Cardiovascular Risk FactorsCARAMEL RSNCT06999317
CARAMEL: Retrospective Study for Personalized Risk Assessment of Cardiovascular Disease in Menopausal and Perimenopausal Women Using Real World Data
An observational study of Cardiovascular Risk Factors and Menopausal Women, run by Hospital Universitario Virgen Macarena.
Trial summary
This retrospective observational study, part of the EU-funded CARAMEL project, aims to develop and validate personalized cardiovascular disease (CVD) risk assessment models specifically designed for menopausal and perimenopausal women (ages 40-60). Read more about this study
- Who is it for?
- Ages 40 to 60 years, women only
- Conditions the study is for
- Cardiovascular Risk Factors, Menopausal Women, Perimenopausal Women
- How many people
- 1,500,000 participants
- Where
- No sites listed yet
- Study dates
- 1 Mar 2026to 30 Apr 2028
- 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 40 to 60 years
- Women only
- No healthy volunteers
- Adult
Study population: Participants are identified retrospectively from electronic health records, imaging archives, and device registries across multiple healthcare systems and countries
Who may be able to join
- Self-identified as female in the electronic health record (EHR). Age between 40 and 60 years at the time of data collection/index date. Availability of at least 5-6 years of retrospective data in the EHR, depending on the research objective.
- At least one healthcare encounter (visit, imaging, lab test, diagnosis, etc.) within the defined age range.
- For imaging substudies (e.g., RO3-RO5): availability of at least one relevant imaging test (e.g., DXA, digital mammography, cMRI, CCTA, US) during the age range.
- For signal-based analysis (RO6): presence of ECG monitoring data from implanted devices and at least 2 years of follow-up.
Who cannot join
- Prior diagnosis of cardiovascular disease before the observation window (only applicable to specific ROs, e.g., RO2, RO4).
- Insufficient data quality or missing key variables needed for modeling (e.g., absence of blood pressure or lipid profile).
- Patients with incomplete or inconsistent records (e.g., duplicate IDs, mismatched time frames).
- For signal-based RO6: hospitalizations or diagnoses unrelated to cardiovascular health that may bias AI model training.
About this study
This retrospective observational study, part of the EU-funded CARAMEL project, aims to develop and validate personalized cardiovascular disease (CVD) risk assessment models specifically designed for menopausal and perimenopausal women (ages 40-60). The study leverages Real World Data (RWD) collected from multiple international clinical partners, including electronic health records (EHR), diagnostic imaging data, and signal data.
The main objective is to improve the prediction of CVD precursors such as hypertension and dyslipidemia, as well as mid- and long-term risk of CVD events, through advanced artificial intelligence (AI) models. These models will be trained on multimodal data to capture complex, individualized risk trajectories that current risk calculators fail to address, particularly in women. Special focus is placed on under-researched, women-specific risk factors and their interactions with traditional predictors.
Read more
The study includes several research objectives: (1) predicting the onset of hypertension and dyslipidemia using EHR data; (2) modeling the long-term risk of fatal and non-fatal cardiovascular events and disease trajectories; (3) identifying novel imaging biomarkers from routine screening tests such as mammography, DXA, ultrasound, and cardiac MRI; (4) developing multimodal prediction models combining imaging and clinical data; (5) creating automated AI tools for imaging biomarker extraction; and (6) using signal data from cardiac devices to predict disease progression and events.
The study population consists of middle-aged women with retrospective data available across different health systems. The expected outcome is a validated set of stratified, personalized CVD risk models that can support targeted prevention strategies and enable more equitable, sex-specific care. This will contribute to reducing the burden of CVD in women and addressing critical gaps in early detection, clinical decision-making, and health policy.
This project has received funding from the European Union's Horizon Europe Research and Innovation Programme under Grant Agreement No 101156210.
