ClinicalTrials.gg
RecruitingNCT05884840HELENAUpdated Dec 29, 2023

New Cardiovascular Risk Screening Strategy.

An interventional study of HELENA in Cardiovascular Prevention, Screening and Peripheral Artery Disease, sponsored by Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina. Recruiting at 1 site in Spain. Open to participants aged 50 Years to 74 Years. Per ClinicalTrials.gov, last updated 2023-12-29.

Sponsored by Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina · Not applicable, Interventional, and Prevention

From the registry’s dates

  • Primary completion was expected by Jun 2026, 5 months ago, but the record still lists the study as recruiting.
  • Started Nov 2023; still recruiting 2 years 11 months later.
Phase
Not applicable
Study type
Interventional
Enrollment
54,000
Allocation
Randomized
Ages
50 Years to 74 Years
Sex
All
01

Study 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.
02

Conditions studied

  • Cardiovascular Prevention
  • Screening
  • Peripheral Artery Disease
  • Arteriosclerosis
  • Asymptomatic
03

In context

Peripheral Arterial Disease

1,377 studies on the registry are indexed under Peripheral Arterial Disease; 275 are open to participants now.

This study's planned enrollment of 54,000 is above the median of 70 across 927 interventional studies indexed under Peripheral Arterial Disease.

Browse Peripheral Arterial Disease studies →

Lead sponsor

Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina is the lead sponsor of 161 studies on the registry; 21 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
50 Years to 74 Years
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

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

Exclusion Criteria:

  • Symptomatic PAD
  • Coronary disease
  • Stroke
  • Cardiac revascularization
05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
54,000 participants (estimated)

Study arms

  • Experimental
    Intervention group PAD screening program

    Patients aged 50-74 years free of any symptomatic or history of CVD and a Framingham-REGICOR risk ≥7%, will be candidates for PAD screening program using REASON's function predicative capacity

    Diagnostic Test: HELENA

  • No intervention
    Control group PAD screening program

    Patients aged 50-74 years free of any symptomatic or history of CVD will be candidates as a comparison group to calculate the cost-utility and reduction of CVD risk and events.

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.

06

What researchers measure

Primary outcomes

  1. Hard coronary heart disease (CHD)

    Myocardial infarction, cardiac revascularization, or coronary death

    Time frame: 3 years

  2. Major adverse cardiovascular event (MACE)

    A composite of hard CHD (myocardial infarction, cardiac revascularization, or coronary death) and stroke (fatal and nonfatal ischemic stroke)

    Time frame: 3 years

  3. All-cause mortality

    Time frame: 3 years

  4. Tabaco consumption (CVD risk factors improvement assessment)

    Smoker, ex-smoker or non-smoker

    Time frame: 3 years

  5. Lipid profile (CVD risk factors improvement assessment)

    Total cholesterol (mg/dl), LDL (mg/dl), HDL (mg/dl), Triglycerides (mg/dl)

    Time frame: 3 years

  6. Systolic and diastolic pressure (CVD risk factors improvement assessment)

    mm Hg

    Time frame: 3 years

  7. Weight (CVD risk factors improvement assessment)

    kg

    Time frame: 3 years

  8. Height (CVD risk factors improvement assessment)

    m

    Time frame: 3 years

  9. BMI (CVD risk factors improvement assessment)

    (kg/m2) Will be calculated dividing the weight in kilograms by their height in metres squared

    Time frame: 3 years

  10. Glycaemia (CVD risk factors improvement assessment)

    Fasting blood sugar (mg/dl)

    Time frame: 3 years

  11. Glycated haemoglobin (CVD risk factors improvement assessment)

    (in DM patients) glycosylated hemoglobin in the blood (mg/dl) or percentage (%)

    Time frame: 3 years

  12. Creatinine (CVD risk factors improvement assessment)

    mg/dL

    Time frame: 3 years

  13. Proteinuria (CVD risk factors improvement assessment)

    mg/dL protein in urine

    Time frame: 3 years

  14. Albumin-to-creatinine ratio (ACR) (CVD risk factors improvement assessment)

    ACR (mg/g) will be calculated by by dividing mg of proteinuria (albumine) by g of creatinine.

