CARAMEL Observational Study
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Perimenopause, Menopause, Cardiovascular (CV) Risk, Women (Between 30 to 60 Years Old). Basic parameters: 40 years — 60 years · Female.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Colombia, Croatia, Greece, Lithuania, Spain
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
CArdiovascular Risk Assessment Via Multimodal Data Analysis Enabling Personalised Prevention Strategies Targeting MEnopausaL Women - Observational Study
Overview
CARAMEL is a project funded by the European Commission under the Horizon Europe programme. Its aim is to develop a personalized prevention approach based on state-of-the-art artificial intelligence models for cardiovascular risk stratification in women aged 40-60 years. These models are trained using large amounts of multi-source data and complemented by digital self-assessment and self-management tools. The CARAMEL consortium brings together a diverse group of 25 organizations, including technology companies and research centers, clinical institutions, as well as experts in ethics, law, and communication. The CARAMEL-OS study is an observational study aimed at prospectively completing the proposed personalized cardiovascular risk stratification model for women aged 40-60 years that will be developed during the earlier phases of the overall CARAMEL project (https://www.caramel-project.eu/). The study has a purely observational design, and patient stratification will not entail any clinical intervention. The data collected will be used to complete the design of the personalized stratification model, as well as to develop and validate the performance of the predictive models in an independent prospective cohort, distinct from the retrospective cohort initially used. The performance of the models developed using retrospective data will be assessed in terms of accuracy, discrimination, calibration, and other relevant metrics. In addition, the study will enable the development of new predictive models with short-term prediction horizons, incorporating additional variables that are not available retrospectively. The study population will be recruited in four European Union countries: Croatia, Spain (Andalusia and The Basque Country - Gipuzkoa), Greece and Lithuania; and in Colombia. A prospective cohort of 3,000 women aged 40-60 will be recruited, with each partner contributing 500 participants.
Detailed description
A prospective observational study involving 3,000 women across six clinical sites will be conducted to generate a comprehensive multi-source dataset for the development of cardiovascular disease (CVD) risk assessment models. In addition to socioeconomic, clinical, biochemical, and imaging data, the study will use novel non-invasive technologies to collect additional potentially relevant variables, aiming to improve understanding of female-specific cardiovascular risk factors and biological changes around menopause age. By refining the CARAMEL stratification scheme based on the most effective approaches, the project aims to provide innovative tools for personalized CVD prevention and risk stratification. This ambitious and integrative approach is expected to advance precision medicine in women's cardiovascular health, support clinical decision-making, and inform future preventive strategies at both individual and population levels. Central to these strategies is the development of the datApp - a mobile application designed to serve as a personalised companion for women throughout their menopausal transition.
Primary outcome measures
- Incidence of hypertension [Time frame: From enrollment to program completion, spanning 21-24 months depending on the enrollment date.]
- Incidence of dyslipidaemia [Time frame: From enrollment to program completion, lasting 21-24 months depending on the enrollment date.]
- Incidence of diabetes mellitus [Time frame: From enrollment to program completion, lasting 21-24 months depending on the enrollment date.]
- Incidence of cardiovascular disease [Time frame: From enrollment to program completion, spanning 21-24 months depending on the enrollment date.]
Secondary outcome measures (1)
- Mortality of cardiovascular events. [Time frame: From enrollment to program completion, spanning 21-24 months depending on the enrollment date.]
Eligibility criteria
Inclusion criteria
- Women 40 to 60 years of age, at recruitment.
- Ability to understand and complete the required informed consent for the study.
- Women who are covered by the corresponding healthcare system operating at each clinical site.
Exclusion criteria
- Severe comorbidity with less than 24 months life expectancy.