- Keywords
- Cardiovascular Disease, Cardiovascular risk factors, Menopausal women, Perimenopausal women, real world data, personalised prevention, computational modelling, women-specific risks
- Medical subject headings
- Cardiovascular Diseases
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 |
|---|---|---|
| ASCIRES IMAGE DATABASE | Digital imaging biobank 10y long from several manufact 1,000 cMRI; 500 cardiac CT; 500 coronary artery calcification; 1,000 DXA From women 40- 60y urers / modalities | |
| Basque Health Service Database | Longitudinal EHR data up to 15y including diagnosis, procedures, prescriptions, lab tests, visits, imaging, etc. ~128,00 women 40-60 14,880 DM, 3,124 DXA, 332 carotid US | |
| Clalit Primary Prevention Database | Manually curated DB of structured EHR data ~750,000 middleaged women | |
| Irish Implant Devices Registry | Irish Implant Devices Registry (REG) (HRI) 15y of data for implant procedures and follow-ups (pacemakers, ICD's, loop recorders) ~85,000 implant (pacemaker) proced ures ~700,000 follow-up w. indications \& diagnosis | |
| Keralty Colombia Database | EHR data from primary/specialised care centres. Longitudinal EHR data up to 5-10y Including diagnosis, procedures, prescriptions, lab tests, visits, etc. ~85,593 women 40-60y ~25,000 women with CVD problems | |
| Andalusian Health Population Database & Macarena University Hospital EHR | Longitudinal EHR data up to 15y including diagnosis, clinical procedures, prescriptions, lab tests, visits, etc. The hospital Dataset is OMOP CMD mapped ~700,000 middleaged women | |
| Lithuanian High Cardiovascular Risk (LitHiR) primary prevention programme database | EHR data from primary cardiovascular prevention programme in VULSK (1 centre). Data including demographics, risk factors, lab tests (including lipid profile, renal function, etc.), arterial markers (pulse wave velocity analysis data; CardioAngle Vascular Index data; carotid artery intimamedia thickness data). Some patients have 5-10y longitudinal data with outcomes. ~6000 women 40-65y with high - very high cardiovascular risk, but without overt CVD; | |
| National and Kapodistrian University of Athens Database - Aretaieion Hospital | EHR data from Menopause clinic of Aretaieion university hospital including blood tests, medication, prescriptions, visits ~4000 middle aged women | |
| CoroPrevention - Tampere University (TAU) | Pan-European (25 sites) contemporary prospective CVD prevention cohort from ongoing HEU project it includes clinical data, 3-year CV event data, lifestyle, RFs. Standard + CVD biomarkers (CERT2, hsTNI, NTproBNP, Cystatin C…) N=~3,000 women (subsample of whole cohort) | |
| AKRIBEA - Cooperative Research Centre for Biosciences Association (CIC) | Non-oriented 7y follow-up cohort from Basque Country Region. Urine+serum biomarkers and metabolome; serum lipoproteins by NMR; demographics \& RFs N=~ 2,500 women (40 to 60 y) | |
| MENO - Cooperative Research Centre for Biosciences Association (CIC) | Pre- and post-menopausal women cohort from Basque Country Region. Urine+serum biomarkers and metabolome; serum lipoproteins by NMR; demographics \& RFs N =~ 1,700 women | |
| UK Biobank - UK Biobank | Largest geno-phenotype-rich population-based study in the world (500K), includes multi-modal imaging data (60K) and eye and vision (67K), biomarkers, demographic data, lifestyle (100K with wearables) and health outcomes. Middle-aged women among: * 500K baseline * 60K imaging study * 67K retina \& OCT | |
| Qatar Biobank | Population-based with annotated data, biological samples, tests and imaging for 60K participants. It includes Demographics data, lifestyle, biomarkers, weight \& body fat, hip\&waist, BP, ECG, carotid US, full-body MRI, retinography, DXA Middle-aged women among ~60K total participants | |
| International Agency for Research on Cancer (IARC) / EPIC-Europa | Long-term European population-based cohort (520K participants across 10 countries). Includes clinical data, anthropometric measurements, demographic, lifestyle, dietary habits, and socioeconomic data, reproductive history, and biological samples such as serum, plasma and DNA for biochemical data and genotyping data N = ~367k women between 35 to 65 years old (subsample of whole cohort) ~65k CVD cases across the full cohort | |
| ILERVAS -Institute for Research in Biomedicine IRB Lleida | Interventional longitudinal study that includes detailed assessments of subclinical atheromatosis in 12 vascular territories using ultrasound, along with clinical, anthropometric, lifestyle, dietary, and biochemical data. N = ~4165 women (50 to 70y) (subsample of whole cohort) |
What is being measured
The primary outcome is the main question the study is designed to answer.
