DyslipidemiaNCT07502703
Validation of Remote Photoplethysmography (rPPG)-Derived Cardiovascular Parameters Against Standard Clinical Measurements and Risk Scores in a Community
An observational study of Dyslipidemia and Angina (Stable), run by Tarumanagara University at 1 site in Indonesia.
Trial summary
The goal of this observational study is to evaluate whether a contactless camera-based technology, called remote photoplethysmography (rPPG), can accurately measure cardiovascular parameters and estimate cardiovascular risk in adults aged 30 years and older living in a community setting in Semanan, Jakarta. Read more about this study
- Who is it for?
- Ages 30 years and olderHealthy volunteers can take part
- Conditions the study is for
- Dyslipidemia, Angina (Stable), Coronary Artery Disease (CAD)
- How many people
- 300 participants
- Where
- 1 siteIndonesia
- Study dates
- 23 Apr 2026to 30 Dec 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 30 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The study population consists of community-dwelling adults aged 30 years and older residing in Semanan, Jakarta, Indonesia. Participants will be recruited through community-based consecutive sampling, including local residents, visitors to primary healthcare facilities, and individuals participating in community health programs. Eligible participants are those who are able to provide informed consent and undergo facial video scanning, clinical examination, and basic laboratory testing. Individuals with conditions that may interfere with rPPG signal acquisition (e.g., significant facial abnormalities), inability to remain still during measurement, severe clinical instability, or incomplete key data will be excluded. This population represents a general adult community suitable for evaluating cardiovascular risk screening tools in real-world, primary care and community settings.
Who may be able to join
- Adults aged ≥30 years
- Willing to participate and provide informed consent
- Able to undergo face scan, clinical examination, and laboratory testing
Who cannot join
- Facial abnormalities interfering with rPPG signal acquisition
- Inability to remain still during measurement
- Severe clinical instability
- Incomplete key variables
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Indonesia1 site
Kelurahan Semanan
Jakarta, Jakarta Special Capital Region
Wenny Sanwani, +6281585013412, wenny.sanwani@gmail.com
Hanna Wijaya, +6281223787878, hannwijaya@yahoo.com
About this study
Official title: Validation of Remote Photoplethysmography (rPPG)-Derived Cardiovascular Parameters Against Standard Clinical Measurements and Risk Scores in a Community-Based Population in Semanan, Jakarta
The goal of this observational study is to evaluate whether a contactless camera-based technology, called remote photoplethysmography (rPPG), can accurately measure cardiovascular parameters and estimate cardiovascular risk in adults aged 30 years and older living in a community setting in Semanan, Jakarta. This study aims to determine if rPPG can be used as a simple and accessible tool for early cardiovascular screening.
The main questions it aims to answer are:
Read more
- Do cardiovascular parameters measured using rPPG (such as blood pressure, heart rate, and cardiac workload) agree with standard clinical measurements?
- Do cardiovascular risk estimates generated by rPPG (such as ASCVD risk and Framingham heart age) correspond to risk calculations obtained using conventional clinical and laboratory methods?
Researchers will compare results obtained from rPPG-based facial video scans with results from standard medical assessments, including blood pressure measurements, heart rate evaluation, and laboratory tests for cholesterol levels, to determine the level of agreement and accuracy.
Participants will:
- Undergo a short facial video scan (approximately 30-60 seconds) using an rPPG-based system
- Receive standard clinical assessments, including blood pressure and heart rate measurements
- Provide basic health information (such as age, sex, smoking status, and treatment history) Undergo simple laboratory testing for cholesterol levels
This study is expected to help determine whether rPPG can be used as a reliable, non-invasive, and scalable screening tool for cardiovascular risk in community and primary healthcare settings.
Read the detailed description
Introduction Remote photoplethysmography (rPPG) is an emerging contactless technology that enables extraction of physiological signals from facial video, allowing estimation of cardiovascular parameters such as heart rate and blood pressure. With the growing burden of atherosclerotic cardiovascular disease (ASCVD), early and accessible risk screening tools are essential, particularly in community settings with limited access to laboratory-based assessments. Although established risk models such as the ASCVD and Framingham scores are widely used, their application often requires clinical and laboratory data that may not be readily available. The integration of rPPG-based measurements with cardiovascular risk estimation offers a promising approach; however, its clinical validity and agreement with standard methods remain insufficiently explored .
