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New Cardiovascular Risk Screening Strategy.

Health Program for prEvention of cardiovascuLar disEases Based on a Risk screeNing Strategy With Ankle-brachial Index.

Status
Recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05884840
Acronym
HELENA
Enrollment
54000
Registered
2023-06-01
Start date
2023-11-20
Completion date
2026-06-30
Last updated
2023-12-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Arteriosclerosis, Asymptomatic, Cardiovascular Prevention, Peripheral Artery Disease, Screening

Brief summary

Mortality due to cardiovascular disease (CVD) in Spain accounted for 29% of all deaths (32% in women and 26% in men) in 2017. Out of those, 67% were related to a coronary or a cerebrovascular disease . A key strategy in primary prevention of CVD is to use risk functions to individualize preventive interventions for each patient. The current CV risk-screening program in some regions of Spain, is based using an adapted Framingham scale, REGICOR's risk function, which is integrated in the primary care electronic health record. This risk function predicts the probability within 10 years of developing a coronary event. However, this function fails to identify patients that fall into low- or intermediate-risk level, and might develop a CV event in the up following 10 years. Ankle-brachial index (ABI) is a simple, non-invasive and economic technique, which allows detecting peripheral arterial disease (PAD), and gives independent risk function information compared to other coronary risk functions. Even tough, between 13-27% of middle age population have an ABI ≤ 9, around 50-89% of them do not exhibit any symptoms. However, they hold higher mortality risk and CV events. Current clinical guidelines for PAD screening, have a limited level of evidence, and only recommend using ABI on patients aged 50-70, who have diabetes or are smokers, and patients older than 70 years old. A new risk function, REASON, to assess CVD risk has been designed. This model has proven to improve predictive capacity of holding an ABI ≤ 0.9 on those patients aged 50-74 that are apparently free of CVD. Therefore, a strategy that combines the current CV risk estimation using REGICOR, and the prediction capacity of pathologic ABI with REASON, would allow detecting high-risk patients with a PAD screening program. It is possible that patients, who hold an ABI ≤ 0.9, even if being asymptomatic, will adopt physician's recommendations on healthy life habits and preventive treatment. The aims of this study are: * To assess the effectiveness and cost-utility of adding a screening program with ABI to the current strategy of CV risk detection to reduce the incidence of CVD and mortality from all causes in the population aged 50 to 74. * To assess the effectiveness of adding a screening program with ABI to the current strategy of CV risk detection to improve cardiovascular risk factors in the population aged 50 to 74.

Interventions

DIAGNOSTIC_TESTHELENA

The current CV risk screening program in based using the REGICOR risk function, which is integrated in the primary care electronic health record. This risk function predicts the probability within 10 years of developing a coronary event. Those who are categorized as high risk, obtaining a 10% of probability, are candidates of receiving lipid lowering drugs and recommendations on healthy life habits. What this intervention suggests is that, besides the REGICOR estimation, the electronic health records will also incorporate a new CV risk function, REASON. The model predicts the risk of holding a pathologic ABI score, in people aged 50-74 years old who are apparently free of CV. Patients who obtain a score ≥ 7 will undergo a PAD screening program with ABI test. If the value of the test is ≤0.9, the REGICOR, physicians will recommend indications of the Health Catalan Institute's CV and lipid Guidelines to the patients.

Sponsors

Hospital del Mar Research Institute (IMIM)
CollaboratorOTHER
Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
CollaboratorOTHER
Institut Català de la Salut
CollaboratorOTHER
Biocruces Bizkaia Health Research Institute
CollaboratorOTHER_GOV
Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
NONE

Intervention model description

This study will be conducted as a clustered randomized pragmatic clinical trial (CRT) in primary care practice. During the period of two years (2023-2025), randomization of the eight Health Regions (274 primary care centres) in Catalonia will take place. The current strategy, in Catalonia, for cardiovascular risk screening is based on risk assessment using Framingham-REGICOR risk function. In the intervention group, a screening program with ABI will be added to all 50-74-year-old individuals with Framingham-REGICOR risk ≥7% and high probability of having ABI≤0.9. The probability of having ABI≤0.9 will be estimated using the REASON function and will be defined as a probability ≥7%. People that are classified as ABI≤0.9 high-risk, will undergo a PAD screening program using ABI test. If the result of the ABI is equal and lower than 0.9, indications of the Health Catalan Institute's CV and lipid guidelines will be recommended by physicians to the patients.

Eligibility

Sex/Gender
ALL
Age
50 Years to 74 Years
Healthy volunteers
No

Inclusion criteria

* Patients aged 50 to 74, which are free or do not have previous history of CVD. Patients that hold a REGICOR CV risk score ≥7, and REASON risk core ≥7, during a routine primary care visit

Exclusion criteria

* Symptomatic PAD * Coronary disease * Stroke * Cardiac revascularization

Design outcomes

Primary

MeasureTime frameDescription
Glomerular filtrate rate (CVD risk factors improvement assessment)3 yearsLevels of creatinine in milliliters of cleansed blood per minute per body surface (mL/min/1.73m2).
Glycated haemoglobin (CVD risk factors improvement assessment)3 years(in DM patients) glycosylated hemoglobin in the blood (mg/dl) or percentage (%)
Creatinine (CVD risk factors improvement assessment)3 yearsmg/dL
Proteinuria (CVD risk factors improvement assessment)3 yearsmg/dL protein in urine
Albumin-to-creatinine ratio (ACR) (CVD risk factors improvement assessment)3 yearsACR (mg/g) will be calculated by by dividing mg of proteinuria (albumine) by g of creatinine.
Hard coronary heart disease (CHD)3 yearsMyocardial infarction, cardiac revascularization, or coronary death
Major adverse cardiovascular event (MACE)3 yearsA composite of hard CHD (myocardial infarction, cardiac revascularization, or coronary death) and stroke (fatal and nonfatal ischemic stroke)
All-cause mortality3 years
Tabaco consumption (CVD risk factors improvement assessment)3 yearsSmoker, ex-smoker or non-smoker
Lipid profile (CVD risk factors improvement assessment)3 yearsTotal cholesterol (mg/dl), LDL (mg/dl), HDL (mg/dl), Triglycerides (mg/dl)
Systolic and diastolic pressure (CVD risk factors improvement assessment)3 yearsmm Hg
Weight (CVD risk factors improvement assessment)3 yearskg
Height (CVD risk factors improvement assessment)3 yearsm
BMI (CVD risk factors improvement assessment)3 years(kg/m2) Will be calculated dividing the weight in kilograms by their height in metres squared
Glycaemia (CVD risk factors improvement assessment)3 yearsFasting blood sugar (mg/dl)

Secondary

MeasureTime frameDescription
Cerebrovascular disease3 yearsA composite of stroke (fatal and nonfatal ischemic stroke) and transient ischemic attack
Cardiovascular disease3 yearsa composite of MACE, angina and transient ischemic attack
Lipid lowering medication Adverse effects3 years1\) Short-term effects: Muscular and hepatic alterations, and 2) long-term effects: Diabetes and cancer
Coronary heart disease3 yearsA composite of angina and hard CHD

Countries

Spain

Contacts

Primary ContactRafel Ramos Blanes, MD, PhD
rramos.girona.ics@gencat.cat+34 972 48 79 68

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026