Occurrence and Predicted Risk of Cardiovascular Disease (CVD) Events (fatal and non-fatal)
The study will retrospectively evaluate the occurrence of cardiovascular disease (CVD) events and develop predictive models to estimate individual risk profiles for such events. CVD events include both fatal and non-fatal occurrences such as myocardial infarction, stroke, heart failure, arrhythmias, and atherosclerotic disease. Events will be identified using structured electronic health records (EHR) and coded using ICD-10 classifications. Risk will be modeled using multimodal data sources (EHR, imaging, and signals) to predict short- and long-term outcomes, stratified by individual characteristics.
The outcome integrates:
Event-based measures: Time to first fatal or non-fatal CVD event.
Risk-based measures: Individual predicted probabilities of experiencing a CVD event or precursor condition (e.g., hypertension, dyslipidemia) over different time frames.
Measured: up to 10 years
Secondary outcomes (6)
RO1. Personalized risk prediction of CVD precursors
First observation of HT or DY registered in the EHR, registered as a diagnostic code, or as a laboratory result or test. These include:
- Diagnosis of HT registered in the EHR with either of the following ICD10 codes:
- I10 Essential (primary) hypertension
- I11.0 Hypertensive heart disease with heart failure
- I11.9 Hypertensive heart disease without heart failure
- I12.0 Hypertensive chronic kidney disease with stage 5 chronic kidney disease or end stage renal disease
- I13.0 Hypertensive heart and chronic kidney disease with heart failure and stage 1 through stage 4 chronic kidney disease, or unspecified chronic kidney disease
- I13.1 Hypertensive heart and chronic kidney disease without heart failure
- I13.2 Hypertensive heart and chronic kidney disease with heart failure and with stage 5 chronic kidney disease, or end stage renal disease
- Diagnosis of DY registered in the EHR with either of the following ICD10 codes:
- E78.1 Pure hyperglyceridemia
- E78.2 Mixed hyperlipidemia
Measured: up to 8 years
RO2. Personalized Risk Prediction of CVD Events and CVD trajectories
The occurrence of CVD events, which will be classified in fatal (if they are registered as the cause of death) or not fatal (if they are not registered as cause of death).
- Fatal CVD events include the following ICD codes registered in the EHR:
- I10-16 Hypertensive disease
- I20-25 Ischemic heart disease
- I46-52 Arrhythmias and heart failure, excluding I51.4 (Myocarditis unspecified)
- I60-69 Cerebrovascular diseases
- I70-73 Atherosclerosis/AAA
- Not fatal CVD events include only the following ICD codes:
- I21-I23 Not fatal myocardial infarction
- I60-69 Not-fatal stroke
Measured: Up to 16 years
RO3. Novel Imaging Biomarkers and Patterns for CVD Risk Assessment
Evaluates the predictive performance of multimodal models combining imaging features (e.g., cardiac MRI, DXA, digital mammography) and electronic health record (EHR) variables to estimate the mid- and long-term risk of cardiovascular events (CVD) in women aged 40-60. The endpoint is the first occurrence of a fatal or non-fatal CVD event after the imaging test, as documented in the EHR. The models will be compared against standard risk assessment tools (e.g., SCORE2).
Measured: Baseline
RO4. Multimodal EHR and ImageBased CVD Prediction Models
The occurrence of CVD events, which will be classified in fatal (if they are registered as the cause of death) or not fatal (if they are not registered as cause of death).
- Fatal CVD events include the following ICD codes registered in the EHR:
- I10-16 Hypertensive disease
- I20-25 Ischemic heart disease
- I46-52 Arrhythmias and heart failure, excluding I51.4 (Myocarditis unspecified)
- I60-69 Cerebrovascular diseases
- I70-73 Atherosclerosis/AAA
- Not fatal CVD events include only the following ICD codes:
- I21-I23 Not fatal myocardial infarction
- I60-69 Not-fatal stroke
Measured: Up to 16 years
RO5. Automatic imaging marker and pattern extraction
The performance and clinical relevance of AI-based tools for the automatic extraction of cardiovascular imaging biomarkers in women aged 40-60. These tools will be used to segment anatomical regions and calculate quantitative measures from multimodal imaging (e.g., ultrasound, DXA, cardiac CT, cMRI, mammography).