Objective This study aims to evaluate the agreement and concordance between rPPG-derived cardiovascular parameters and standard clinical measurements, as well as to assess the alignment of rPPG-estimated ASCVD risk and Framingham heart age with conventional risk calculations.
Methods This study will use an analytical observational cross-sectional design conducted in Kelurahan Semanan, Jakarta. Adult participants (≥30 years) will be recruited through community-based sampling. Each participant will undergo clinical anamnesis, physical examination (blood pressure and heart rate), and laboratory testing (total cholesterol and HDL). In parallel, rPPG-based facial video scans will be performed under standardized conditions to obtain systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, cardiac workload, ASCVD risk, and Framingham heart age. Framingham risk will be calculated using sex-specific equations based on clinical and laboratory variables. Agreement between rPPG and standard measurements will be assessed using Bland-Altman analysis, while correlations will be evaluated using Pearson or Spearman tests. Concordance for categorical risk classification will be analyzed using Cohen's Kappa.
Expected Results It is expected that rPPG-derived heart rate will demonstrate good agreement with standard measurements, while blood pressure parameters will show moderate agreement. Additionally, rPPG-based ASCVD risk and Framingham heart age are anticipated to exhibit acceptable concordance with conventional risk calculations. These findings may support the potential role of rPPG as a preliminary screening and risk stratification tool in community-based and telemedicine settings.
- Conditions
- Dyslipidemia, Angina (Stable), Coronary Artery Disease (CAD), Heart Disease, Hypertension, Diabetes (DM)
- Keywords
- remote photoplethysmography, rPPG, cardiovascular risk, ASCVD, Framingham score, digital health, screening tool
- Medical subject headings
- Dyslipidemias, Angina, Stable, Coronary Artery Disease, Heart Diseases, Hypertension, Diabetes Mellitus
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Community Adults Undergoing rPPG and Standard Cardiovascular Assessment | This cohort includes adults aged ≥30 years residing in Semanan, Jakarta, recruited through community-based sampling. Participants will undergo both index testing using remote photoplethysmography (rPPG) via facial video scan and reference standard assessments, including blood pressure measurement, heart rate evaluation, and laboratory testing (total cholesterol and HDL). Additional data such as age, sex, smoking status, and antihypertensive treatment will be collected. There is no intervention applied; all procedures are non-invasive and observational. The study aims to compare rPPG-derived cardiovascular parameters and risk estimates (ASCVD risk and Framingham heart age) with standard clinical measurements to assess agreement and validity. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Agreement of rPPG-Derived Blood Pressure with Standard Measurements
Assessment of agreement between systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure obtained from rPPG-based facial video analysis and standard measurements using aneroid or digital sphygmomanometers. Agreement will be evaluated using Bland-Altman analysis (mean difference and limits of agreement).
Measured: Day 1
Agreement of rPPG-Derived Heart Rate and Cardiac Workload
Evaluation of agreement between heart rate and cardiac workload obtained from rPPG and those measured using standard methods (palpation and pulse oximetry). Agreement will be analyzed using Bland-Altman and correlation analysis (Pearson/Spearman).
Measured: Day 1
Concordance of rPPG-Based ASCVD Risk with Standard Risk Calculation
Assessment of agreement and concordance between ASCVD risk (%) and risk categories (low, intermediate, high) estimated using rPPG and those calculated using conventional clinical and laboratory data. Concordance will be evaluated using Cohen's Kappa and correlation analysis.
Measured: Day 1
Concordance of rPPG-Derived Framingham Heart Age
Evaluation of agreement between Framingham heart age estimated using rPPG-derived parameters and heart age calculated using standard Framingham risk equations based on clinical and laboratory variables. Agreement will be assessed using correlation and Bland-Altman analysis.
Measured: Day 1
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Mar 2026
- Study start23 Apr 2026 (estimated)
- Primary completion30 Jun 2026 (estimated)
- Study completion30 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (10)Papers the sponsor has linked to this study.