- Lack of basic digital skills to use or carry a smartphone and wearable devices.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Cohort
Study locations
Spain · 2 centers
- Biogipuzkoa Health Research Institute — San Sebastián
- Fundacion Para La Gestion de La Investigacion En Salud de Sevilla — Seville
Colombia · 1 center
- Keralty SAS — Bogotá
Croatia · 1 center
- Magdalena - Klinika Za Kardiovaskularne Bolesti Medicinskog Fakultetasveucilista J.J. Stro — Krapinske Toplice
Greece · 1 center
- Ethniko Kai Kapodistriako Panepistimio Athinon — Athens
Lithuania · 1 center
- Viesoji Istaiga Vilniaus Universiteto Ligonine Santaros Klinikos — Vilnius
Publications
- Mazzolai L, Teixido-Tura G, Lanzi S, Boc V, Bossone E, Brodmann M, Bura-Riviere A, De Backer J, Deglise S, Della Corte A, Heiss C, Kaluzna-Oleksy M, Kurpas D, McEniery CM, Mirault T, Pasquet AA, Pitcher A, Schaubroeck HAI, Schlager O, Sirnes PA, Sprynger MG, Stabile E, Steinbach F, Thielmann M, van Kimmenade RRJ, Venermo M, Rodriguez-Palomares JF; ESC Scientific Document Group. 2024 ESC Guidelines PMID 39210722
- Vrints C, Andreotti F, Koskinas KC, Rossello X, Adamo M, Ainslie J, Banning AP, Budaj A, Buechel RR, Chiariello GA, Chieffo A, Christodorescu RM, Deaton C, Doenst T, Jones HW, Kunadian V, Mehilli J, Milojevic M, Piek JJ, Pugliese F, Rubboli A, Semb AG, Senior R, Ten Berg JM, Van Belle E, Van Craenenbroeck EM, Vidal-Perez R, Winther S; ESC Scientific Document Group. 2024 ESC Guidelines for the mana PMID 39210710
- Thygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, White HD; Executive Group on behalf of the Joint European Society of Cardiology (ESC)/American College of Cardiology (ACC)/American Heart Association (AHA)/World Heart Federation (WHF) Task Force for the Universal Definition of Myocardial Infarction. Fourth Universal Definition of Myocardial Infarction (2018). J Am Coll Cardiol. 2018 PMID 30153967
- American Diabetes Association Professional Practice Committee. 1. Improving Care and Promoting Health in Populations: Standards of Care in Diabetes-2025. Diabetes Care. 2025 Jan 1;48(1 Suppl 1):S14-S26. doi: 10.2337/dc25-S001. PMID 39651974
- Cherla A, Kyriopoulos I, Pearcy P, Tsangalidou Z, Hajrulahovic H, Theodorakis P, Andersson CE, Mehra MR, Mossialos E. Trends in avoidable mortality from cardiovascular diseases in the European Union, 1995-2020: a retrospective secondary data analysis. Lancet Reg Health Eur. 2024 Sep 27;47:101079. doi: 10.1016/j.lanepe.2024.101079. eCollection 2024 Dec. PMID 39397877
- McCarthy CP, Bruno RM, McEvoy JW, Touyz RM. 2024 ESC Guidelines for the management of elevated blood pressure and hypertension: what is new in pharmacotherapy? Eur Heart J Cardiovasc Pharmacother. 2025 Feb 8;11(1):7-9. doi: 10.1093/ehjcvp/pvae084. No abstract available. PMID 39439212
- Rajput D, Wang WJ, Chen CC. Evaluation of a decided sample size in machine learning applications. BMC Bioinformatics. 2023 Feb 14;24(1):48. doi: 10.1186/s12859-023-05156-9. PMID 36788550
- Kouz K, Monge Garcia MI, Cerutti E, Lisanti I, Draisci G, Frassanito L, Sander M, Ali Akbari A, Frey UH, Grundmann CD, Davies SJ, Donati A, Ripolles-Melchor J, Garcia-Lopez D, Vojnar B, Gayat E, Noll E, Bramlage P, Saugel B. Intraoperative hypotension when using hypotension prediction index software during major noncardiac surgery: a European multicentre prospective observational registry (EU HYPR PMID 37588176
Identifiers
NCT: NCT07695376 · PI2025166 (PS)