Measured: Baseline
RO6. Signal-based CVD prediction models
Occurrance of CVD events, which include:
- The occurrence of Arrhythmia episodes including atrial fibrillation, ventricular tachycardia, and bradyarrhythmias.
- The occurrence of Heart failure and structural heart disease, particularly severe left ventricular dysfunction and cardiomyopathy.
- The occurrence of Ischemic events such as myocardial infarction (MI), coronary artery disease (CAD), and cerebrovascular accidents (CVA).
- Device-related events, including the transition from loop recorders to pacemakers or ICDs due to worsening conditions. Unit of Measure: Recorded episodes (frequency/time) or binary outcome (present/absent).
Measured: Up to 16 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 May 2025
- Study start1 Mar 2026 (estimated)
- Primary completion1 Dec 2027 (estimated)
- Study completion30 Apr 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Cardiovascular Risk FactorsStudies 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
- Other
- Time perspective
- Retrospective
- Enrolment
- 1,500,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hospital Universitario Virgen Macarena
- Sponsor type
- University, hospital or other
- Collaborators
- VISUAL INTERACTION & COMMUNICATION TECHNOLOGIES - VICOMTECH, Clinic for Cardiovascular Diseases Magdalena, Biokeralty Research Institute, Keralty SAS. Colombia, ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINON, Fundación Pública Andaluza para la gestión de la Investigación en Sevilla, University of Dublin, Trinity College, TREE Technology S.A., Dublin City University, Tampere University, Ben-Gurion University of the Negev, Biogipuzkoa Health Research Institute, Vilnius University Hospital Santaros Klinikos
- Responsible party
- Principal investigator, Luis Gabriel Luque Romero, Hospital Universitario Virgen Macarena
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06999317
- Sponsor's protocol ID
- CARAMEL RS
- Acronym
- CARAMEL RS
- Status last verified
- Jan 2026
- First submitted
- 14 May 2025
- Last updated
- 15 Jan 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 15 Jan 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- CARAMEL: Retrospective Study for Personalized Risk Assessment of Cardiovascular Disease in Menopausal and Perimenopausal Women Using Real World Data
- ClinicalTrials.gov ID
- NCT06999317
- Acronym / sponsor ID
- CARAMEL RS / CARAMEL RS
- Keywords
- Cardiovascular Disease, Cardiovascular risk factors, Menopausal women, Perimenopausal women, real world data, personalised prevention, computational modelling, women-specific risks
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,500,000 participants (estimated)
- Lead sponsor
- Hospital Universitario Virgen MacarenaUniversity, hospital or other
- Collaborators
- VISUAL INTERACTION & COMMUNICATION TECHNOLOGIES - VICOMTECH, Clinic for Cardiovascular Diseases Magdalena, Biokeralty Research Institute, Keralty SAS. Colombia, ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINON, Fundación Pública Andaluza para la gestión de la Investigación en Sevilla, University of Dublin, Trinity College, TREE Technology S.A., Dublin City University, Tampere University, Ben-Gurion University of the Negev, Biogipuzkoa Health Research Institute, Vilnius University Hospital Santaros Klinikos
- Study start
- 1 Mar 2026 (estimated)
- Primary completion
- 1 Dec 2027 (estimated)
- Study completion
- 30 Apr 2028 (estimated)
- First posted
- 31 May 2025 (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.
This retrospective observational study, part of the EU-funded CARAMEL project, aims to develop and validate personalized cardiovascular disease (CVD) risk assessment models specifically designed for menopausal and perimenopausal women (ages 40-60). The study leverages Real World Data (RWD) collected from multiple international clinical partners, including electronic health records (EHR), diagnostic imaging data, and signal data.
The main objective is to improve the prediction of CVD precursors such as hypertension and dyslipidemia, as well as mid- and long-term risk of CVD events, through advanced artificial intelligence (AI) models. These models will be trained on multimodal data to capture complex, individualized risk trajectories that current risk calculators fail to address, particularly in women. Special focus is placed on under-researched, women-specific risk factors and their interactions with traditional predictors.