- Other trials for DyslipidemiaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Ecologic or community
- Time perspective
- Cross-sectional
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Tarumanagara University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yohanes Firmansyah, dr, MH, MM, Tarumanagara University
- Investigators
- Ernawati Ernawati, Principal investigator, Universitas TarumanagaraYohanes Firmansyah, Study director, Universitas TarumanagaraAlexander Halim Santoso, Study director, Universitas TarumanagaraDavid Wongso, Study director, DexWellnessRatheesh Nair, Study director, Watch Your HealthSri Tiarti, Study chair, Universitas TarumanagaraNoer Saelan Tadjudin, Study chair, Universitas TarumanagaraClement Drew, Principal investigator, Universitas Tarumanagara
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07502703
- Sponsor's protocol ID
- 20260325
- Status last verified
- Apr 2026
- First submitted
- 24 Mar 2026
- Last updated
- 20 Apr 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: De-identified individual participant data (IPD) will be shared, including demographic variables (age, sex), clinical data (blood pressure, heart rate, smoking status, antihypertensive treatment), laboratory results (total cholesterol, HDL), and rPPG-derived parameters (systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, cardiac workload, ASCVD risk, and Framingham heart age). Derived variables such as calculated ASCVD risk scores and Framingham heart age based on standard methods will also be included. All shared data will be anonymized to remove any personally identifiable information, ensuring participant confidentiality. Supporting documents such as the study protocol, statistical analysis plan, and data dictionary will also be made available upon request.
Publications
van Es VAA, Lopata RGP, Scilingo EP, Nardelli M. Contactless Cardiovascular Assessment by Imaging Photoplethysmography: A Comparison with Wearable Monitoring. Sensors (Basel). 2023 Jan 29;23(3):1505. doi: 10.3390/s23031505.
PubMed 36772543Shetty NS, Gaonkar M, Patel N, Vekariya N, Li P, Arora G, Arora P. PREVENT and Pooled Cohort Equations in Mortality Risk Prediction: National Health and Nutrition Examination Survey. JACC Adv. 2024 Dec 26;3(12):101372. doi: 10.1016/j.jacadv.2024.101372. eCollection 2024 Dec.
PubMed 39817066Debnath U, Kim S. A comprehensive review of heart rate measurement using remote photoplethysmography and deep learning. Biomed Eng Online. 2025 Jun 20;24(1):73. doi: 10.1186/s12938-025-01405-5.
PubMed 40542336Pandey A, Mehta A, Paluch A, Ning H, Carnethon MR, Allen NB, Michos ED, Berry JD, Lloyd-Jones DM, Wilkins JT. Performance of the American Heart Association/American College of Cardiology Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Self-reported Physical Activity Levels. JAMA Cardiol. 2021 Jun 1;6(6):690-696. doi: 10.1001/jamacardio.2021.0948.
PubMed 33909016Nguyen QD, Odden MC, Peralta CA, Kim DH. Predicting Risk of Atherosclerotic Cardiovascular Disease Using Pooled Cohort Equations in Older Adults With Frailty, Multimorbidity, and Competing Risks. J Am Heart Assoc. 2020 Sep 15;9(18):e016003. doi: 10.1161/JAHA.119.016003. Epub 2020 Sep 2.
PubMed 32875939Muntner P, Colantonio LD, Cushman M, Goff DC Jr, Howard G, Howard VJ, Kissela B, Levitan EB, Lloyd-Jones DM, Safford MM. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA. 2014 Apr 9;311(14):1406-15. doi: 10.1001/jama.2014.2630.
PubMed 24682252Mora S, Wenger NK, Cook NR, Liu J, Howard BV, Limacher MC, Liu S, Margolis KL, Martin LW, Paynter NP, Ridker PM, Robinson JG, Rossouw JE, Safford MM, Manson JE. Evaluation of the Pooled Cohort Risk Equations for Cardiovascular Risk Prediction in a Multiethnic Cohort From the Women's Health Initiative. JAMA Intern Med. 2018 Sep 1;178(9):1231-1240. doi: 10.1001/jamainternmed.2018.2875.
PubMed 30039172Khera R, Pandey A, Ayers CR, Carnethon MR, Greenland P, Ndumele CE, Nambi V, Seliger SL, Chaves PHM, Safford MM, Cushman M, Xanthakis V, Vasan RS, Mentz RJ, Correa A, Lloyd-Jones DM, Berry JD, de Lemos JA, Neeland IJ. Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index. JAMA Netw Open. 2020 Oct 1;3(10):e2023242. doi: 10.1001/jamanetworkopen.2020.23242.
PubMed 33119108Chin JW, Chan PHD, Chen S, Cheng CH, So RHY, Chow E, Fok BSP, Wong KL. Clinical Validation of rPPG-Enabled Contactless Pulse Rate Monitoring Software in Cardiovascular Disease Patients. Bioengineering (Basel). 2026 Feb 20;13(2):246. doi: 10.3390/bioengineering13020246.
