major cardiovascular risk factors
Usual care follows the national prevention and management guidelines for major cardiovascular risk factors including hypertension, dyslipidemia, diabetes, smoking, obesity, and physical inactivity. Patients typically undergo periodic clinical assessment which includes measurement of blood pressure, weight and BMI, review of lifestyle risk factors, and laboratory testing such as fasting blood glucose and lipid profile when indicated. Standard lifestyle counseling is provided in the form of brief verbal advice concerning smoking cessation, healthy diet, and increasing physical activity. Pharmacological therapy is initiated or adjusted based on the clinical assessment and guideline recommendations (e.g., antihypertensive medications, statins, antidiabetic treatment). Follow-up visits (monthly visits for 3 months).
Other: usual clinic care follows the national prevention and management guidelines for major cardiovascular risk factors
• Web app features: User account with secure login, baseline profile (age, sex, BP, lipids, smoking, diabetes, medications) Automated calculation of 10-year cardio vascular disease risk (ASCVDR) will be done using The American College of Cardiology (ACC)/American Heart Association (AHA) Risk Estimator of ASCVD. * Educational modules (short, evidence-based content in Arabic) * Integrated AI chat An AI-powered chatbot is integrated into the web application to provide interactive health education and respond to user inquiries regarding cardiovascular risk, lifestyle modification, dietary advices and prevention strategies. The chatbot is connected to a large language model API, enabling natural language conversations and is accessible to participants 24 hours a day. Medical content and responses were reviewed and supervised by the research team to ensure accuracy and adherence to international guidelines (American Heart Association \[AHA\] and European Society of Cardiology \[ESC\].
Usual care follows the national prevention and management guidelines for major cardiovascular risk factors including hypertension, dyslipidemia, diabetes, smoking, obesity, and physical inactivity. Patients typically undergo periodic clinical assessment which includes measurement of blood pressure, weight and BMI, review of lifestyle risk factors, and laboratory testing such as fasting blood glucose and lipid profile when indicated. Standard lifestyle counseling is provided in the form of brief verbal advice concerning smoking cessation, healthy diet, and increasing physical activity. Pharmacological therapy is initiated or adjusted based on the clinical assessment and guideline recommendations (e.g., antihypertensive medications, statins, antidiabetic treatment). Follow-up visits (monthly visits for 3 months).
Mean absolute change in predicted 10-year cardiovascular risk (%) from baseline to 3 months in intervention and control groups.
Time frame: 3 months
Mean change in systolic BP (mmHg)
Change in systolic blood pressure from baseline to 3 months, measured in mmHg.
Time frame: 3 months
Mean change in diastolic blood pressure
Change in diastolic blood pressure from baseline to 3 months, measured in mmHg.
Time frame: 3 months
Mean change in LDL cholesterol
Change in low-density lipoprotein (LDL) cholesterol level from baseline to 3 months, measured in mg/dL.
Time frame: 3 months
Mean change in HDL cholesterol
Change in high-density lipoprotein (HDL) cholesterol level from baseline to 3 months, measured in mg/dL.
Time frame: 3 months
Mean change in total cholesterol
Change in total cholesterol level from baseline to 3 months, measured in mg/dL.
Time frame: 3 months
Mean change in HbA1c among participants with diabetes
Change in glycated hemoglobin (HbA1c) from baseline to 3 months among participants with diabetes, measured as a percentage (%).
Time frame: 3 months
System Usability Scale (SUS) score
Usability of the web-based application will be assessed using the 10-item System Usability Scale (SUS), with total scores ranging from 0 to 100. Higher scores indicate better perceived usability.
Time frame: 3 months
Change in medication adherence score
Change in medication adherence from baseline to 3 months, assessed using Adherence to Refills and Medications Scale (ARMS) questionnaire . It consists of 12 items covering two main domains: medication-taking behavior and prescription refill adherence Each item is scored on a 4-point Likert scale ranging from 1 (none of the time) to 4 (all of the time), with higher scores indicating lower adherence
Time frame: 3 months
No study locations are listed for this record.
Plan to share: Undecided
No publications or documents are linked to this record.
Start is estimated for Oct 2026; primary completion for Aug 2027, 10 months later.
How these figures are worked out, and which studies are left out of them.
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
This study is not yet recruiting, as verified in Oct 2026. You cannot join it, but the record below documents what was studied.
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