The study includes several research objectives: (1) predicting the onset of hypertension and dyslipidemia using EHR data; (2) modeling the long-term risk of fatal and non-fatal cardiovascular events and disease trajectories; (3) identifying novel imaging biomarkers from routine screening tests such as mammography, DXA, ultrasound, and cardiac MRI; (4) developing multimodal prediction models combining imaging and clinical data; (5) creating automated AI tools for imaging biomarker extraction; and (6) using signal data from cardiac devices to predict disease progression and events.
The study population consists of middle-aged women with retrospective data available across different health systems. The expected outcome is a validated set of stratified, personalized CVD risk models that can support targeted prevention strategies and enable more equitable, sex-specific care. This will contribute to reducing the burden of CVD in women and addressing critical gaps in early detection, clinical decision-making, and health policy.
This project has received funding from the European Union's Horizon Europe Research and Innovation Programme under Grant Agreement No 101156210.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 15
| Arm | Type | Receives |
|---|---|---|
| ASCIRES IMAGE DATABASE | – | –Digital imaging biobank 10y long from several manufact 1,000 cMRI; 500 cardiac CT; 500 coronary artery calcification; 1,000 DXA From women 40- 60y urers / modalities |
| Basque Health Service Database | – | –Longitudinal EHR data up to 15y including diagnosis, procedures, prescriptions, lab tests, visits, imaging, etc. ~128,00 women 40-60 14,880 DM, 3,124 DXA, 332 carotid US |
| Clalit Primary Prevention Database | – | –Manually curated DB of structured EHR data ~750,000 middleaged women |
| Irish Implant Devices Registry | – | –Irish Implant Devices Registry (REG) (HRI) 15y of data for implant procedures and follow-ups (pacemakers, ICD's, loop recorders) ~85,000 implant (pacemaker) proced ures ~700,000 follow-up w. indications \& diagnosis |
| Keralty Colombia Database | – | –EHR data from primary/specialised care centres. Longitudinal EHR data up to 5-10y Including diagnosis, procedures, prescriptions, lab tests, visits, etc. ~85,593 women 40-60y ~25,000 women with CVD problems |
| Andalusian Health Population Database & Macarena University Hospital EHR | – | –Longitudinal EHR data up to 15y including diagnosis, clinical procedures, prescriptions, lab tests, visits, etc. The hospital Dataset is OMOP CMD mapped ~700,000 middleaged women |
| Lithuanian High Cardiovascular Risk (LitHiR) primary prevention programme database | – | –EHR data from primary cardiovascular prevention programme in VULSK (1 centre). Data including demographics, risk factors, lab tests (including lipid profile, renal function, etc.), arterial markers (pulse wave velocity analysis data; CardioAngle Vascular Index data; carotid artery intimamedia thickness data). Some patients have 5-10y longitudinal data with outcomes. ~6000 women 40-65y with high - very high cardiovascular risk, but without overt CVD; |
| National and Kapodistrian University of Athens Database - Aretaieion Hospital | – | –EHR data from Menopause clinic of Aretaieion university hospital including blood tests, medication, prescriptions, visits ~4000 middle aged women |
| CoroPrevention - Tampere University (TAU) | – | –Pan-European (25 sites) contemporary prospective CVD prevention cohort from ongoing HEU project it includes clinical data, 3-year CV event data, lifestyle, RFs. Standard + CVD biomarkers (CERT2, hsTNI, NTproBNP, Cystatin C…) N=~3,000 women (subsample of whole cohort) |
| AKRIBEA - Cooperative Research Centre for Biosciences Association (CIC) | – | –Non-oriented 7y follow-up cohort from Basque Country Region. Urine+serum biomarkers and metabolome; serum lipoproteins by NMR; demographics \& RFs N=~ 2,500 women (40 to 60 y) |
| MENO - Cooperative Research Centre for Biosciences Association (CIC) | – | –Pre- and post-menopausal women cohort from Basque Country Region. Urine+serum biomarkers and metabolome; serum lipoproteins by NMR; demographics \& RFs N =~ 1,700 women |
| UK Biobank - UK Biobank | – | –Largest geno-phenotype-rich population-based study in the world (500K), includes multi-modal imaging data (60K) and eye and vision (67K), biomarkers, demographic data, lifestyle (100K with wearables) and health outcomes. Middle-aged women among: * 500K baseline * 60K imaging study * 67K retina \& OCT |
| Qatar Biobank | – | –Population-based with annotated data, biological samples, tests and imaging for 60K participants. It includes Demographics data, lifestyle, biomarkers, weight \& body fat, hip\&waist, BP, ECG, carotid US, full-body MRI, retinography, DXA Middle-aged women among ~60K total participants |