PubMed 41749785Allado E, Poussel M, Moussu A, Hily O, Temperelli M, Cherifi A, Saunier V, Bernard Y, Albuisson E, Chenuel B. Accurate and Reliable Assessment of Heart Rate in Real-Life Clinical Settings Using an Imaging Photoplethysmography. J Clin Med. 2022 Oct 17;11(20):6101. doi: 10.3390/jcm11206101.
PubMed 36294422
Study at a glance
From the registry record, last updated by the sponsor on 20 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of Remote Photoplethysmography (rPPG)-Derived Cardiovascular Parameters Against Standard Clinical Measurements and Risk Scores in a Community-Based Population in Semanan, Jakarta
- ClinicalTrials.gov ID
- NCT07502703
- Acronym / sponsor ID
- 20260325
- Conditions
- Dyslipidemia, Angina (Stable), Coronary Artery Disease (CAD), Heart Disease, Hypertension, Diabetes (DM)
- Keywords
- remote photoplethysmography, rPPG, cardiovascular risk, ASCVD, Framingham score, digital health, screening tool
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Tarumanagara UniversityUniversity, hospital or other
- Study start
- 23 Apr 2026 (estimated)
- Primary completion
- 30 Jun 2026 (estimated)
- Study completion
- 30 Dec 2026 (estimated)
- First posted
- 31 Mar 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this observational study is to evaluate whether a contactless camera-based technology, called remote photoplethysmography (rPPG), can accurately measure cardiovascular parameters and estimate cardiovascular risk in adults aged 30 years and older living in a community setting in Semanan, Jakarta. This study aims to determine if rPPG can be used as a simple and accessible tool for early cardiovascular screening.
The main questions it aims to answer are:
- Do cardiovascular parameters measured using rPPG (such as blood pressure, heart rate, and cardiac workload) agree with standard clinical measurements?
- Do cardiovascular risk estimates generated by rPPG (such as ASCVD risk and Framingham heart age) correspond to risk calculations obtained using conventional clinical and laboratory methods?
Researchers will compare results obtained from rPPG-based facial video scans with results from standard medical assessments, including blood pressure measurements, heart rate evaluation, and laboratory tests for cholesterol levels, to determine the level of agreement and accuracy.
Participants will:
- Undergo a short facial video scan (approximately 30-60 seconds) using an rPPG-based system
- Receive standard clinical assessments, including blood pressure and heart rate measurements
- Provide basic health information (such as age, sex, smoking status, and treatment history) Undergo simple laboratory testing for cholesterol levels
This study is expected to help determine whether rPPG can be used as a reliable, non-invasive, and scalable screening tool for cardiovascular risk in community and primary healthcare settings.
Detailed description
Introduction Remote photoplethysmography (rPPG) is an emerging contactless technology that enables extraction of physiological signals from facial video, allowing estimation of cardiovascular parameters such as heart rate and blood pressure. With the growing burden of atherosclerotic cardiovascular disease (ASCVD), early and accessible risk screening tools are essential, particularly in community settings with limited access to laboratory-based assessments. Although established risk models such as the ASCVD and Framingham scores are widely used, their application often requires clinical and laboratory data that may not be readily available. The integration of rPPG-based measurements with cardiovascular risk estimation offers a promising approach; however, its clinical validity and agreement with standard methods remain insufficiently explored .
Objective This study aims to evaluate the agreement and concordance between rPPG-derived cardiovascular parameters and standard clinical measurements, as well as to assess the alignment of rPPG-estimated ASCVD risk and Framingham heart age with conventional risk calculations.
Methods This study will use an analytical observational cross-sectional design conducted in Kelurahan Semanan, Jakarta. Adult participants (≥30 years) will be recruited through community-based sampling. Each participant will undergo clinical anamnesis, physical examination (blood pressure and heart rate), and laboratory testing (total cholesterol and HDL). In parallel, rPPG-based facial video scans will be performed under standardized conditions to obtain systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, cardiac workload, ASCVD risk, and Framingham heart age. Framingham risk will be calculated using sex-specific equations based on clinical and laboratory variables. Agreement between rPPG and standard measurements will be assessed using Bland-Altman analysis, while correlations will be evaluated using Pearson or Spearman tests. Concordance for categorical risk classification will be analyzed using Cohen's Kappa.