    Time frame: 3 years

  15. Glomerular filtrate rate (CVD risk factors improvement assessment)

    Levels of creatinine in milliliters of cleansed blood per minute per body surface (mL/min/1.73m2).

    Time frame: 3 years

Secondary outcomes

  1. Coronary heart disease

    A composite of angina and hard CHD

    Time frame: 3 years

  2. Cerebrovascular disease

    A composite of stroke (fatal and nonfatal ischemic stroke) and transient ischemic attack

    Time frame: 3 years

  3. Cardiovascular disease

    a composite of MACE, angina and transient ischemic attack

    Time frame: 3 years

  4. Lipid lowering medication Adverse effects

    1) Short-term effects: Muscular and hepatic alterations, and 2) long-term effects: Diabetes and cancer

    Time frame: 3 years

07

Study locations

1 of 1 sites recruiting
08

References and documents

Publications

  • Ministerio de Sanidad SS e I. Indicadores de Salud 2020 Evolución de los indicadores del estado de salud en España y su magnitud en el contexto de la Unión Europea. Madrid; 2020.
  • Institute for Health Metrics and Evaluation. Global Burden of Disease Results Tool, Global Health Data Exchange. 2017
  • Wilkins E, et al. European Cardiovascular Disease Statistics. European Heart Network, editor. Brussels; 2017
  • Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Back M, Benetos A, Biffi A, Boavida JM, Capodanno D, Cosyns B, Crawford C, Davos CH, Desormais I, Di Angelantonio E, Franco OH, Halvorsen S, Hobbs FDR, Hollander M, Jankowska EA, Michal M, Sacco S, Sattar N, Tokgozoglu L, Tonstad S, Tsioufis KP, van Dis I, van Gelder IC, Wanner C, Williams B; ESC National Cardiac Societies; ESC Scientific Document Group. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021 Sep 7;42(34):3227-3337. doi: 10.1093/eurheartj/ehab484. No abstract available. Erratum In: Eur Heart J. 2022 Nov 7;43(42):4468. doi: 10.1093/eurheartj/ehac458. PubMed 34458905 ↗
  • Comin E, Solanas P, Cabezas C, Subirana I, Ramos R, Gene-Badia J, Cordon F, Grau M, Cabre-Vila JJ, Marrugat J. [Estimating cardiovascular risk in Spain using different algorithms]. Rev Esp Cardiol. 2007 Jul;60(7):693-702. Spanish. PubMed 17663853 ↗
  • Morrow DA, de Lemos JA. Benchmarks for the assessment of novel cardiovascular biomarkers. Circulation. 2007 Feb 27;115(8):949-52. doi: 10.1161/CIRCULATIONAHA.106.683110. No abstract available. PubMed 17325253 ↗
  • Grewal J, Anand S, Islam S, Lonn E; SHARE and SHARE-AP Investigators. Prevalence and predictors of subclinical atherosclerosis among asymptomatic "low risk" individuals in a multiethnic population. Atherosclerosis. 2008 Mar;197(1):435-42. doi: 10.1016/j.atherosclerosis.2007.06.020. Epub 2007 Aug 6. PubMed 17675040 ↗
  • Greenland P, Abrams J, Aurigemma GP, Bond MG, Clark LT, Criqui MH, Crouse JR 3rd, Friedman L, Fuster V, Herrington DM, Kuller LH, Ridker PM, Roberts WC, Stanford W, Stone N, Swan HJ, Taubert KA, Wexler L. Prevention Conference V: Beyond secondary prevention: identifying the high-risk patient for primary prevention: noninvasive tests of atherosclerotic burden: Writing Group III. Circulation. 2000 Jan 4;101(1):E16-22. doi: 10.1161/01.cir.101.1.e16. No abstract available. PubMed 10618318 ↗
  • McDermott MM, Greenland P, Liu K, Guralnik JM, Celic L, Criqui MH, Chan C, Martin GJ, Schneider J, Pearce WH, Taylor LM, Clark E. The ankle brachial index is associated with leg function and physical activity: the Walking and Leg Circulation Study. Ann Intern Med. 2002 Jun 18;136(12):873-83. doi: 10.7326/0003-4819-136-12-200206180-00008. Erratum In: Ann Intern Med. 2003 Aug 19;139(4):306. PubMed 12069561 ↗
  • Ramos R, Quesada M, Solanas P, Subirana I, Sala J, Vila J, Masia R, Cerezo C, Elosua R, Grau M, Cordon F, Juvinya D, Fito M, Isabel Covas M, Clara A, Angel Munoz M, Marrugat J; REGICOR Investigators. Prevalence of symptomatic and asymptomatic peripheral arterial disease and the value of the ankle-brachial index to stratify cardiovascular risk. Eur J Vasc Endovasc Surg. 2009 Sep;38(3):305-11. doi: 10.1016/j.ejvs.2009.04.013. Epub 2009 Jun 10. PubMed 19515589 ↗
  • Heald CL, Fowkes FG, Murray GD, Price JF; Ankle Brachial Index Collaboration. Risk of mortality and cardiovascular disease associated with the ankle-brachial index: Systematic review. Atherosclerosis. 2006 Nov;189(1):61-9. doi: 10.1016/j.atherosclerosis.2006.03.011. Epub 2006 Apr 18. PubMed 16620828 ↗
  • Ankle Brachial Index Collaboration; Fowkes FG, Murray GD, Butcher I, Heald CL, Lee RJ, Chambless LE, Folsom AR, Hirsch AT, Dramaix M, deBacker G, Wautrecht JC, Kornitzer M, Newman AB, Cushman M, Sutton-Tyrrell K, Fowkes FG, Lee AJ, Price JF, d'Agostino RB, Murabito JM, Norman PE, Jamrozik K, Curb JD, Masaki KH, Rodriguez BL, Dekker JM, Bouter LM, Heine RJ, Nijpels G, Stehouwer CD, Ferrucci L, McDermott MM, Stoffers HE, Hooi JD, Knottnerus JA, Ogren M, Hedblad B, Witteman JC, Breteler MM, Hunink MG, Hofman A, Criqui MH, Langer RD, Fronek A, Hiatt WR, Hamman R, Resnick HE, Guralnik J, McDermott MM. Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a meta-analysis. JAMA. 2008 Jul 9;300(2):197-208. doi: 10.1001/jama.300.2.197. PubMed 18612117 ↗
  • Espinola-Klein C, Rupprecht HJ, Bickel C, Lackner K, Savvidis S, Messow CM, Munzel T, Blankenberg S; AtheroGene Investigators. Different calculations of ankle-brachial index and their impact on cardiovascular risk prediction. Circulation. 2008 Aug 26;118(9):961-7. doi: 10.1161/CIRCULATIONAHA.107.763227. Epub 2008 Aug 12. PubMed 18697822 ↗
  • US Preventive Services Task Force; Curry SJ, Krist AH, Owens DK, Barry MJ, Caughey AB, Davidson KW, Doubeni CA, Epling JW Jr, Kemper AR, Kubik M, Landefeld CS, Mangione CM, Silverstein M, Simon MA, Tseng CW, Wong JB. Screening for Peripheral Artery Disease and Cardiovascular Disease Risk Assessment With the Ankle-Brachial Index: US Preventive Services Task Force Recommendation Statement. JAMA. 2018 Jul 10;320(2):177-183. doi: 10.1001/jama.2018.8357. PubMed 29998344 ↗
  • Norgren L, Hiatt WR, Dormandy JA, Nehler MR, Harris KA, Fowkes FG; TASC II Working Group; Bell K, Caporusso J, Durand-Zaleski I, Komori K, Lammer J, Liapis C, Novo S, Razavi M, Robbs J, Schaper N, Shigematsu H, Sapoval M, White C, White J, Clement D, Creager M, Jaff M, Mohler E 3rd, Rutherford RB, Sheehan P, Sillesen H, Rosenfield K. Inter-Society Consensus for the Management of Peripheral Arterial Disease (TASC II). Eur J Vasc Endovasc Surg. 2007;33 Suppl 1:S1-75. doi: 10.1016/j.ejvs.2006.09.024. Epub 2006 Nov 29. No abstract available. PubMed 17140820 ↗
  • Ramos R, Baena-Diez JM, Quesada M, Solanas P, Subirana I, Sala J, Alzamora M, Fores R, Masia R, Elosua R, Grau M, Cordon F, Pera G, Rigo F, Marti R, Ponjoan A, Cerezo C, Brugada R, Marrugat J. Derivation and validation of REASON: a risk score identifying candidates to screen for peripheral arterial disease using ankle brachial index. Atherosclerosis. 2011 Feb;214(2):474-9. doi: 10.1016/j.atherosclerosis.2010.11.015. Epub 2010 Nov 19. PubMed 21167488 ↗
  • Perlstein TS, Creager MA. The ankle-brachial index as a biomarker of cardiovascular risk: it's not just about the legs. Circulation. 2009 Nov 24;120(21):2033-5. doi: 10.1161/CIRCULATIONAHA.109.907238. Epub 2009 Nov 9. No abstract available. PubMed 19901185 ↗
  • Ramos R, Garcia-Gil M, Comas-Cufi M, Quesada M, Marrugat J, Elosua R, Sala J, Grau M, Marti R, Ponjoan A, Alves-Cabratosa L, Blanch J, Bolibar B. Statins for Prevention of Cardiovascular Events in a Low-Risk Population With Low Ankle Brachial Index. J Am Coll Cardiol. 2016 Feb 16;67(6):630-640. doi: 10.1016/j.jacc.2015.11.052. PubMed 26868687 ↗
  • Lindholt JS, Sogaard R. Population screening and intervention for vascular disease in Danish men (VIVA): a randomised controlled trial. Lancet. 2017 Nov 18;390(10109):2256-2265. doi: 10.1016/S0140-6736(17)32250-X. Epub 2017 Aug 28. PubMed 28859943 ↗
  • Diederichsen AC, Rasmussen LM, Sogaard R, Lambrechtsen J, Steffensen FH, Frost L, Egstrup K, Urbonaviciene G, Busk M, Olsen MH, Mickley H, Hallas J, Lindholt JS. The Danish Cardiovascular Screening Trial (DANCAVAS): study protocol for a randomized controlled trial. Trials. 2015 Dec 5;16:554. doi: 10.1186/s13063-015-1082-6. PubMed 26637993 ↗
  • Betriu A, Farras C, Abajo M, Martinez-Alonso M, Arroyo D, Barbe F, Buti M, Lecube A, Portero M, Purroy F, Torres G, Valdivielso JM, Fernandez E. Randomised intervention study to assess the prevalence of subclinical vascular disease and hidden kidney disease and its impact on morbidity and mortality: The ILERVAS project. Nefrologia. 2016 Jul-Aug;36(4):389-96. doi: 10.1016/j.nefro.2016.02.008. Epub 2016 Apr 1. English, Spanish. PubMed 27044887 ↗
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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Dec 29, 2023, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT05884840
Collaborators
Hospital del Mar Research Institute (IMIM), Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta, Institut Català de la Salut, Biocruces Bizkaia Health Research Institute
Responsible party
Sponsor
First posted
Jun 1, 2023
Start date
Nov 20, 2023
Primary completion
Jun 2026 (estimated)
Completion
Jun 2026 (estimated)
Last update
Dec 29, 2023

Study contacts

Rafel Ramos Blanes, MD, PhD
Contact
rramos.girona.ics@gencat.cat
+34 972 48 79 68
Rafel Ramos Blanes, MD, PhD
principal investigator · Unidad de Investigación en Atención Primaria de Girona, IDIAP Jordi Gol

Oversight

FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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