| International Agency for Research on Cancer (IARC) / EPIC-Europa | – | –Long-term European population-based cohort (520K participants across 10 countries). Includes clinical data, anthropometric measurements, demographic, lifestyle, dietary habits, and socioeconomic data, reproductive history, and biological samples such as serum, plasma and DNA for biochemical data and genotyping data N = ~367k women between 35 to 65 years old (subsample of whole cohort) ~65k CVD cases across the full cohort |
| ILERVAS -Institute for Research in Biomedicine IRB Lleida | – | –Interventional longitudinal study that includes detailed assessments of subclinical atheromatosis in 12 vascular territories using ultrasound, along with clinical, anthropometric, lifestyle, dietary, and biochemical data. N = ~4165 women (50 to 70y) (subsample of whole cohort) |
Who may qualify
- Ages
- 40 to 60 years
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult
- Study population
- Participants are identified retrospectively from electronic health records, imaging archives, and device registries across multiple healthcare systems and countries
Key inclusion criteria (4 listed)
- Self-identified as female in the electronic health record (EHR). Age between 40 and 60 years at the time of data collection/index date. Availability of at least 5-6 years of retrospective data in the EHR, depending on the research objective.
- At least one healthcare encounter (visit, imaging, lab test, diagnosis, etc.) within the defined age range.
- For imaging substudies (e.g., RO3-RO5): availability of at least one relevant imaging test (e.g., DXA, digital mammography, cMRI, CCTA, US) during the age range.
- For signal-based analysis (RO6): presence of ECG monitoring data from implanted devices and at least 2 years of follow-up.
Key exclusion criteria (4 listed)
- Prior diagnosis of cardiovascular disease before the observation window (only applicable to specific ROs, e.g., RO2, RO4).
- Insufficient data quality or missing key variables needed for modeling (e.g., absence of blood pressure or lipid profile).
- Patients with incomplete or inconsistent records (e.g., duplicate IDs, mismatched time frames).
- For signal-based RO6: hospitalizations or diagnoses unrelated to cardiovascular health that may bias AI model training.
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
Occurrence and Predicted Risk of Cardiovascular Disease (CVD) Events (fatal and non-fatal)
Time frame: up to 10 years
The study will retrospectively evaluate the occurrence of cardiovascular disease (CVD) events and develop predictive models to estimate individual risk profiles for such events. CVD events include both fatal and non-fatal occurrences such as myocardial infarction, stroke, heart failure, arrhythmias, and atherosclerotic disease. Events will be identified using structured electronic health records (EHR) and coded using ICD-10 classifications. Risk will be modeled using multimodal data sources (EHR, imaging, and signals) to predict short- and long-term outcomes, stratified by individual characteristics. The outcome integrates: Event-based measures: Time to first fatal or non-fatal CVD event. Risk-based measures: Individual predicted probabilities of experiencing a CVD event or precursor condition (e.g., hypertension, dyslipidemia) over different time frames.
6 secondary outcomes
RO1. Personalized risk prediction of CVD precursors
Time frame: up to 8 years
RO2. Personalized Risk Prediction of CVD Events and CVD trajectories
Time frame: Up to 16 years
RO3. Novel Imaging Biomarkers and Patterns for CVD Risk Assessment
Time frame: Baseline
RO4. Multimodal EHR and ImageBased CVD Prediction Models
Time frame: Up to 16 years
RO5. Automatic imaging marker and pattern extraction
Time frame: Baseline
RO6. Signal-based CVD prediction models
Time frame: Up to 16 years
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 15 Jan 2026.
- Individual participant dataSharing planned: Undecided
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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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Cardiovascular Risk Factors and Menopausal Women, run by Hospital Universitario Virgen Macarena.
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 4 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 15 Jan 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Occurrence and Predicted Risk of Cardiovascular Disease (CVD) Events (fatal and non-fatal) (time frame: up to 10 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 15 Jan 2026.