# Cardiovascular disease in North African women: insights from the Middle East African Women CardioVascular Disease (MEA-WCVD) registry

Salma Charfeddine, Leila Abid, Sarra Chenik, Iheb Ben Krayen, Oussama Haddar, Aymen Ghrab, Selim Boudiche, Haithem Touati, Oumaima Ayedi, Mohamed Amine Ammar, et al.

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## To cite this version:

Salma Charfeddine, Leila Abid, Sarra Chenik, Iheb Ben Krayen, Oussama Haddar, et al. Cardiovascular disease in North African women: insights from the Middle East African Women CardioVascular Disease (MEA-WCVD) registry. Frontiers in Cardiovascular Medicine, 2025, 12, pp.1577793. 10.3389/fcvm.2025.1577793. inserm-05353678

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## OPEN ACCESS

### EDITED BY

Alicia Del Saz Lara,
University of Castilla-La Mancha, Spain

### REVIEWED BY

Ariane Vieira Scarlatelli Macedo,
Santa Casa of Sao Paulo, Brazil
Sunny Goel,
Mount Sinai Hospital, United States
Fadoum Hassan,
National Health Fund, Djibouti

### *CORRESPONDENCE

Salma Charfeddine

selma_charfeddine@yahoo.fr

RECEIVED 16 February 2025

ACCEPTED 23 July 2025

PUBLISHED 08 September 2025

### CITATION

Charfeddine S, Abid L, Chenik S, Ben Krayen I, Haddar O, Ghrab A, Boudiche S, Touati H, Ayedi O, Ammar MA, Ben Halima M, Ben Ayed H, Brahim A, ElAyech F, Allouche E, Thabet H, Mahfoudhi H, Jabloun TY, Ayadi Y, Ayadi A, Romdhani G, Gargouri H, Zidi O, Guedri MA, Tili R, Trabelsi B, Hammami S, Othmen R, Antit S, Saidane S, Dardour S, Iddir S, Kharrat E, Cheikhrouhou A, Derwich M, Mrabet A, Lassoued T, Rekik E, Gmiha S, Laribi N, Lamine H, Triki Z, Ayari S, Boujelbene F, Boughzela E, Rekik H, Ben Ameur I, Abid S, Oueghlani K, Haggui A, Ben Halima A, Ouechtati W, Bennour E, Hammami R, Jabeur M, Zairi I, Drissa M, Addad F, Milouchi S, Mourali MS, Ben Slima H, Bezdah L, Neffati E, Ben Ameur Y, Kraiem S, Kachboura S, Kammoun I, Zakhama L, Ibn Hadj Amor H, Ben Hamda K, Messoudi Y, Ben Hlima N, Dahmani R, Gamra H, Ibn Elhadj Z, Denguir H, Ghorbel C, Mechri N, Ernez Hajri S, Mebazaa A, Ben Dhaou F, Trigui M, Fehri W and Abdessalem S (2025) Cardiovascular disease in North African women: insights from the Middle East African Women CardioVascular Disease (MEA-WCVD) registry.

Front. Cardiovasc. Med. 12:1577793.

doi: 10.3389/fcvm.2025.1577793

### COPYRIGHT

© 2025 Charfeddine, Abid, Chenik, Ben Krayen, Haddar, Ghrab, Boudiche, Touati, Ayedi, Ammar, Ben Halima, Ben Ayed, Brahim, ElAyech, Allouche, Thabet, Mahfoudhi, Jabloun, Ayadi, Ayadi, Romdhani, Gargouri, Zidi, Guedri, Tili, Trabelsi, Hammami, Othmen, Antit, Saidane, Dardour, Iddir, Kharrat, Cheikhrouhou, Derwich, Mrabet, Lassoued, Rekik, Gmiha, Laribi, Lamine, Triki, Ayari, Boujelbene, Boughzela, Rekik, Ben Ameur, Abid, Oueghlani, Haggui, Ben Halima,

# Cardiovascular disease in North African women: insights from the Middle East African Women CardioVascular Disease (MEA-WCVD) registry