Expected Results It is expected that rPPG-derived heart rate will demonstrate good agreement with standard measurements, while blood pressure parameters will show moderate agreement. Additionally, rPPG-based ASCVD risk and Framingham heart age are anticipated to exhibit acceptable concordance with conventional risk calculations. These findings may support the potential role of rPPG as a preliminary screening and risk stratification tool in community-based and telemedicine settings.
Study design
- Observational model
- Ecologic or community
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Community Adults Undergoing rPPG and Standard Cardiovascular Assessment | – | –This cohort includes adults aged ≥30 years residing in Semanan, Jakarta, recruited through community-based sampling. Participants will undergo both index testing using remote photoplethysmography (rPPG) via facial video scan and reference standard assessments, including blood pressure measurement, heart rate evaluation, and laboratory testing (total cholesterol and HDL). Additional data such as age, sex, smoking status, and antihypertensive treatment will be collected. There is no intervention applied; all procedures are non-invasive and observational. The study aims to compare rPPG-derived cardiovascular parameters and risk estimates (ASCVD risk and Framingham heart age) with standard clinical measurements to assess agreement and validity. |
Who may qualify
- Ages
- 30 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of community-dwelling adults aged 30 years and older residing in Semanan, Jakarta, Indonesia. Participants will be recruited through community-based consecutive sampling, including local residents, visitors to primary healthcare facilities, and individuals participating in community health programs. Eligible participants are those who are able to provide informed consent and undergo facial video scanning, clinical examination, and basic laboratory testing. Individuals with conditions that may interfere with rPPG signal acquisition (e.g., significant facial abnormalities), inability to remain still during measurement, severe clinical instability, or incomplete key data will be excluded. This population represents a general adult community suitable for evaluating cardiovascular risk screening tools in real-world, primary care and community settings.
Key inclusion criteria (3 listed)
- Adults aged ≥30 years
- Willing to participate and provide informed consent
- Able to undergo face scan, clinical examination, and laboratory testing
Key exclusion criteria (4 listed)
- Facial abnormalities interfering with rPPG signal acquisition
- Inability to remain still during measurement
- Severe clinical instability
- Incomplete key variables
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Agreement of rPPG-Derived Blood Pressure with Standard Measurements
Time frame: Day 1
Assessment of agreement between systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure obtained from rPPG-based facial video analysis and standard measurements using aneroid or digital sphygmomanometers. Agreement will be evaluated using Bland-Altman analysis (mean difference and limits of agreement).
Agreement of rPPG-Derived Heart Rate and Cardiac Workload
Time frame: Day 1
Evaluation of agreement between heart rate and cardiac workload obtained from rPPG and those measured using standard methods (palpation and pulse oximetry). Agreement will be analyzed using Bland-Altman and correlation analysis (Pearson/Spearman).
Concordance of rPPG-Based ASCVD Risk with Standard Risk Calculation
Time frame: Day 1
Assessment of agreement and concordance between ASCVD risk (%) and risk categories (low, intermediate, high) estimated using rPPG and those calculated using conventional clinical and laboratory data. Concordance will be evaluated using Cohen's Kappa and correlation analysis.
Concordance of rPPG-Derived Framingham Heart Age
Time frame: Day 1
Evaluation of agreement between Framingham heart age estimated using rPPG-derived parameters and heart age calculated using standard Framingham risk equations based on clinical and laboratory variables. Agreement will be assessed using correlation and Bland-Altman analysis.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Apr 2026.
- Background: PubMed 36772543van Es VAA, Lopata RGP, Scilingo EP, Nardelli M. Contactless Cardiovascular Assessment by Imaging Photoplethysmography: A Comparison with Wearable Monitoring. Sensors (Basel). 2023 Jan 29;23(3):1505. doi: 10.3390/s23031505.
- Background: PubMed 39817066Shetty NS, Gaonkar M, Patel N, Vekariya N, Li P, Arora G, Arora P. PREVENT and Pooled Cohort Equations in Mortality Risk Prediction: National Health and Nutrition Examination Survey. JACC Adv. 2024 Dec 26;3(12):101372. doi: 10.1016/j.jacadv.2024.101372. eCollection 2024 Dec.
- Background: PubMed 40542336Debnath U, Kim S. A comprehensive review of heart rate measurement using remote photoplethysmography and deep learning. Biomed Eng Online. 2025 Jun 20;24(1):73. doi: 10.1186/s12938-025-01405-5.
- Background: PubMed 33909016Pandey A, Mehta A, Paluch A, Ning H, Carnethon MR, Allen NB, Michos ED, Berry JD, Lloyd-Jones DM, Wilkins JT. Performance of the American Heart Association/American College of Cardiology Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Self-reported Physical Activity Levels. JAMA Cardiol. 2021 Jun 1;6(6):690-696. doi: 10.1001/jamacardio.2021.0948.
- Background: PubMed 32875939Nguyen QD, Odden MC, Peralta CA, Kim DH. Predicting Risk of Atherosclerotic Cardiovascular Disease Using Pooled Cohort Equations in Older Adults With Frailty, Multimorbidity, and Competing Risks. J Am Heart Assoc. 2020 Sep 15;9(18):e016003. doi: 10.1161/JAHA.119.016003. Epub 2020 Sep 2.
- Background: PubMed 24682252Muntner P, Colantonio LD, Cushman M, Goff DC Jr, Howard G, Howard VJ, Kissela B, Levitan EB, Lloyd-Jones DM, Safford MM. Validation of the atherosclerotic cardiovascular disease Pooled Cohort risk equations. JAMA. 2014 Apr 9;311(14):1406-15. doi: 10.1001/jama.2014.2630.
- Background: PubMed 30039172Mora S, Wenger NK, Cook NR, Liu J, Howard BV, Limacher MC, Liu S, Margolis KL, Martin LW, Paynter NP, Ridker PM, Robinson JG, Rossouw JE, Safford MM, Manson JE. Evaluation of the Pooled Cohort Risk Equations for Cardiovascular Risk Prediction in a Multiethnic Cohort From the Women's Health Initiative. JAMA Intern Med. 2018 Sep 1;178(9):1231-1240. doi: 10.1001/jamainternmed.2018.2875.
- Background: PubMed 33119108Khera R, Pandey A, Ayers CR, Carnethon MR, Greenland P, Ndumele CE, Nambi V, Seliger SL, Chaves PHM, Safford MM, Cushman M, Xanthakis V, Vasan RS, Mentz RJ, Correa A, Lloyd-Jones DM, Berry JD, de Lemos JA, Neeland IJ. Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index. JAMA Netw Open. 2020 Oct 1;3(10):e2023242. doi: 10.1001/jamanetworkopen.2020.23242.
- Background: PubMed 41749785Chin JW, Chan PHD, Chen S, Cheng CH, So RHY, Chow E, Fok BSP, Wong KL. Clinical Validation of rPPG-Enabled Contactless Pulse Rate Monitoring Software in Cardiovascular Disease Patients. Bioengineering (Basel). 2026 Feb 20;13(2):246. doi: 10.3390/bioengineering13020246.
- Background: PubMed 36294422Allado E, Poussel M, Moussu A, Hily O, Temperelli M, Cherifi A, Saunier V, Bernard Y, Albuisson E, Chenuel B. Accurate and Reliable Assessment of Heart Rate in Real-Life Clinical Settings Using an Imaging Photoplethysmography. J Clin Med. 2022 Oct 17;11(20):6101. doi: 10.3390/jcm11206101.
- Individual participant dataSharing planned: Yes. De-identified individual participant data (IPD) will be shared, including demographic variables (age, sex), clinical data (blood pressure, heart rate, smoking status, antihypertensive treatment), laboratory results (total cholesterol, HDL), and rPPG-derived parameters (systolic and diastolic blood pressure, mean arterial pressure, pulse pressure, heart rate, cardiac workload, ASCVD risk, and Framingham heart age). Derived variables such as calculated ASCVD risk scores and Framingham heart age based on standard methods will also be included. All shared data will be anonymized to remove any personally identifiable information, ensuring participant confidentiality. Supporting documents such as the study protocol, statistical analysis plan, and data dictionary will also be made available upon request.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Ernawati Ernawati principal investigator
Universitas Tarumanagara
Yohanes Firmansyah study director
Universitas Tarumanagara
Alexander Halim Santoso study director
Universitas Tarumanagara
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Dyslipidemia and Angina (Stable), run by Tarumanagara University at 1 site in Indonesia.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 20 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Indonesia. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Alexander Halim Santoso, MD (+6281381606869, alexanders@fk.untar.ac.id), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Agreement of rPPG-Derived Blood Pressure with Standard Measurements (time frame: Day 1). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07502703, which also lists 10 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 20 Apr 2026.