Gender Differences in Prevention Strategies and Therapeutic Adherence After Acute Myocardial Infarction - GENAMI PREVENTION
Conditions: Gender Differences, Adherence, Medication, Therapeutic Adherence, Type 1 Acute Myocardial Infarction
Sponsor: Spanish Society of Cardiology

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Gender differences in prevention strategies 
and therapeutic adherence 
after acute myocardial infarction 
 
 
GENAMI PREVENTION 
 
 
 
 
 
 
Study protocol 
 
 
 
 
 
 
 
 
 
 
 
 
Principal Investigator Contact Information 
Héctor Bueno, MD, PhD 
Área de Investigación Cardiovascular. Instituto de Investigación i+12 
Servicio de Cardiología. Hospital Universitario 12 de Octubre, Madrid 
Centro Nacional de Investigación Cardiovasculares (CNIC) 
 

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SUMMARY 
Background and objectives. Women with acute myocardial infarction (AMI) 
are less likely to receive acute treatments according to guidelines 
recommendations, often present worse short- and long-term outcomes, and are 
less likely to receive secondary prevention therapies. However, comparisons 
have 
been 
hampered 
by 
several 
differences 
in 
the 
epidemiology, 
pathophysiology and presentation of AMI between men and women, including 
age, comorbidities, pathophysiology, and AMI types.  
While several studies have been dedicated to understand and reduce the 
gender gap in acute care, the role of gender on compliance with secondary 
prevention recommendations (pharmacological and non-pharmacological), and 
the factors associated with non-compliance in women are largely unknown.  
The aims of the study is to compare between a cohort of women who have 
suffered an AMI and a comparable cohort of men:1) the proportion of 6- and 12-
month 
adherence 
to 
the 
secondary 
cardiovascular 
prevention 
recommendations, 2) the proportion of patients with adequate control of risk 
factors, 3) the incidence of clinical outcomes, and 4) to study the factors 
associated with lower adherence (including biological, disease-related, 
psychosocial, and gender-related). 
Design. Prospective, matched cohort study of patients hospitalized for type 1 
acute myocardial infarction with significant coronary artery disease. The 
reference cohort will be composed of 500 women and the comparison group of 
500 men with a 1:1 matching for age (±2 years) and ECG (STEMI/NSTEMI), 
with 1-year follow-up assessing adherence with pharmacological and non-
pharmacological secondary prevention recommendations, risk factor control 
and clinical outcomes. 
End-points. Primary end-point: composite outcome of adherence to all 
secondary CV prevention recommendations 12 months after discharge, 
including pharmacological therapies, diet, physical activity and participation in 
cardiac rehabilitation programs. Secondary end-points: adherence to all 
secondary CV prevention recommendations at 6 months, percentage of patients 
achieving optimal control of all individual CV risk factors, composite clinical 
endpoint at 12 months: all-cause death, all-cause rehospitalization, and all-
cause emergency department visits, among others. 
Statistical analysis. A logistic regression models will be used to evaluate 
differences in the primary outcome between women and men, as well as in 
other outcomes. All subjects will be assumed to have a fixed follow-up (12±1 
month). Multivariate adjusted models will be used to address any potential 
confounding in the associations between sex and each of the outcomes. 
Covariates will be selected based on their pre-defined clinical value and the 
unbalances observed across groups in the univariate analyses. 
 
 

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Sponsor: Sociedad Española de Cardiología 
Funding: ORGANON (Unrestricted grant) 
Principal Investigator: Héctor Bueno, MD, PhD 
Executive Committee: Héctor Bueno, MD, PhD; Juan José Gómez Doblas, 
MD, PhD, Juan Cosín Sales, MD, PhD, Xavier Rosselló, MD, PhD; Lourdes 
Vicent, MD, PhD 
Scientific Committee: Héctor Bueno, MD, PhD; Juan José Gómez Doblas, 
MD, PhD, Juan Cosín Sales, MD, PhD; Juan José Gómez Doblas, MD, PhD, 
Xavier Rosselló, MD, PhD; Lourdes Vicent, MD, PhD; Alberto Cordero Fort, 
MD, PhD; Leticia Fernández Friera, MD, PhD; Ignacio Ferreira González, MD, 
PhD; 
 
 
 

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Clinical sites (25)  
 
 
C. Autónoma Hospital 
Población 
1 Andalucía 
Hospital Universitario Virgen Macarena 
Sevilla 
2 Andalucía 
Hospital Universitario Virgen de la Victoria 
Málaga 
3 Aragón 
Hospital Universitario  Lozano Blesa 
Zaragoza 
4 Asturias 
Hospital Universitario Central de Asturias 
Oviedo 
5 Baleares 
Hospital Universitari Son Espases 
Palma de 
Mallorca 
6 C. La Mancha Complejo Hospitalario de Toledo 
Toledo 
7 C. La Mancha Complejo Hospitalario Universitario de Albacete 
Albacete 
8 C. León 
Hospital Clínico Universitario de Salamanca 
Salamanca 
9 C. León 
Complejo Asistencial Universitario de León 
León 
10 C. Madrid 
Hospital Universitario Fundación Alcorcón 
Alcorcón 
11 C. Madrid 
Hospital Universitario 12 de Octubre 
Madrid 
12 C. Valenciana Hospital General Universitario de Alicante 
Alicante 
13 C. Valenciana Hospital Clínico Universitario de Valencia 
Valencia 
14 Canarias 
Hospital Universitario de Gran Canaria Dr. Negrín (*) Las Palmas de 
Gran Canaria 
15 Canarias 
Complejo Hospitalario Universitario de Canarias, La 
Laguna 
Tenerife 
16 Cantabria 
Hospital Universitario Marqués de Valdecilla 
Santander 
17 Cataluña 
Hospital Universitario de Bellvitge 
Barcelona 
18 Cataluña 
Hospital Universitario Vall´d Hebron 
Barcelona 
19 Extremadura 
Hospital San Pedro de Alcántara 
Cáceres 
20 Galicia 
Hospital Álvaro Cunqueiro de Vigo 
Vigo 
21 Galicia 
Hospital Universitario de Santiago de Compostela 
Santiago 
22 Murcia 
Hospital Universitario Virgen de la Arrixaca 
Murcia 
23 Navarra 
Complejo Hospitalario de Navarra 
Pamplona 
24 País Vasco 
Hospital Universitario de Basurto 
Bilbao 
25 País Vasco 
Hospital Universitario de Áraba (sede Txagorritxu) Vitoria 
 
 
 

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1. RATIONALE AND BACKGROUND 
Coronary artery disease (CAD) is the leading cause of death worldwide, both in 
women and men,1 mostly driven by acute coronary syndromes. Actually, CAD 
kills twice as many women as breast cancer.2 In recent years there has been a 
decrease in the fatality rate due to CAD3 of 31.8% (from 2006 to 2016), 
standing at 132.3 in men and 67.9 in women, of white race, per 100,000 
inhabitants (146.5 and 85.4 for men and women, of African American race, 
respectively).4 Part of this phenomenon is due to a decrease in recent years in 
the incidence of ST-segment elevation acute myocardial infarction (STEMI), a 
slight increase in the incidence of non-ST-segment elevation acute myocardial 
infarction (NSTEMI) and a decrease in in-hospital mortality.5–8 However, these 
data are controversial, since the annual incidence of hospitalizations for AMI 
has increased in young people, with the greatest increase observed in young 
women. Also trends in mortality have changed, with increasing CAD mortality 
among woman and higher in-hospital mortality in young women (<45 years).9,10 
Women with AMI are undertreated and also have a greater burden of 
comorbidities.11,12 Likewise, the number of hospitalizations for AMI, as well as 
the risk of in-hospital mortality, has been decreasing in recent years (although 
in-hospital mortality in women has increased slightly).13 One other factor that 
explains the decrease in mortality after an AMI is the development and 
implementation of effective evidence-based therapies, such as coronary 
revascularization and pharmacological treatments. These treatments are started 
in the acute hospitalization phase and are continued during follow-up 
(secondary prevention).14 These facts should persuade us to conduct further 
studies, especially in young women, to try to explain these effects. 
 
The role of biology and gender in the pathophysiology and outcomes of 
AMI 
There are notable differences in the susceptibility and pathophysiological 
mechanisms of AMI between men and women, some biologically-based but 
others due to environmental factors, among which, gender-specific conditions 
have gained interest in recent years. Men have a greater predisposition to 
atherothrombotic (type 1) AMI, usually presenting at younger ages. In contrast, 
although type 1 is the most common form of presentation in women, they 

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present more frequently other mechanisms of AMI (i.e. type 2 myocardial 
infarctions caused by spontaneous coronary artery dissection, or AMI with non-
obstructive coronary artery disease —MINOCA—, i.e. coronary vasospasm or 
microvascular dysfunction, especially in the younger age group).15  
Most medical treatments that demonstrated clinical benefits in AMI did so 
mainly in patients with type 1 AMI (antiplatelet drugs, lipid-lowering therapies, 
beta-blockers…). 
Risk factors for atherosclerotic CAD can be classified in four major groups: 
- 
Traditional cardiovascular risk factors. Cardiovascular risk factors are 
underreported in women who come to the Primary Care consultation.16,17 
This lack of diagnosis prevents specific preventive actions. Another 
noteworthy aspect is that while in men there has been a decrease in 
unhealthy lifestyle habits such as smoking, in women, especially in the 
younger group, it has remained stable or may even have increased.3,18 
Obesity and sedentary lifestyle are more frequent in women. Notably, the 
impact of metabolic risk factors such as diabetes could confer a higher 
cardiovascular risk in women than in men.18 
o Non-modifiable 
biological 
risk 
factors: 
age, 
sex, 
ethnic 
background, familiar history of cardiovascular disease.  
o Modifiable risk factors: hypertension, diabetes, dyslipidemia, 
smoking, obesity. 
- 
Non-traditional risk factors: obstructive sleep apnea syndrome and 
chronic kidney disease. 
- 
Sex-specific risk factors.2,19–25 A number of clinical conditions unique to 
women that have been identified to be associated with increased risk of 
cardiovascular disease. Reproductive factors include early menarche, 
early menopause, history of miscarriages, reproductive treatments, 
polycystic ovary syndrome (which is closely related to metabolic 
syndrome and insulin resistance), gestational diabetes, number of 
pregnancies, breastfeeding and lactation duration, hysterectomy, 
hormone replacement therapy, use of hormonal contraceptives, history of 
pre-eclampsia, eclampsia, or pregnancy-associated hypertension 2. 
Female protection against CVD is associated with sex hormone levels as 
the incidence and severity of CVD increases in postmenopausal 

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women26 and the prevalence of CAD is greater in young women who had 
an oophorectomy compared to those with intact ovaries.27 Taken 
together, this data has sparked much investigation into the potential of 
female sex hormones in conferring cardioprotection. The mechanisms 
that explain the association between these factors and the increase in 
cardiovascular risk are complex, but could be related to greater adiposity 
in patients who present them (i.e. polycystic ovary syndrome, early 
menarche), proinflammatory factors or endothelial dysfunction, among 
others.23  
- 
Socio-economic factors: Social support acts as a protective element that 
reduces the impact of negative life events in people's lives.28 Therefore, it 
is considered that poor social support is associated with a 1.5 to 2-fold 
increase in the risk of CVD, both in healthy people and in those with 
heart disease.28 Low socioeconomic status is associated with increased 
risk of cardiovascular events, including AMI and poorer survival 29,30. The 
impact of material deprivation and level of socioeconomic resources is 
even greater in women than in men.31 For women, living in a deprived 
neighborhood may affect coronary health in a greater extent than men, 
especially in the younger stratum.32  
- 
Psycho-social risk factors.33 Increasing importance is given to factors 
such as chronic stress, anxiety disorders, depression, personality factors, 
economic status, sleep disorders, social isolation or childhood trauma. 
Depression, anxiety, anger and stress (acute, chronic) are factors that 
increase cardiovascular risk.34 It is considered that there is a dose-
response relationship between depression and cardiovascular events, 
and therefore a more severe depression also increases cardiovascular 
risk.35 Anxiety is related to an increase in cardiac mortality, especially in 
patients with a more severe cardiovascular disease. The influence of 
stress on cardiovascular risk depends on the presence of acute triggers, 
and chronic stress.36 Acute stress affects cardiovascular physiology, 
increasing the risk of arrhythmias, myocardial ischemia, and may 
precipitate an acute myocardial infarction.37 Chronic stress, however, 
seems to influence cardiovascular disease through chronic physiological 
disturbances, and is linked, among others, to work stress, marital 

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problems, long-term caregiving to people in a situation of dependency, 
aspects related to the neighborhood or the economic status.33,38 Work 
stress under burdensome domestic work has been strongly associated 
with depression in women and men 39 but there are differences in the 
levels of work overload reported between genders. Women reported 
higher levels of work overload, stress and conflict than men, which 
increased significantly with the number of children at home. The various 
stress indices reached a peak between the ages of 35 and 39. 40 The 
role of social, psychological and cultural factors has not been fully 
studied. Psychosocial factors have a greater impact on the outcomes of 
women who present with an AMI, especially in the younger age stratum, 
as they have high rates of poverty, social isolation, history of sexual 
abuse or childhood trauma and are often from minority groups.41,42 
Depression is present in more than half of women aged <50 years who 
present with an AMI, and is associated with worse outcomes.43,44 The 
role of specific gender issues in the outcome of AMI has been seldom 
studied.45,46 
 
Gender differences in acute myocardial infarction presentation and 
management 
Women with AMI often show longer delays to diagnosis, reperfusion therapy, 
and a higher risk of complications, such as bleeding, cardiogenic shock or 
mechanical complications.47–50 This worse prognosis has traditionally been 
attributed to their higher risk profile, with older age and more comorbidities.51  
Women with AMI are less likely to receive timely reperfusion, other acute 
treatments, secondary prevention therapies or be referred to cardiac 
rehabilitation.52,53,54,55,56 There are sex-related disparities still observed today in 
the care of patients with infarction that disadvantage women and that extend to 
three key moments: ACS diagnosis, acute treatments (including DAPT at arrival 
and reperfusion therapy) and secondary prevention treatments (anti -platelets, 
statins, renin-angiotensin system inhibitors).57,58 Women are less commonly 
prescribed cardiac rehabilitation after ACS, and are particularly unlike to 
participate in cardiac rehabilitation programs.59,60 As cardiac rehabilitation has 

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also shown benefit in women after an ACS, an effort is needed to increase 
utilization among women.  
However, most comparisons between women and men with AMI are hampered 
by the major differences in the epidemiology and pathophysiology of AMI,13 
including the older age of women, their greater comorbidity (particularly, renal 
disease),11 increased risk of adverse effects with therapies (i.e. bleeding)49 and 
the different proportion of different AMI types (i.e. women presenting more often 
with type-2 AMI or with non-obstructive coronary artery disease),15,55,61 which 
has therapeutic and prognostic implications. These differences need to be 
accounted for to improve the accuracy of comparisons and define more clearly 
the role of sex and gender on the management and outcomes of AMI.46 
 
Gender and determinants of adherence to evidence-based therapies after 
AMI 
Age, gender, the presence of comorbidities and polypharmacy are factors that 
predict adherence to secondary prevention therapies 62. Women with AMI have 
been found to have differences in adherence compared with men, with lower 
adherence to P2Y12 inhibitors (i.e. clopidogrel) 63 or a 10% greater probability of 
non-adherence to statins.64 In a study with 148,654 patients with AMI, who had 
received secondary prevention measures in accordance with the clinical 
guidelines (loading dose of antiplatelets and chronic doses of aspirin, beta-
blockers and ACE inhibitors in patients with AMI and reduced left ventricular 
ejection fraction, lipid-lowering drugs and medical advice smoking cessation) 
female gender was associated with poorer adherence on all measures 65. 
However, a recent meta-analysis showed a lower adherence to lipid-lowering 
drugs (OR = 0.87, 95% CI 0.82-0.92) with no differences in the other three 
major pharmacological groups of secondary prevention (ACE inhibitors/ARA-II, 
beta-blockers and antiplatelets) in women post-MI,66 but the role of the 
differences in age and comorbidities in these results is unknown. Regarding the 
adherence to non-pharmacological secondary prevention measures, registries 
and observational studies have observed that men are less likely to achieve 
blood pressure goals than women.67 The results of the EUROASPIRE V survey 
also reveal that women change their healthy food habits in compliance with the 
recommendations, more frequently than men do.68  

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With the increasing awareness of sex disparities in cardiac care in the last 
years, it is possible that the sex-related differences in the prescription of 
secondary prevention therapies have improved. However, in the last two years, 
due to the COVID-19 pandemic, social disparities have increased and this may 
have had an unfavorable impact on women’s health, increasing the gender gap. 
The reasons for these differences are not well known and should be explored in 
order to develop interventions to improve effective secondary prevention 
strategies tailored for women, and their outcomes. 
 
 
2. HIPOTHESIS 
 
We have the following three alternative hypotheses. 
Compared with men:  
● the adherence to secondary prevention strategies after AMI is lower in 
women, regardless of their baseline differences. 
● the control of CV risk factors after AMI is poorer in women. 
● The incidence of clinical outcomes and/or use of healthcare resources 
after AMI is higher in women. 
The null hypothesis for each of the previous statements is that there is no 
difference between men and women for each of the outcomes. The main 
rationale for our alternative hypotheses is based on gender-related factors 
rather than on biological differences.  
 
In addition, we hypothesize that there are gender-related factors associated 
with (non-) adherence to secondary prevention recommendations in women. 
 
 
 

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3. OBJECTIVES 
 
General objective. To evaluate if there are differences in the level of 
adherence to recommended secondary prevention therapies (pharmacological 
and non-pharmacological) between women and men surviving a type 1 AMI 
(with obstructive CAD), its potential consequences, and the potential factors 
related to that difference, if present. 
 
Specific objectives. To compare between women and men: 
 
1)  The adherence to recommended secondary prevention therapies at 6 
months and 12 months measured as the 
1a. Proportion of patients adherent to all recommended pharmacological 
secondary prevention therapies at 6 and 12 months 
1b. Proportion of patients adherent to all recommended non-
pharmacological secondary prevention therapies at 6 and 12 months 
2) The relationship of the adherence with control of risk factors, clinical 
outcomes, and use of healthcare resources 
2a. The proportion of patients with optimal control of all cardiovascular 
risk factors at 6 and 12 months 
2b. The incidence of clinical outcomes at 6 and 12 months 
2c.  The cumulative use of healthcare resources and cost after discharge 
 
3)  To assess the factors associated with non-adherence to recommended 
secondary prevention therapies, with special emphasis to socioeconomic 
factors and gender issues. 
 
 
 

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4. STUDY DESIGN AND RESEARCH PLAN 
 
4.1. DESIGN. 
Prospective, matched cohort study of patients hospitalized for a type 1 AMI 
with evidence of obstructive coronary artery disease who are discharged home 
alive. Women will be enrolled first, ideally in a consecutive manner, as they are 
the focus of the study. Men will be recruited subsequently as the comparison 
group, with 1:1 matching for age and ECG presentation. Matching will be 
performed locally, in each study site (hospital). All patients will undergo 1-year 
follow-up with clinical and therapeutic adherence evaluation. 
 
 
Reference cohort: 500 women discharged alive after a hospitalization for a 
type 1 AMI with significant CAD 
Comparator cohort: 500 age (±2 years) and ECG (STEMI/NSTEMI) locally 
matched men discharged alive after a hospitalization for a type 1 AMI with 
significant CAD 
 
 
4.2. RECRUITMENT. 
 
Participant centers  
25 hospitals managing routinely AMIs and representing different regions from 
Spain will be invited to participate  
 
Patient recruitment 
All consecutive women fulfilling all inclusion criteria and without exclusion 
criteria surviving the index hospitalization will be invited to participate. 
Subsequently, men with inclusion criteria and without exclusion criteria, 
matched for age and ECG presentation, will be recruited. 
Inclusion criteria 
- Hospitalization for a type 1 AMI69 (detection of a rise and/or fall of cTn 
value above the 99th percentile URL and with at least one of the 
followings: symptoms of acute myocardial ischemia; new ischaemic 
ECG changes; development of phathological Q waves; imaging 
evidence of new loss of viable myocardium or new regional wall motion 

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abnormality in a patterns consistent with an ischaemic aetiology; 
identification of a coronary thrombus by angiography including 
intracoronary imaging) 
- Presence of obstructive coronary artery disease (CAD)70 (i.e. coronary 
artery stenosis ≥50%) 
- Age >18 years. No maximal age limit applies 
- Signed informed consent 
 
Exclusion criteria 
- Terminal disease (expected survival <12 months)  
- Unavailable 
for 
12-month 
follow-up (i.e.: 
living 
abroad, 
social 
situation…) 
- Does not speak Spanish 
- Major active comorbidity (severe renal or liver failure, active cancer 
requiring 
chemotherapy…), 
interfering 
with 
regular 
post-MI 
management  
 
5. INITIAL EVALUATION 
5.1. BASELINE CHARACTERISTICS 
5.1.1. Biological factors 
- Anthropological: age, sex, weight, height and body mass index. 
- Sex-specific factors of women’s cardiovascular risk: menarche age, 
number of pregnancies, gestational diabetes, early menopause, 
polycystic ovary syndrome, presence and number of miscarriages, 
use of hormonal replacement therapy (yes/no, duration), fertility 
treatments, use of hormonal contraceptives, history of eclampsia or 
pre-eclampsia, history of breast or endometrial cancer. 
- Vital signs: blood pressure (SBP, DBP) and heart rate. 
- Risk factors: hypertension, diabetes, hyperlipidemia, LDL, HDL, total 
cholesterol, triglycerides, lipoprotein(a), uric acid, tobacco and 
alcohol consumption, chronic alcoholism, HbA1c level, waist 
circumference, familiar history of premature coronary artery disease 
or familiar hypercholesterolemia. Pattern of food consumption and 
practice of physical activity (this will be measured using 

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questionnaire MEDAS and IPAQ which will be described in the 
followings sections). 
- Comorbidities: prior coronary artery disease (acute or chronic 
coronary syndrome), prior percutaneous coronary intervention, prior 
CABG, prior cerebrovascular disease (transient ischemic attack, 
ischemic stroke), peripheral vascular disease, heart failure, chronic 
kidney 
disease, 
COPD, 
Obstructive 
sleep 
apnea/hypopnea 
syndrome (OSAHS), atrial fibrillation, autoimmune disorders, anemia, 
depression (diagnosis of major depressive disorder), anxiety 
(diagnosis of generalized anxiety disorder) and Charlson Comorbidity 
Index (CCI).15 
 
5.1.2. Disease related factors 
AMI features: 
- Type of MI (STEMI/NSTEMI) 
- Number of diseased vessels 
- BARI segment responsible of AMI 
- Left ventricular ejection fraction at discharge (LVEF) before 
discharge (typically by echocardiography) 
- Killip class (on admission, “maximal”) 
- In-hospital complications (heart failure, bleeding, arrhythmias, 
cardiogenic shock). 
In-hospital management: 
- 
Reperfusion rates and times (for STEMI) 
- 
Patients receiving coronary angiography (for non-STEMI) and time 
since diagnosis to coronary angiography 
- 
Type of coronary revascularization 
- 
Coronary revascularization rates and completeness 
- 
Admission to the coronary unit 
- 
Length of hospital stay 
5.1.3. Socioeconomic factors 
- Social factors: ethnic group, educational level, marital status/living 
arrangements, role of primary caregiver and overload, country of 
birth, zip code. 

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- Economic factors: income category, employment status, type of 
contract (part-time or full-time), work conciliation. 
- Quality of life (SF-1216), Spanish version.71 
- 
 
5.1.4. Psychological factors 
- Anxiety and Depression (HADS 72), Spanish version.73 
5.1.5. Gender issues 
- Domestic and care workloads and intensity, frequency and duration 
of care: time of care and domestic work and intensity, frequency and 
duration of care, as well as the distribution of care (CUIDAR-SE 
Questionnaire). 
- Zarit Caregiver Burden Interview,74 Spanish version75 
 
5.2. SECONDARY PREVENTION RECOMMENDATIONS 
5.2.1. PHARMACOLOGICAL TREATMENTS 
- 
Secondary prevention strategies and medications (drugs) 
o Antiplatelets: Aspirin and P2Y12 inhibitors (including type) 
o Lipid-lowering therapies (statins, ezetimibe, PCSK9) 
o RAASi 
o Betablockers 
o Glucose control medications [SGLT2 inhibitors, GLP-1 
agonists…] 
- 
Prescription pattern: Total number of daily intakes, dose of each 
medication, total number of medications, use of injectable drugs, 
past difficulties regarding type of therapy. 
- 
 
5.2.2. Referral To Cardiac Rehabilitation/Secondary Prevention 
Program 
- 
Prescription pattern: Recommendation and scheduling to attend 
and 
participate 
in 
a 
structured 
program 
of 
cardiac 
rehabilitation/secondary prevention education 
- 
Adherence to the cardiac rehabilitation program 
o Number of attended sessions divided by the number of 
sessions prescribed.  
o ¿Achieve goals of target heart rate? TBD 

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- 
 
5.2.3. Diet Recommendations 
Current cardiovascular prevention guidelines recommend adopting a 
diet based on farm products and reducing foods of animal origin, 
together with the following recommendations:76 
• The consumption of saturated fats should not exceed 10% of 
total daily energy intake. Likewise, it is recommended to replace 
these 
with 
fats 
that 
contain 
polyunsaturated 
and 
monounsaturated fatty acids. 
• Replace carbohydrates in the diet with whole grain products 
(with whole grain cereals). 
• Trans fats should be minimized as much as possible, especially 
those from processed foods, whose consumption is totally 
discouraged. 
• Reduce salt intake to <5 g per day. 
• Consume 30-45 g of fiber per day, preferably from whole grain 
cereals. 
• The intake of more than 200 grams of fruit per day (2 or 3 
meals per day) is recommended. 
• Eat more than 200 grams of vegetables a day (2 or 3 meals a 
day). 
• Reduce the consumption of red meat to a total of 150-500 
grams per week, especially processed meats. 
• The consumption of fish is recommended 1 or 2 times a week, 
particularly the consumption of fish with essential fatty acids. 
• Consume 30 grams of unsalted nuts per day. 
• Reduce alcohol consumption to a maximum of 100 grams per 
week. 
• The consumption of sugary drinks such as soft drinks or fruit 
juices is discouraged. 
 
5.2.4. Physical Activity Recommendations 
- 
Prescription pattern: current cardiovascular prevention guidelines 
recommend performing moderate-intensity physical activity for 30 
minutes a day 5 or 7 days a week (a total of 150-300 minutes a 

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week) or performing 75 minutes of vigorous activity 1 or 2 days a 
week (a total of 75-150 minutes a week) for cardiovascular risk 
reduction 76. 
 
5.3. OUTCOMES 
All outcomes will be compared between men and women. 
OUTCOME DEFINITIONS 
5.3.1. Co-Primary outcomes 
- Pharmacological primary endpoint: outcome of adherence to 
pharmacological therapies (MMAS-8) 12 months after discharge. 
- Non-pharmacological primary endpoint: Composite outcome 
of adherence to non-pharmacological secondary CV prevention 
recommendations 12 months after discharge, including diet, 
physical activity and participation in cardiac rehabilitation 
programs. 
Adherence will be defined as compliance with at least 80% of each of 
the CV prevention recommendations separately: medications, cardiac 
rehabilitation program, diet and physical activity. This outcome is 
defined as an all-or-nothing endpoint with a binary response. These 
outcomes are defined as an all-or-none endpoint with a binary 
response.  
 
5.3.2. Secondary outcomes. 
- Pharmacological primary endpoint: outcome of adherence to 
pharmacological therapies (MMAS-8) 6 months after discharge. 
- Non-pharmacological primary endpoint: Composite outcome of 
adherence to non-pharmacological secondary CV prevention 
recommendations 6 months after discharge, including diet, physical 
activity and participation in cardiac rehabilitation programs. 
 
5.3.3. Pre-defined exploratory outcomes 
• Composite outcome of adherence to all secondary CV prevention 
recommendations 6 months after discharge (all-or-none composite 
outcome with a binary response) 

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• Percentage of patients achieving optimal (guidelines-recommended) 
control of all individual CV risk factors (LDL-cholesterol levels, blood 
pressure levels, HbA1c levels, smoking, levels of physical 
activity/sedentary life) 
• 12-month incidence of the composite clinical endpoint: All-cause 
death, 
all-cause 
rehospitalization, 
and 
all-cause 
emergency 
department visits 
• Use of healthcare resources at 12 months, including: days 
hospitalized (re-hospitalizations), number of ED visits, number of 
cardiac rehabilitation sessions, number of outpatient specialist visits, 
and number of urgent PCI procedures).  
• Assessment of the main predictors of adherence with secondary 
prevention recommendations in women (biological, disease-related, 
pharmacological, socio-economic, psychological, gender) 
• Composite outcome of adherence to all secondary pharmacological 
CV prevention recommendations 12 months after discharge, using 
pharmacy dispensation records. 
• In addition, data on changes in dose or drug will be collected to 
analyze their influence on adherence. 
• Evaluation of each individual components of the composite of 
adherence to secondary CV prevention recommendations 6 and 12 
months after discharge (these recommendations will be given to all 
patients at discharge): 
- Pharmacological therapies 
- Diet 
- Physical activity and  
- Participation in cardiac rehabilitation programs 
• Percentage of patients achieving optimal (guidelines-recommended) 
control of all individual CV risk factors: 
- LDL-cholesterol levels 
- Blood pressure levels 
- HbA1c levels 
- BMI 
- Smoking 

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- Levels of physical activity/sedentary life 
- Diet 
• Composite endpoint of cardiovascular death, rehospitalization, and 
emergency department visits for cardiovascular causes, and urgent 
coronary revascularization. 
• Effect of delays on return to work on adherence to cardiac 
rehabilitation and other secondary prevention measures. 
 
OUTCOME METRICS 
● Primary endpoint: Composite outcome of adherence to all secondary 
CV prevention recommendations at 12 months after discharge. The 
composite is built as an all-or-nothing response to an adherence ≥80% in 
all prescribed components of the endpoint: pharmacological therapies 
(MMAS-8), diet, physical activity and participation in a cardiac 
rehabilitation program. Adherence will be defined as having at least 80% 
compliance with all CV prevention recommendations; drugs, cardiac 
rehabilitation program, diet and physical activity) 
● Measurement of adherence to secondary prevention recommendations: 
At least 80% of adherence for the following prescribed recommendations 
at 6 and 12 months: 
- 
Diet recommendations 
- 
Physical activity recommendations 
- 
Drug prescriptions: 
o Aspirin for all without contraindications 
o P2Y12 inhibitors for all, according to the time indicated at 
discharge (if none, use 12 months) 
o Statins / other lipid-lowering therapies for all 
o Any of the following if indicated: 
▪ Beta blockers (if LVEF <0.40 or HF) 
▪ Angiotensin-converting enzyme inhibitors or angiotensin 
receptor blockers (if LVEF <0.40 or HF) 
▪ Glucose control medications (SGLT2 inhibitors/GLP-1 
agonists)  
1. Measurement of adherence to pharmacological recommendations:  

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a) The Morinsky Medication Adherence Scale (MMAS-8).77 A total score of 
all items will be calculated with a sum score ranging from 0 to 8 for 
adherence. MMAS-8 Score will be calculated if the respondent answers 
at least 6 of 8 items. MMAS is trichomized in three levels of adherence: 
● High adherence (score 8) 
● Medium adherence (score, 6 to 7) 
● Low adherence (score, <6) 
b) Records of dispensations in the pharmacy: This is an indirect method to 
measure compliance based on evaluating the collection of the 
medication in the pharmacy. Patients who withdrew all medications 
during the year will be considered adherent. The information will be 
checked from the medical history that records the withdrawal of drugs 
from the pharmacy. This will be done for each of the secondary 
prevention medications to calculate adherence to each of them (aspirin, 
P2Y12 inhibitors, statins, and beta blockers or ACE inhibitors). 
2. Measurement of adherence to non-pharmacological recommendations:  
c) Adherence to diet: to evaluate this measure, the 14-point Mediterranean 
Diet Adherence Screener (MEDAS) questionnaire of Schröder et al, 
(2011) will be used 78. It is a 14-item questionnaire derived from the 
PREDIMED study (Primary Prevention Mediterranean Diet). Each item 
is assessed with a binary score (0 or 1) according to the diet pattern, 
referring to daily or weekly consumption, during the last 3 months. The 
score ranges between 0 and 14 points, establishing two levels of 
adherence: 
● Score <9: Poor adherence to the Mediterranean Diet, which 
requires an improvement in eating habits. 
● Score ≥9: Good adherence to the Mediterranean Diet 
d) Adherence to physical activity: it will be used the International Physical 
Activity Questionnaire (IPAQ) (Craig, 2003) 79. It consists of 5 questions 
about the frequency, duration and intensity (vigorous or moderate) of 
physical activity, carried out in the last week (last 7 days). It also 
collects the frequency and duration of the walking activity and the time 
that the person remains seated on a weekday. The IPAQ allows 
individuals to be assigned to three categories (low, medium, high) 

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according to the estimated energy expenditure for each activity: 
vigorous, 8 MET (metabolic equivalent task); moderate, 4 METs; and 
walking, 3.3 METs. According to the IPAQ categories, individuals who 
belong to the high or medium category are compliant, and those who 
belong to the low category are non-compliant. In addition to the 
classification by METs, there is the possibility of classifying individuals 
based on the duration, frequency and intensity of physical activity, 
without the need to calculate METs. These criteria included in the 
official guidelines published by the IPAQ Research Consortium are the 
following: 
● Low – No activity reported or some activity reported, but not 
enough to meet Category 2 or 3. 
● Moderate: any of the following 3 criteria 
○ 3 or more days of vigorous activity of at least 20 
minutes per day 
○ 5 or more days of moderate-intensity activity and/or 
walking for at least 30 minutes per day 
○ 5 or more days of any combination of moderate-
intensity 
or 
vigorous-intensity 
walking 
activities, 
achieving a minimum of at least 600 METs/min per 
week. 
● High: either of the following 2 criteria 
○ Vigorous intensity activity on at least 3 days and 
accumulating at least 1500 MET-minutes/week 
○ 7 or more days of any combination of walking, 
moderate 
or 
vigorous 
intensity 
activities 
that 
accumulate at least 3000 MET-minutes/week 
e) Cardiac rehabilitation: Attendance to all cardiac rehabilitation sessions 
will be collected and those who have completed at least 80% of 
scheduled sessions will be considered adherent. To explore its 
influence on cardiac rehabilitation attendance, time from discharge to 
return to work will be collected as an outcome. 
f) Measurement of clinical endpoints: 

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o Major adverse cardiovascular events at 6 and 12 months, 
including the combined endpoint of cardiovascular 
mortality, nonfatal AMI, nonfatal ischemic stroke 
o Cardiovascular mortality 
o Hospitalizations due to cardiovascular reasons 
o Emergency department visits due to cardiac causes 
o Urgent revascularization 
o Acute myocardial infarction 
g) The independent predictors of adherence with secondary prevention 
recommendations in women will be estimated with adequate statistical 
analyses (e.g., logistic regression models)  
h) The use of healthcare resources will be analyzed using the 
COHERENT model 80. 
 
 
 
 
 
 
 
 
 

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5.4. TIMELINE 
 
Number of Sites: 
25 
Site Names: 
Cardiology Departments from Spanish hospitals  
Study Start Date: 
September-2022 
Study End Date: 
December-2024 
Number of Subjects: 
1000 (500 cases and 500 controls) 
First Patient In Date: 
September-2022 
Last Patient Out Date: June-2024 
Enrollment Period 
6 months 
 

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Figure 1. Study design and flowchart 

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6. STATISTICAL ANALYSIS 
A minimum sample size of 820 participants (410 per group) was estimated for 
an expected relative difference in recommendations compliance of the all-or-
none composite primary outcome of 20%. An α error of 0.05 and a β error of 
0.20 were considered for the sample size. The recommendations compliance 
was estimated as 42% for women and 52% for men. With the consideration of 
20% of lost to follow-up (discontinuations) the total sample size is 984 patients, 
which is rounded out to 1000 patients (500 women and 500 men). To increase 
regional representation and allow exploration of potential regional variability, 25 
hospitals from all regions in Spain (17 Autonomous Communities) will be invited 
to participate. 
For the description of continuous variables, mean and SD, or median and 
interquartile range will be used for Gaussian and non-normal distributions, 
respectively. For describing categorical variables, frequencies and percentages 
per category will be used. Categorical variables will be compared using the chi2 
test, whilst continuous variables will be compared using the student t test.  
Logistic regression models will be used to evaluate differences in binary 
outcomes between women and men (in hospital AMI management, post 
discharge MI management). All subjects will be assumed to have a fixed follow-
up (12±1 month). Multivariate adjusted models will be used to address any 
potential confounding in the associations between sex and each of the 
outcomes. Covariates will be selected based on their pre-defined clinical value 
and the unbalances observed across groups in the univariate analyses. Linear, 
multinomial or ordinal regression models would be used in case of continuous, 
categorical, or ordinal outcomes, respectively. 
In addition to the models evaluating the association between sex and outcomes, 
a predictive model will be conducted to set predictors for the following 
outcomes: 
1) a composite of all preventive therapies (all-or-nothing for diet, physical 
activity, P2Y12 inhibitors, statins, and beta blockers or ACE inhibitors [if 
prescribed at discharge]), and  

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2) each group of preventive interventions (drugs, cardiac rehab, diet, physical 
activity) 
Candidate predictors are classified as biological factors (age, sex, risk factors, 
comorbidities), disease-related (type of MI: STEMI/NSTEMI, LVEF, number of 
vessels…), pharmacological factors (daily number of drugs, daily number of 
doses, specific drugs), socio-economic factors (zip code, education level, 
employment 
status, 
wages…) 
and 
specific 
gender 
issues 
(family 
responsibilities, work conciliation…). Special consideration will be given to age 
due to the high figures of in-hospital mortality in young women. 
For women-specific analysis, female specific factors (menarche age, 
pregnancies, gestational diabetes, menopause…) will be considered. 
We will use the Clinical Outcomes, HEalthcare REsource UtilizatioN, and 
relaTed costs (COHERENT) model to study the hospital-related healthcare 
resources (ED visits, specialist visits, re-hospitalizations and urgent procedures) 
and costs. 
 
 
 

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7. DATA MANAGEMENT PLAN PROPOSAL 
According to the Ethics Principles, only patients for whom a signed informed 
consent is obtained will be enrolled in the study. The research project is 
scientifically justified and described in a detailed protocol which will be 
presented to and approved first by the imas12 Research Commission and 
Research Ethics Committee and secondly by the Research Committees of all 
centers. Patient data will be recorded according to common practice. A "Patient 
Identification Log", including personal data and the patient ID codes will be 
generated and securely saved in the investigators file under strict physical, 
digital and personal security measures, guarded by the team researchers and 
never shared.  
Data will be generated as per protocol. Variables will be collected manually by 
project researchers or automatically by the electronic systems or equipment. 
Data files generated will be labelled appropriately and placed in suitably 
labelled/organised folders and sub-folders, with questionnaires, permissions, 
informed consents, protocol and study versions properly identified to facilitate 
easy finding, process automation and analysis, and reduce errors. Qualitative 
and quantitative data will be generated. Raw data will be analyzed and 
presented as tables, graphs and images in presentations and publications. The 
format and scale of the datasets will depend on data composition and 
magnitude. These will be accessible using common software facilitating access, 
data sharing, and long-term validity during and after the project. The research 
results will comply with the FAIR (Findable, Accessible, Interoperable and 
Reusable) principles and published in scientific journals in open access mode.  
Standard protocols will be defined, optimized and implemented to obtain data in 
a reliable and consistent manner. The services of a CRO will be contracted to 
assess data consistency though a Data Monitoring plan with individual random 
evaluation of the patients included in this study and overall analysis of the 
project's key variables. In addition, the Informed Consents will be reviewed to 
ensure adequate compliance with current regulations on GCP in research. The 
project staff will be adequately trained in the protocol requirements by the CRO 
staff to ensure high quality results. Data generated and methods used will be 
scrutinized to ensure that procedures have been carried out correctly, 

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appropriate controls used, and all information is suitably recorded to have 
accurate and reliable data. These routine procedures for high quality research 
will facilitate positive evaluation by peer reviewers in scientific contexts and 
high-impact publishers.  
Electronic data records will be generated, saved in one server with automated 
daily backups. File names/locations will be recorded in screening logs to allow 
electronic records to be linked to raw data. File names will have appropriately 
descriptive titles, including date of data generation to allow easy finding. Details 
of all data collected from patients will be recorded in REDCap, located in one 
server of the imas12 Research Institute. Additionally, regular electronic 
progress reports summarising the key information will be compiled by project 
staff. Electronic and written records will be retained for at least 10 years after 
the end of the project. 
Access to pre-publication electronic data will be limited to the members of the 
research group and relevant collaborators via limited access to shared drives on 
the imas12 Research Institute server. Access to servers are controlled by 
imas12 IT staff to reduce the likelihood of malicious loss/damage. All computers 
used in this project will run Standard Staff Desktop with firewalls and antivirus 
software automatically upgraded and secure remote access to data enabled. 
The study team’s exclusive use of the data will be made available at the time of 
publication, at the latest. Depending on the nature of the data, this may be 
made available earlier, either to interested researchers or potential new 
collaborators on an individual basis after prior request and review or publicly 
whenever needed (negative data). When research data or resources are shared 
with external users ahead of publication, specific written agreements will be 
signed by all parts to avoid misuse or external result communication/publication 
without the PI review and written approval of content and conditions (i.e. 
authorship). 
All people involved in the research project will have knowledge and 
accreditation of international standards of Good Clinical Practice (GCP) to 
guarantee the safety, rights and well-being of the participants and the quality 
and validity of research data. All collected and stored study data will be 
pseudoanimized, with only a limited part of the research team will have 

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restricted access to the linking participants identity, in accordance with the 
provisions of the Organic Law 3/2018 (Dec 5, 2018), Data Protection Personal 
Data and Guarantee of Digital Rights, Law 14/2007 (July 3, 2007), and 
Biomedical Research Law 41/2002, (November 14, 2002), basic regulator of 
patient´s autonomy of rights and obligations regarding information and clinical 
documentation. 
 

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References 
1.  Nowbar AN, Gitto M, Howard JP, Francis DP, Al-Lamee R. Mortality From Ischemic Heart 
Disease. Circ Cardiovasc Qual Outcomes. 2019;12:e005375.  
2.  Maas AHEM, Rosano G, Cifkova R, Chieffo A, van Dijken D, Hamoda H, Kunadian V, Laan 
E, Lambrinoudaki I, Maclaran K, Panay N, Stevenson JC, van Trotsenburg M, Collins P. 
Cardiovascular health after menopause transition, pregnancy disorders, and other 
gynaecologic 
conditions: 
a 
consensus 
document 
from 
European 
cardiologists, 
gynaecologists, and endocrinologists. European Heart Journal. 2021;42:967–984.  
3.  Jagannathan R, Patel SA, Ali MK, Narayan KMV. Global Updates on Cardiovascular 
Disease Mortality Trends and Attribution of Traditional Risk Factors. Curr Diab Rep. 
2019;19:44.  
4.  Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, 
Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, 
Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, 
Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, 
Matsushita K, Moran AE, Mussolino ME, O’Flaherty M, Pandey A, Perak AM, Rosamond 
WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes 
A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani 
SS. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart 
Association. Circulation. 2019;139:e56–e528.  
5.  Yeh RW, Sidney S, Chandra M, Sorel M, Selby JV, Go AS. Population trends in the 
incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362:2155–
2165.  
6.  Neumann JT, Goßling A, Sörensen NA, Blankenberg S, Magnussen C, Westermann D. 
Temporal trends in incidence and outcome of acute coronary syndrome. Clin Res Cardiol. 
2020;109:1186–1192.  
7.  Chi GC, Kanter MH, Li BH, Qian L, Reading SR, Harrison TN, Jacobsen SJ, Scott RD, 
Cavendish JJ, Lawrence JM, Tartof SY, Reynolds K. Trends in Acute Myocardial Infarction 
by Race and Ethnicity. J Am Heart Assoc. 2020;9:e013542.  
8.  Goldberg RJ, Tisminetzky M, Tran HV, Yarzebski J, Lessard D, Gore JM. Decade Long 
Trends (2001-2011) in the Incidence Rates of Initial Acute Myocardial Infarction. Am J 
Cardiol. 2019;123:206–211.  
9.  Bangalore S, Fonarow GC, Peterson ED, Hellkamp AS, Hernandez AF, Laskey W, 
Peacock WF, Cannon CP, Schwamm LH, Bhatt DL. Age and Gender Differences in Quality 
of Care and Outcomes for Patients with ST-segment Elevation Myocardial Infarction. The 
American Journal of Medicine. 2012;125:1000–1009.  
10.  Bossard M, Latifi Y, Fabbri M, Kurmann R, Brinkert M, Wolfrum M, Berte B, Cuculi F, 
Toggweiler S, Kobza R, Chamberlain AM, Moccetti F. Increasing Mortality From Premature 
Coronary Artery Disease in Women in the Rural United States. Journal of the American 
Heart Association. 2020;9:e015334.  
11.  Arora S, Stouffer GA, Kucharska-Newton AM, Qamar A, Vaduganathan M, Pandey A, 
Porterfield D, Blankstein R, Rosamond WD, Bhatt DL, Caughey MC. Twenty Year Trends 
and Sex Differences in Young Adults Hospitalized With Acute Myocardial Infarction. 
Circulation. 2019;139:1047–1056.  
12.  Wu WY, Berman AN, Biery DW, Blankstein R. Recent trends in acute myocardial infarction 
among the young. Curr Opin Cardiol. 2020;35:524–530.  
13.  Rodríguez-Padial L, Fernández-Pérez C, Bernal JL, Anguita M, Sambola A, Fernández-
Ortiz A, Elola FJ. Differences in in-hospital mortality after STEMI versus NSTEMI by sex. 
Eleven-year trend in the Spanish National Health Service. Rev Esp Cardiol (Engl Ed). 
2021;74:510–517.  
14.  Cortés-Beringola A, Fitzsimons D, Pelliccia A, Moreno G, Martín-Asenjo R, Bueno H. 
Planning secondary prevention: Room for improvement. European Journal of Preventive 
Cardiology. 2017;24:22–28.  
15.  Mehta LS, Beckie TM, DeVon HA, Grines CL, Krumholz HM, Johnson MN, Lindley KJ, 
Vaccarino V, Wang TY, Watson KE, Wenger NK. Acute Myocardial Infarction in Women. 
Circulation. 2016;133:916–947.  

GENAMI PREVENTION Research protocol 
 
Protocol Version 3.0 
 
 
May 22, 2022 
 
 
31 
16.  Woodward M. Cardiovascular Disease and the Female Disadvantage. Int J Environ Res 
Public Health. 2019;16:1165.  
17.  Hyun KK, Redfern J, Patel A, Peiris D, Brieger D, Sullivan D, Harris M, Usherwood T, 
MacMahon S, Lyford M, Woodward M. Gender inequalities in cardiovascular risk factor 
assessment and management in primary healthcare. Heart. 2017;103:492.  
18.  Young L, Cho L. Unique cardiovascular risk factors in women. Heart. 2019;105:1656.  
19.  Gao Z, Chen Z, Sun A, Deng X. Gender differences in cardiovascular disease. Medicine in 
Novel Technology and Devices. 2019;4:100025.  
20.  Regitz-Zagrosek V, Oertelt-Prigione S, Prescott E, Franconi F, Gerdts E, Foryst-Ludwig A, 
Maas AHEM, Kautzky-Willer A, Knappe-Wegner D, Kintscher U, Ladwig KH, Schenck-
Gustafsson K, Stangl V. Gender in cardiovascular diseases: impact on clinical 
manifestations, management,  and outcomes. Eur Heart J. 2016;37:24–34.  
21.  Regitz-Zagrosek V, Kararigas G. Mechanistic Pathways of Sex Differences in 
Cardiovascular Disease. Physiol Rev. 2017;97:1–37.  
22.  Gerdts E, Regitz-Zagrosek V. Sex differences in cardiometabolic disorders. Nat Med. 
2019;25:1657–1666.  
23.  Peters SA, Woodward M. Women’s reproductive factors and incident cardiovascular 
disease in the UK Biobank. Heart. 2018;104:1069.  
24.  Agarwala A, Michos ED, Samad Z, Ballantyne CM, Virani SS. The Use of Sex-Specific 
Factors in the Assessment of Women’s Cardiovascular Risk. Circulation. 2020;141:592–
599.  
25.  Tørris C, Bjørnnes AK. Duration of Lactation and Maternal Risk of Metabolic Syndrome: A 
Systematic Review and Meta-Analysis. Nutrients. 2020;12.  
26.  Hayward CS, Kelly RP, Collins P. The roles of gender, the menopause and hormone 
replacement on cardiovascular function. Cardiovascular Research. 2000;46:28–49.  
27.  Parker WH, Jacoby V, Shoupe D, Rocca W. Effect of Bilateral Oophorectomy on Women’s 
Long-Term Health. Womens Health (Lond Engl). 2009;5:565–576.  
28.  Smith SB, Geske JB, Kathuria P, Cuttica M, Schimmel DR, Courtney DM, Waterer GW, 
Wunderink RG. Analysis of National Trends in Admissions for Pulmonary Embolism. Chest. 
2016;150:35–45.  
29.  Rosvall M, Gerward S, Engström G, Hedblad B. Income and short-term case fatality after 
myocardial infarction in the whole middle-aged population of Malmö, Sweden. Eur J Public 
Health. 2008;18:533–538.  
30.  Coughlin SS, Young L. Social Determinants of Myocardial Infarction Risk and Survival: A 
Systematic Review. Eur j Cardiovasc Res. 2020;1:10.31487/j.ejcr.2020.01.02.  
31.  Deguen S, Lalloue B, Bard D, Havard S, Arveiler D, Zmirou-Navier D. A small-area 
ecologic study of myocardial infarction, neighborhood deprivation, and sex: a Bayesian 
modeling approach. Epidemiology. 2010;21:459–466.  
32.  Koopman C, van Oeffelen A, Bots M, Engelfriet P, Verschuren W, Rossem L, van Dis I, 
Capewell S, Vaartjes I. Neighbourhood socioeconomic inequalities in incidence of acute 
myocardial infarction: A cohort study quantifying age- and gender-specific differences in 
relative and absolute terms. BMC public health. 2012;12:617.  
33.  Peterson PN. JAHA Spotlight on Psychosocial Factors and Cardiovascular Disease. J Am 
Heart Assoc. 2020;9:e017112.  
34.  Greaney JL, Koffer RE, Saunders EFH, Almeida DM, Alexander LM. Self-Reported 
Everyday Psychosocial Stressors Are Associated With Greater Impairments in Endothelial 
Function in Young Adults With Major Depressive Disorder. J Am Heart Assoc. 
2019;8:e010825.  
35.  Rozanski A, Blumenthal JA, Kaplan J. Impact of psychological factors on the pathogenesis 
of cardiovascular disease and implications for therapy. Circulation. 1999;99:2192–2217.  
36.  Greaney JL, Surachman A, Saunders EFH, Alexander LM, Almeida DM. Greater Daily 
Psychosocial Stress Exposure is Associated With Increased Norepinephrine-Induced 
Vasoconstriction in Young Adults. J Am Heart Assoc. 2020;9:e015697.  

GENAMI PREVENTION Research protocol 
 
Protocol Version 3.0 
 
 
May 22, 2022 
 
 
32 
37.  Mittleman MA, Maclure M, Sherwood JB, Mulry RP, Tofler GH, Jacobs SC, Friedman R, 
Benson H, Muller JE. Triggering of Acute Myocardial Infarction Onset by Episodes of 
Anger. Circulation. 1995;92:1720–1725.  
38.  Nabi H, Kivimäki M, Batty GD, Shipley MJ, Britton A, Brunner EJ, Vahtera J, Lemogne C, 
Elbaz A, Singh-Manoux A. Increased risk of coronary heart disease among individuals 
reporting adverse impact of stress on their health: the Whitehall II prospective cohort study. 
Eur Heart J. 2013;34:2697–2705.  
39.  Molarius A, Metsini A. Domestic Work, Self-Reported Diagnosed Depression and Related 
Costs among Women and Men-Results from a Population-Based Study in Sweden. Int J 
Environ Res Public Health. 2021;18.  
40.  Lundberg U, Mårdberg B, Frankenhaeuser M. The total workload of male and female white 
collar workers as related to age, occupational level, and number of children. Scand J 
Psychol. 1994;35:315–327.  
41.  Vaccarino V, Shah AJ, Rooks C, Ibeanu I, Nye JA, Pimple P, Salerno A, D’Marco L, Karohl 
C, Bremner JD, Raggi P. Sex differences in mental stress-induced myocardial ischemia in 
young survivors of an acute myocardial infarction. Psychosom Med. 2014;76:171–180.  
42.  Rossello X, Mas-Lladó C, Pocock S, Vicent L, Van de Werf F, Chin CT, Danchin N, Lee 
SWL, Medina J, Huo Y, Bueno H. Sex differences in mortality after an acute coronary 
syndrome increase with lower country wealth and higher income inequality. Revista 
Española 
de 
Cardiología 
(English 
Edition) 
[Internet]. 
Available 
from: 
/18855857/unassign/S1885585721001596/v2_202107040503/en/main.assets 
43.  Lichtman JH, Froelicher ES, Blumenthal JA, Carney RM, Doering LV, Frasure-Smith N, 
Freedland KE, Jaffe AS, Leifheit-Limson EC, Sheps DS, Vaccarino V, Wulsin L. 
Depression as a Risk Factor for Poor Prognosis Among Patients With Acute Coronary 
Syndrome: Systematic Review and Recommendations. Circulation. 2014;129:1350–1369.  
44.  Smolderen KG, Strait KM, Dreyer RP, D’Onofrio G, Zhou S, Lichtman JH, Geda M, Bueno 
H, Beltrame J, Safdar B, Krumholz HM, Spertus JA. Depressive Symptoms in Younger 
Women and Men With Acute Myocardial Infarction: Insights From the VIRGO Study. J Am 
Heart Assoc. 4:e001424.  
45.  Raparelli V, Norris CM, Bender U, Herrero MT, Kautzky-Willer A, Kublickiene K, El Emam 
K, Pilote L. Identification and inclusion of gender factors in retrospective cohort studies: the 
GOING-FWD framework. BMJ Global Health. 2021;6:e005413.  
46.  Rossi AM, Pilote L. Let’s Talk About Sex…and Gender! Circulation Cardiovasc Qual 
Outcomes. 2016;9:S100–S101.  
47.  Wu J, Gale CP, Hall M, Dondo TB, Metcalfe E, Oliver G, Batin PD, Hemingway H, Timmis 
A, West RM. Editor’s Choice - Impact of initial hospital diagnosis on mortality for acute 
myocardial infarction: A national cohort study. Eur Heart J Acute Cardiovasc Care. 
2018;7:139–148.  
48.  Bugiardini R, Ricci B, Cenko E, Vasiljevic Z, Kedev S, Davidovic G, Zdravkovic M, Miličić 
D, Dilic M, Manfrini O, Koller A, Badimon L. Delayed Care and Mortality Among Women 
and Men With Myocardial Infarction. J Am Heart Assoc. 2017;6:e005968.  
49.  Ahmed B, Dauerman HL. Women, Bleeding, and Coronary Intervention. Circulation. 
2013;127:641–649.  
50.  Damluji AA, van Diepen S, Katz JN, Menon V, Tamis-Holland JE, Bakitas M, Cohen MG, 
Balsam LB, Chikwe J, null  null. Mechanical Complications of Acute Myocardial Infarction: 
A Scientific Statement From the American Heart Association. Circulation. 2021;144:e16–
e35.  
51.  Kuehnemund L, Koeppe J, Feld J, Wiederhold A, Illner J, Makowski L, Gerß J, Reinecke H, 
Freisinger E. Gender differences in acute myocardial infarction-A nationwide German real-
life analysis from 2014 to 2017. Clin Cardiol. 2021;44:890–898.  
52.  Matetic A, Shamkhani W, Rashid M, Volgman AS, Van Spall HGC, Coutinho T, Mehta LS, 
Sharma G, Parwani P, Mohamed MO, Mamas MA. Trends of Sex Differences in Clinical 
Outcomes After Myocardial Infarction in the United States. CJC Open. 2021;3:S19–S27.  
53.  Eindhoven DC, Hilt AD, Zwaan TC, Schalij MJ, Borleffs CJW. Age and gender differences 
in medical adherence after myocardial infarction: Women do not receive optimal treatment 
– The Netherlands claims database. Eur J Prev Cardiolog. 2018;25:181–189.  

GENAMI PREVENTION Research protocol 
 
Protocol Version 3.0 
 
 
May 22, 2022 
 
 
33 
54.  Hyun K, Negrone A, Redfern J, Atkins E, Chow C, Kilian J, Rajaratnam R, Brieger D. 
Gender Difference in Secondary Prevention of Cardiovascular Disease and Outcomes 
Following the Survival of Acute Coronary Syndrome. Heart Lung Circ. 2021;30:121–127.  
55.  Gulati M, Hendry C, Parapid B, Mulvagh SL. Why We Need Specialised Centres for 
Women’s Hearts: Changing the Face of Cardiovascular Care for Women. Eur Cardiol. 
2021;16:e52–e52.  
56.  Smolina K, Ball L, Humphries KH, Khan N, Morgan SG. Sex Disparities in Post-Acute 
Myocardial Infarction Pharmacologic Treatment Initiation and Adherence: Problem for 
Young Women. Circ Cardiovasc Qual Outcomes. 2015;8:586–592.  
57.  Hao Y, Liu J, Liu J, Yang N, Smith SCJ, Huo Y, Fonarow GC, Ge J, Taubert KA, Morgan L, 
Zhou M, Xing Y, Ma C-S, Han Y, Zhao D. Sex Differences in In-Hospital Management and 
Outcomes of Patients With Acute Coronary Syndrome. Circulation. 2019;139:1776–1785.  
58.  Dagan M, Dinh DT, Stehli J, Tan C, Brennan A, Warren J, Ajani AE, Freeman M, Murphy 
A, Reid CM, Hiew C, Oqueli E, Clark DJ, Duffy SJ, on behalf of the Melbourne 
Interventional Group. Sex disparity in secondary prevention pharmacotherapy and clinical 
outcomes following acute coronary syndrome. Eur Heart J Qual Care Clin Outcomes. 
2021;qcab007.  
59.  Witt BJ, Jacobsen SJ, Weston SA, Killian JM, Meverden RA, Allison TG, Reeder GS, 
Roger VL. Cardiac rehabilitation after myocardial infarction in the community. J Am Coll 
Cardiol. 2004;44:988–996.  
60.  Crnko S, Du Pré BC, Sluijter JPG, Van Laake LW. Circadian rhythms and the molecular 
clock in cardiovascular biology and disease. Nature Reviews Cardiology. 2019;16:437–
447.  
61.  Heras M. Ischemic heart disease in women: clinical presentation, non-invasive testing and 
management of acute coronary syndromes. Rev Esp Cardiol (English Edition). 
2006;59:371–381.  
62.  Hamood H, Hamood R, Green MS, Almog R. Determinants of adherence to evidence-
based therapy after acute myocardial infarction. Eur J Prev Cardiol. 2016;23:975–985.  
63.  Zhu B, Zhao Z, McCollam P, Anderson J, Bae JP, Fu H, Zettler M, Lenarz L. Factors 
associated with clopidogrel use, adherence, and persistence in patients with acute 
coronary syndromes undergoing percutaneous coronary intervention. Curr Med Res Opin. 
2011;27:633–641.  
64.  Lewey J, Shrank WH, Bowry ADK, Kilabuk E, Brennan TA, Choudhry NK. Gender and 
racial disparities in adherence to statin therapy: a meta-analysis. Am Heart J. 
2013;165:665–678, 678.e1.  
65.  Kumbhani DJ, Fonarow GC, Cannon CP, Hernandez AF, Peterson ED, Peacock WF, 
Laskey WK, Pan W, Schwamm LH, Bhatt DL. Predictors of adherence to performance 
measures in patients with acute myocardial infarction. Am J Med. 2013;126:74.e1–9.  
66.  Bots SH, Inia JA, Peters SAE. Medication Adherence After Acute Coronary Syndrome in 
Women Compared With Men: A Systematic Review and Meta-Analysis. Front Glob 
Womens Health. 2021;2:637398.  
67.  Sakalaki M, Barywani S, Rosengren A, Björck L, Fu M. Determinants of suboptimal long-
term secondary prevention of acute myocardial infarction: the structural interview method 
and physical examinations. BMC Cardiovasc Disord. 2019;19:243.  
68.  Marques-Vidal P, Jankowski P, De Bacquer D, Kotseva K. Dietary measures among 
patients with coronary heart disease in Europe. ESC EORP Euroaspire V. Int J Cardiol. 
2020;302:5–14.  
69.  Thygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, White HD, Group 
ESD. Fourth universal definition of myocardial infarction (2018). 269 [Internet]. 2019 [cited 
2022 Apr 21];Available from: http://spiral.imperial.ac.uk/handle/10044/1/73052 
70.  Agewall S, Beltrame JF, Reynolds HR, Niessner A, Rosano G, Caforio ALP, De Caterina 
R, Zimarino M, Roffi M, Kjeldsen K, Atar D, Kaski JC, Sechtem U, Tornvall P, on behalf of 
the WG on Cardiovascular Pharmacotherapy. ESC working group position paper on 
myocardial infarction with non-obstructive coronary arteries. European Heart Journal. 
2017;38:143–153.  

GENAMI PREVENTION Research protocol 
 
Protocol Version 3.0 
 
 
May 22, 2022 
 
 
34 
71.  Schmidt S, Vilagut G, Garin O, Cunillera O, Tresserras R, Brugulat P, Mompart A, Medina 
A, Ferrer M, Alonso J. Normas de referencia para el Cuestionario de Salud SF-12 versión 
2 basadas en población general de Cataluña. Medicina Clínica. 2012;139:613–625.  
72.  Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiatr 
Scand. 1983;67:361–370.  
73.  Cantero MC, López-Roig S, Rodríguez-Marín J, Gelabert M, Pastor M-Á, Reig MT. 
Propiedades psicométricas de la Escala Hospitalaria de Ansiedad y Estrés (HAD) en 
población española. Ansiedad y Estrés. 2007;13:163–176.  
74.  Zarit SH, Reever KE, Bach-Peterson J. Relatives of the impaired elderly: correlates of 
feelings of burden. Gerontologist. 1980;20:649–655.  
75.  Martin-Carrasco M, Otermin P, Pérez-Camo V, Pujol J, Agüera L, Martín MJ, Gobartt AL, 
Pons S, Balañá M. EDUCA study: Psychometric properties of the Spanish version of the 
Zarit Caregiver Burden Scale. Aging Ment Health. 2010;14:705–711.  
76.  Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Bäck M, Benetos A, Biffi A, 
Boavida J-M, 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 Scientific Document Group. 2021 ESC Guidelines on 
cardiovascular disease prevention in clinical practice: Developed by the Task Force for 
cardiovascular disease prevention in clinical practice with representatives of the European 
Society of Cardiology and 12 medical societies With the special contribution of the 
European Association of Preventive Cardiology (EAPC). European Heart Journal. 
2021;42:3227–3337.  
77.  Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication 
adherence measure in an outpatient setting. J Clin Hypertens (Greenwich). 2008;10:348–
354.  
78.  Schröder H, Fitó M, Estruch R, Martínez-González MA, Corella D, Salas-Salvadó J, 
Lamuela-Raventós R, Ros E, Salaverría I, Fiol M, Lapetra J, Vinyoles E, Gómez-Gracia E, 
Lahoz C, Serra-Majem L, Pintó X, Ruiz-Gutierrez V, Covas M-I. A short screener is valid 
for assessing Mediterranean diet adherence among older Spanish men and women. J 
Nutr. 2011;141:1140–1145.  
79.  Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, Pratt M, 
Ekelund U, Yngve A, Sallis JF, Oja P. International physical activity questionnaire: 12-
country reliability and validity. Med Sci Sports Exerc. 2003;35:1381–1395.  
80.  Bueno H, Bernal JL, Jiménez-Jiménez V, Martín-Sánchez FJ, Rossello X, Moreno G, Goñi 
C, Gil V, Llorens P, Naranjo N, Jacob J, Herrero-Puente P, Garrote S, Silla-Castro JC, 
Pocock SJ, Miró Ò. The Clinical outcomes, healthcare resource utilization, and related 
costs (COHERENT) model. Application in heart failure patients. Rev Esp Cardiol (Engl Ed). 
2021;S1885-5857(21)00259–0.