Salma Charfeddine<fnref n="1" />*, Leila Abid<fnref n="1" />, Sarra Chenik², Iheb Ben Krayen³, Oussama Haddar<fnref n="1" />, Aymen Ghrab<fnref n="1" />, Selim Boudiche⁴, Haithem Touati³, Oumaima Ayedi<fnref n="1" />, Mohamed Amine Ammar⁵, Manel Ben Halima⁴, Houssem Ben Ayed², Asma Brahim⁴, Faten ElAyech⁶, Emna Allouche⁶, Houssem Thabet⁷, Houaida Mahfoudhi², Taha Yessine Jabloun², Yasmine Ayadi<fnref n="1" />, Alaeddine Ayadi⁸, Ghassen Romdhani⁹, Hassen Gargouri<fnref n="1" />, Oumayma Zidi¹⁰, Mohamed Ali Guedri⁹, Rami Tili¹⁰, Bechir Trabelsi⁹, Selim Hammami<fnref n="1" />, Rim Othmen⁹, Saoussen Antit¹¹, Syrine Saidane⁹, Sirine Dardour⁹, Skander Iddir⁹, Elmahdi Kharrat⁹, Anis Cheikhrouhou<fnref n="1" />, Mohamed Derwich<fnref n="1" />, Amal Mrabet⁹, Taha Lassoued³, Emna Rekik<fnref n="1" />, Sahar Gmiha<fnref n="1" />, Niez Laribi<fnref n="1" />, Hakim Lamine⁹, Zied Triki⁸, Samir Ayari⁵, Fatma Boujelbene¹², Essia Boughzela¹³, Hajer Rekik¹², Ines Ben Ameur¹², Syrine Abid¹³, Khalil Oueghlani¹⁴, Abddayem Haggui², Afef Ben Halima¹⁰, Wejdene Ouechtati⁶, Emna Bennour¹⁰, Rania Hammami<fnref n="1" />, Mariem Jabeur<fnref n="1" />, Ihsen Zairi⁹, Mariem Drissa⁸, Faouzi Addad¹³, Sami Milouchi³, Mohamed Sami Mourali⁴, Hedi Ben Slima⁵, Leila Bezdah⁶, Elyes Neffati⁷, Youssef Ben Ameur⁸, Sondos Kraiem⁹, Salem Kachboura¹⁰, Ikram Kammoun¹⁰, Lilia Zakhama¹¹, Hassen Ibn Hadj Amor¹⁵, Khaldoun Ben Hamda¹⁶, Yosra Messoudi¹⁷, Nejah Ben Hlima¹⁷, Rana Dahmani¹⁸, Habib Gamra¹⁹, Zied Ibn Elhadj²⁰, Hichem Denguir²¹, Chayma Ghorbel²², Nizar Mechri²³, Samia Ernez Hajri²⁴, Alexandre Mebazaa²⁵, Fedi Ben Dhaou²⁶, Maroua Trigui²⁶, Wafa Fehri² and Salem Abdessalem²⁷

<footnote n="1">¹Cardiology Department, Hedi Chaker University Hospital, Sfax, Tunisia, ²Cardiology Department, Military University Hospital, Tunis, Tunisia, ³Cardiology Department, Habib Bourguiba University Hospital, Medenine, Tunisia, ⁴Cardiology Department, La Rabta University Hospital, Tunis, Tunisia, ⁵Cardiology Department, Menzel Bourguiba University Hospital, Bizerte, Tunisia, ⁶Cardiology Department, Charles Nicolle University Hospital, Tunis, Tunisia, ⁷Cardiology Department, Sahloul University Hospital, Sousse, Tunisia, ⁸Cardiology Department, Mongi Slim La Marsa University Hospital, Tunis, Tunisia, ⁹Cardiology Department, Habib Thameur University Hospital, Tunis, Tunisia, ¹⁰Cardiology Department, Abderrahman Mami University Hospital, Ariana, Tunisia, ¹¹Cardiology Department, FSI La Marsa University Hospital, Tunis, Tunisia, ¹²Private Cardiologist, Sfax, Tunisia, ¹³Private Cardiologist, Tunis, Tunisia, ