Italian Digital Primary Cardiovascular Prevention Study

Study Overview
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Brief Summary
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The CV-PREVITAL study is a randomised clinical trial (RCT) controlled versus usual-care designed to compare the effectiveness of a mobile health (mHealth) intervention with that of usual care in reducing specific cardiovascular (CV) risk factors (in the short term) and the occurrence of vascular events (in the long term). Promoted by the Italian Network of Cardiology (ICN, a cardiovascular research network promoted by the Italian Ministry of Health), in collaboration with the Consorzio Sanità (Co.S., an Italian consortium of general practitioners), CV-PREVITAL aims to develop an innovative model of cardiovascular primary prevention and to validate it in a very large sample of subjects and in 'real life' conditions.

Detailed Description
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CV-PREVITAL is an RCT investigating whether an mHealth application (App) provided on top of usual care, can improve lifestyle habits and CV risk factor control in the short-term, and the incidence of major CV events in the long- term. Participants undergo two clinical visits, the first at baseline and the second after 12 months. During these visits, total cholesterol, HDL, LDL, triglyceride, HbA1c, blood pressure, heart rate, BMI and waist circumference are measured. In addition, using questionnaires provided digitally, participants self-report data on the following topics: adherence to the Mediterranean diet, salt intake, alcohol consumption, physical activity, current and previous smoking history, psychosocial profile, and sleep quality. Demographic information, including education, socio-economic status and ethnic origin are also obtained at baseline. Subjects in the intervention group also receive the credentials to download the App, which contains educational information on cardiovascular risk factors, diet, physical activity, lifestyle and psycho-behavioral aspects. Using ad hoc designed algorithms, the App delivers personalized prevention programs based on periodic messages providing advice, motivational reminders and support to improve lifestyle and risk factor control. When at baseline high levels of blood pressure, blood glucose or cholesterol are detected, the App support the participant in self-monitoring the clinical changes of such variables during the follow up. The efficacy of the intervention is evaluated at the12th month using a cardiovascular risk score developed ad hoc in an Italian population (Modified Moli-Sani Score). The ability of the intervention to maintain its effect over time and its effectiveness in improving clinical outcomes are assessed at the 7th year of follow-up. The cost-effectiveness of the intervention is also evaluated at the 7th year. The study envisages the recruitment of 82,800 participants (aged ≥45y) nationwide. Of these, 50,000 are selected among those who daily access the GPs ambulatories associated to the Co.S. consortium. In order to assess whether the scheduled mHealth intervention can be effective also in settings different from the primary care, several specific cohorts in primary prevention are also enrolled by specialized units belonging to the recruiting IRCCSs. These cohorts include 32,800 subjects in total. Specifically, the UO-1 (IRCCS Cardiologico Monzino in Milan) enrolls 5,000 participants selected among citizens attending to community pharmacies; the UO-2 (IRCCS Auxologico in Milan) enrolls 5,000 subjects, 1,500 of which belonging to the Centre for Sleep Medicine; the UO-3 (IRCCS Humanitas in Milan) enrolls 2,000 subjects attending the institution; the UO-4 (IRCCS Mario Negri in Milan) does not recruit any subject but provides scientific and organizational support for the enrolment carried out by Co.S.; the UO-5 (IRCCS MultiMedica in Milan) enrolls 1,000 subjects with diabetes and 2,000 subjects from the general population; the UO-6 (IRCCS Neuromed in Pozzilli) enrols 10,000 subjects from the Neuromed clinical research centres; the UO-7 (IRCCS San Donato in Milan) enrolls 1,000 subjects selected among its own employees; the UO-8 (IRCCS Maugeri in Pavia) enrolls 1,000 subjects selected among its own employees; the UO-9 (IRCCS ISMETT, Mediterranean Institute for Transplantation and Advanced Specialized Therapies, in Palermo) enrolls 150 subjects who undergoes a physical activity program; the UO-10 (IRCCS San Martino in Genoa) enrolls 2,000 male subjects from the Municipality of Genoa; the UO-11 (IRCCS Ca' Granda of Milan) enrolls 2,000 blood donors afferent to its own Department of Transfusion Medicine and Hematology (DMTE); the UO-12 (IRCCS Gemelli in Rome) enrolls 1,000 subjects attending to the outpatient clinics of the Non-Invasive Cardiology Diagnostic Unit, of the Centre for Hypertension, and of the Centre for Endocrine and Metabolic Diseases; the UO-13 (IRCCS San Matteo in Pavia) enrolls 500 subjects selected among asymptomatic relatives of patients attending to the Policlinico San Matteo for cardiology reasons; the UO-14 (IRCCS San Raffaele in Rome) enrolls 150 subjects selected among its own employees. Baseline data of the 82,800 participants and 1- and 7-years outcomes are also used to develop and validate a new algorithm for cardiovascular risk estimation. The new algorithm is developed by identifying among alcohol intake (as assessed by PREDIMED questionnaire), salt intake (as assessed by MiniSal questionnaire), perceived stress (as assessed by perceived stress scale (PSS), anxiety and depression (as assessed by Patient Health Questionnaire 4; PHQ 4), Locus of control (as assessed by Multidimensional Health Locus of Control scale, MHLCS), General Self Efficacy (as assessed by General Self Efficacy Scale; GSE), Risk propensity (as assessed by Risk Propensity Scale; RPS), and sleep quality (as assessed by Pittsburgh Sleep Quality Index) those variables that significantly improve the predictive power of the modified Moli-Sani algorithm. The CV-PREVITAL trial also envisages a series of ancillary studies that are conducted by the various IRCCSs on the subjects already participating in the main study. Each ancillary study has its own protocol and aims, and foresees the evaluation of the role of further biomarkers relevant in the assessment of cardiovascular risk. The sub-study aims, outcomes information and time frame are described below. Baseline data of many ancillary studies are used to identify conventional and emerging determinants of specific cardiometabolic diseases. Specifically: a) the IRCCS Monzino analyses with multivariable approaches determinants and factors predisposing to diabetes status as assessed by Framingham diabetes score; b) the IRCCS Auxologico will apply additional elements for risk stratification including biomarkers high sensitive C-reactive protein (hs-CRP), Troponin I, N-terminal pro-brain natriuretic peptide (NT-proBNP), as well as 24 h ABPM (Ambulatory Blood Pressure Monitoring) derived variables; c) the IRCCS Humanitas analyses the frequency of genetic polymorphisms related to severe coronary calcification of its own cohort to identify genetic determinants of severe coronary calcification; d) the IRCCS MultiMedica analyses with multivariable approaches anthropometric (e.g. weight, height, BMI), biochemical data (e.g. lipid profile) and specific genetic disorders (e.g. presence of causative mutations in known genes involved in dyslipidemia) to identify determinants predisposing to dyslipidemia, hypertension and diabetes; e) the IRCCS Neuromed analyses with multivariable approaches determinants of dietary changes in the CV-PREVITAL Neuromed sub-study cohort; f) the Istituti Clinici Scientifici Maugeri IRCCS analyses baseline data of its own cohort with multivariable approaches to identify determinants of organ damage such as coronary silent ischemia, ankle brachial index, coronary calcium score and carotid ultrasound as well as Genetic and epigenetic (DNA and RNA) and other chemical determinants and factors predisposing to atherosclerotic diseases; g) the IRCCS Ca' Granda performs a 7 years validation of new monogenic and polygenic cardiovascular risk scores in its own primary prevention cohort. To this aim the study cohort is genotyped with GWAS and Whole Exome Sequencing (WES) for genetic factors influencing intracellular lipid handling (PNPLA3 I148M, TM6SF2 E167K, GCKR P446L, MBOAT7). Epigenetic variables indicated in the literature as early predictors of cardiovascular injury and cardiovascular events are also investigated. In addition to the characterization of genetic variants in known associated genes, the genomic characterization will allow the validation of candidate risk variants in genes reported to influence cardiovascular damage, the identification of potentially new candidate variants, and the calculation of polygenic cardiovascular risk scores and of their possible application to disease risk stratification in the Italian population; h) the IRCCS San Matteo develops new monogenic and polygenic scores and validates existing scores for the risk assessment of developing diabetes, hypertension and hypercholesterolemia. Beyond the specific aims of the single sub-studies, a relevant goal common to all sub-studies is the collection of biological samples for the multisite biobank of the ICN. The full list of approving body and approval number/ID of CV-PREVITAL studies is reported below. Parent study: Approval Number: R1256/20-CCM 1319; Board Name: Comitato Etico degli IRCCS Istituto Europeo di Oncologia e Centro Cardiologico Monzino. Ancillary studies of Monzino: Approval Number: R1579/21-CCM 1677 and R1617/22-CCM 1723; Board Name: Comitato Etico degli IRCCS Istituto Europeo di Oncologia e Centro Cardiologico Monzino. Ancillary study of Istituto Auxologico Italiano: Approval Number: 2022_03_08_06; Board Name: Comitato Etico dell'IRCCS Istituto Auxologico Italiano. Ancillary study of Humanitas: Approval Number: 2860; Board Name: Comitato Etico Indipendente dell'Istituto Clinico Humanitas. Ancillary study of Multimedica: Approval Number: MM: 472.2021; Board Name: Comitato Etico IRCCS Multimedica - Sezione del Comitato Etico Centrale IRCCS Lombardia. Ancillary study of Neuromed: Approval: Session of 28/09/2020; Board Name: Comitato Etico dell'Istituto Neurologico Mediterraneo Neuromed. Ancillary study of San Donato: Approval Number: 197/INT/2021; Board Name: Comitato Etico IRCCS Ospedale San Raffaele. Ancillary study of Maugeri: Approval Number: 2575 CE; Board Name: Comitato Etico degli Istituti Clinici Scientifici Maugeri. Ancillary study of ISMETT: Approval Number: IRRB/16/22; Board Name: Comitato Etico IRCCS Sicilia. Ancillary study of San Martino: Approval Number: 173/2021; Board Name: Comitato Etico Regionale della Liguria. Ancillary study of Ca' Granda: Approval Number: 887_2020; Board Name: Comitato Etico Milano Area 2. Ancillary study of Gemelli: Approval Number: 3614; Board Name: Comitato Etico della Fondazione Policlinico Universitario A. Gemelli IRCCS - Università Cattolica del Sacro Cuore. Ancillary study of San Matteo: Approval Number: 2022-3.11/91 and 2022-3.11/493; Board Name: Comitato Etico Pavia. Ancillary studiy of San Raffaele Roma: Approval Number: 21/21; Board Name: Comitato Etico IRCCS San Raffale Roma.

Official Title
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Digital Strategies in Primary Cardiovascular Prevention in the Italian Population

Conditions
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Healthy Population

Intervention / Treatment
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* Other: Mobile health application


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Subjects aged ≥ 45 years Have given their consent to participate in the study Subjects who have a smartphone Exclusion Criteria: Current or previous cardiovascular disease (personal history of myocardial infarction, angina pectoris, arterial revascularization procedures, stroke, TIA, peripheral artery disease) Psychiatric disorders Participation in other clinical trials

Ages Eligible for Study
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Minimum Age: 45 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Prevention
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Patients will be randomized in two parallel groups: intervention group and usual care. In the setting of general medicine, the procedure randomises the general practitioners (GPs) assuring that in each recruiting centre the number of GPs assigned to the control group (usual care) is balanced with that assigned to the intervention group. In the setting of community pharmacies, the procedure randomises the pharmacies assuring that in each geographic area the number of pharmacies assigned to the control group and is balanced with that assigned to the intervention group. In the setting of IRCCS the procedure directly randomises the patients.
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| No Intervention: Control group<br>Subjects monitored following usual-care. | |
| Experimental: Intervention group<br>Subjects in the intervention group, in addition to usual-care, will download a mHealth App that contains educational information promoting healthy lifestyle behaviours. The participant will be also able to self-monitor his/her clinical status regarding hypertension, diabetes or hypercholesterolemia. | Other: Mobile health application<br>* The mHealth app delivers a personalized support program of digital health. Specifically, using ad hoc designed algorithms which uses the data self-reported by the subject and/or collected by the recruiter at baseline, the App delivers periodic messages with advice, motivational reminders and support to improve lifestyle habits and risk factor control.<br>* Other names: mHealth app;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Cardiovascular risk as assessed by Modified Moli-Sani risk score in the Italian population | A score (modified Moli-Sani Risk Score) developed in the Italian population is used to analyze the efficacy of the intervention at 12 months. The risk score includes of blood pressure, HDL, LDL, triglyceride, blood glucose, overweight, physical activity, adhesion to Mediterranean diet and cigarette smoking. The modified Moli-Sani Risk Score may range from 0 to 100 and higher scores means higher risk. A 10% improvement in score between the baseline and final visit in the intervention group compared with the control group is assumed as indicator of intervention effectiveness. | 12 months | 
| Long-term CV clinical outcome at 7 years follow-up | Incidence of a composite outcome including myocardial infarction (MI), stroke, transient ischemic attack (TIA), peripheral artery disease or CV death. In case of multiple vascular events only the first is used in the analyses of composite outcome, whereas the specific outcome (e.g. MI or stroke) is used when the sub-analyses focused on cardio- or cerebrovascular events are run. | 7 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Change of a combined endpoint including hypertension, diabetes, hypercholesterolemia | For each individual subject, the combined end-point will be calculated, at baseline and at month 12, as the number of variables out of target (according to last European Society of Cardiology guidelines), among blood pressure, HbA1c and blood cholesterol; therefore, its value will range between 0 and 3. The difference in the combined end-point between month 12 and baseline will be compared, between the two experimental groups, using Wilcoxon rank-sum test. | 12 months | 
| Systolic and diastolic blood pressure (mmHg) | Comparison of the mean change from baseline in blood pressure in the two experimental groups. | 12 months | 
| HDL-C, LDL-C, and triglycerides (mg/dL) | Comparison of the mean change from baseline in blood lipids in the two experimental groups. | 12 months | 
| HbA1c (%) | Comparison of the mean change from baseline in HbA1c in the two experimental groups. | 12 months | 
| Body weight (kg) | Comparison of the mean change from baseline in body weight in the two experimental groups. | 12 months | 
| Physical activity (IPAQ questionnaire) | Comparison of the mean change from baseline in levels of physical activity as assessed by the short version (9 items) of the IPAQ (International Physical Activity Questionnaire) in the two experimental groups. | 12 months | 
| Mediterranean diet adherence (PREDIMED questionnaire) | Comparison of the mean change from baseline in adherence to Mediterranean diet as assessed by PREDIMED (Prevention with Mediterranean Diet) questionnaire in the two experimental groups. The PREDIMED score is a 14-item Mediterranean Diet adherence screener. Adherence is stratified in three categories: 1) low adherence (calculated score ≤5) 2) intermediate adherence (calculated score from 6 to 9), 3) high adherence (calculated score ≥10). | 12 months | 
| Mediterranean diet adherence (Moli-Sani questionnaire) | Comparison of the mean change from baseline in adherence to Mediterranean diet as assessed by the Moli-Sani study questionnaire in the two experimental groups. The Moli-Sani Mediterranean diet adherence score may range from 0 to 21, the latter reflecting the maximal adherence to Mediterranean diet. | 12 months | 
| Smoking status | Comparison of the mean change from baseline in cigarette smoking quantified by pack-years (number of packs of cigarettes smoked per day by the number of years the person has smoked) in the two experimental groups. | 12 months | 
| Alcohol intake | Comparison of the mean change from baseline in alcohol intake as assessed by PREDIMED (''Prevención con dieta mediterránea'') questionnaire in the two experimental groups. | 12 months | 
| Salt intake (MiniSal questionnaire) | Comparison of the mean change from baseline in salt intake as assessed by MiniSal questioner in the two experimental groups. The score may range from 0 to 11, the latter reflecting the maximal salt intake. | 12 months | 
| Stress (Perceived Stress Scale; PSS) | Comparison of the mean change from baseline in perceived stress as assessed by PSS (Perceived Stress Scale) in the two experimental groups. The PSS scale may range from 0 to 40 and higher values means higher perceived Stress. | 12 months | 
| Psychological distress (PHQ 4 questionnaire) | Comparison of the mean change from baseline in psychological distress as assessed by Patient Health Questionnaire-4 (PHQ-4) in the two experimental groups. The psychological distress PHQ-4 questionnaire may range from 0 to 12 and higher values means higher presence of the disorder. | 12 months | 
| Anxiety (PHQ 4 questionnaire) | Comparison of the mean change from baseline in anxiety as assessed by Patient Health Questionnaire-4 (PHQ-4) in the two experimental groups. The Anxiety PHQ-4 questionnaire may range from 0 to 6 and higher values means higher presence of the disorder. | 12 months | 
| Depression (PHQ 4 questionnaire) | Comparison of the mean change from baseline in depression as assessed by Patient Health Questionnaire-4 (PHQ-4) in the two experimental groups. The Depression PHQ-4 questionnaire may range from 0 to 6 and higher values means higher presence of the disorder. | 12 months | 
| Multidimensional Health Locus of Control Scale (MHLCS) - Internality | Comparison of the mean change from baseline in locus of control as assessed by Multidimensional Health Locus of Control Scale (MHLCS)-Internality in the two experimental groups. The MHLCS-Internality may range from 6 to 36 and higher values means greater subject's internal locus of control. | 12 months | 
| Multidimensional Health Locus of Control Scale (MHLCS) - Powerful Others Externality | Comparison of the mean change from baseline in locus of control as assessed by Multidimensional Health Locus of Control Scale (MHLCS)-powerful-others-externality in the two experimental groups. The MHLCS-powerful-others-externality may range from 6 to 36 and higher values means greater subject's external (dependent on others) locus of control. | 12 months | 
| Multidimensional Health Locus of Control Scale (MHLCS) - Chance Externality | Comparison of the mean change from baseline in locus of control as assessed by Multidimensional Health Locus of Control Scale (MHLCS)-chance-externality in the two experimental groups. The MHLCS-chance-externality may range from 6 to 36 and higher values means greater external (case-dependent) locus of control of the subject. | 12 months | 
| General Self Efficacy (GSE Scale) | Comparison of the mean change from baseline in general self-efficacy as assessed by General Self Efficacy scale (GSE) in the two experimental groups. The GSE scale may range from 10 to 40 and higher values mean greater self-efficacy perceived by the subject. | 12 months | 
| Risk propensity (RPS Scale) | Comparison of the mean change from baseline in risk propensity as assessed by Risk Propensity Scale (RPS) in the two experimental groups. The RPS scale may range from 7 to 63 and higher values mean greater propensity to take risks. | 12 months | 
| Sleep quality (Pittsburgh Sleep Quality Index) | Comparison of the mean change from baseline in sleep quality as assessed by Pittsburgh Sleep Quality Index (PSQI) in the two experimental groups. The PSQI may range from 0 to 21 and higher values mean lower sleep quality. | 12 months | 
| Subjects' adherence to data recording | The App developed in the project collects information to analyse the participant's compliance with the data recording activities suggested by the app itself (blood pressure and blood glucose measurements, etc.). The subjects' adherence to data recording activities suggested by the app is assessed as the proportion of activities actually accomplished over the activities suggested. | 12 months | 
| Interruptions in the use of the mHealth App | The App developed in the project provides functions able to assess the number of accesses over time of the participant and the actual use of the recommended tools. The interruptions in the use of the mHealth App is assessed as the number of weeks of lack of the actual use of the app. | 12 months | 
| Adherence to recommended therapies | As part of the project, information on current therapies are collected in the eCRF at both baseline and 12 months. This information, together with the clinical/anthropometric data collected on the same occasions, will make it possible to ascertain whether a possible discontinuation of one of the therapies recorded at baseline is due to a improvement in the participant's clinical profile or to poor compliance. A poor adherence to recommended therapies is assessed by computing the frequency of non-medically justified therapy discontinuation. | 12 months | 
| Cost/effectiveness of intervention | Incremental cost-effectiveness ratio (EUR/QALYs) calculated on the basis of costs related to intervention implementation (summation of costs of implementing and maintaining the IT platform, costs of the smartphone application, costs for healthcare professionals training for the use of the IT platform and costs for the involvement and education of participants) combined in an economic model with the QALYs (Quality Adjusted Life Years) modelled based on number of cardiovascular events (fatal and non-fatal) avoided during the seven years of follow-up. | 7 years | 
| House ownership as socioeconomic status indicator | House ownership as socio-economic factor relevant to cardiovascular risk - proportion of subjects who are homeowners. | 7 years | 
| Type of residence as socioeconomic status indicator | Type of residence as socio-economic factor relevant to cardiovascular risk - proportion of subjects living in urban (big or small city) or rural area. | 7 years | 
| Education as socioeconomic status indicator | Education as socio-economic factor relevant to cardiovascular risk - proportion of subjects with: (1) no education (2) elementary education (3) Lower middle school (4) Higher middle school (5) Graduate (6) postgraduate). | 7 years | 
| Employment status as socioeconomic status indicator | Employment status as socio-economic factor relevant to cardiovascular risk - proportion of subjects who: (1) have a full-time job, (2) work less than 5 days a week, (3) have a part-time job, (4) are disability pensioner, (5) are retired due to age limit, (6) are Partially retired, (7) are unemployed, (8) are Housewife. | 7 years | 
| Type of profession as socioeconomic status indicator | Type of profession as socio-economic factor relevant to cardiovascular risk - proportion of subjects who are: (1) professionals, (2) teachers, (3) large business owners, (4) small business owners, (5) services, (6) employees, (7) laborers, (8) farmers, (9) Other. | 7 years | 
| Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - history of hospitalization (questionnaire) | History of hospitalization for SARS-CoV-2 infection as a risk factor for vascular events - proportion of subjects hospitalized for SARS-CoV-2 infection among those who develop or not vascular events over the 7-year follow-up period. | 7 years | 
| Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - history of symptoms (questionnaire) | History of symptoms for SARS-CoV-2 infection as a risk factor for vascular events - proportion of subjects with symptoms for SARS-CoV-2 infection among those who develop or not vascular events over the 7-year follow-up period. | 7 years | 
| Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - history of asymptomatic disease (questionnaire) | History of asymptomatic SARS-CoV-2, documented by at least one positive swab, as a risk factor for vascular events - proportion of subjects with at least one positive swab for SARS-CoV-2 infection among those who do or do not develop vascular events during the 7-year follow-up period. | 7 years | 
| Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - history of vaccination (questionnaire) | History of vaccination against SARS-CoV-2 infection as a protective factor for vascular events - proportion of subjects with at least one dose of vaccination against SARS-CoV-2 infection among those who do or do not develop vascular events during the 7-year follow-up period. | 7 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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CV primary prevention, CV risk factors, Hypertension, Diabetes, Hypercholesterolemia, Lifestyle behaviours, Digital Health, mHealth, Mobile app, Health empowerment, Primary care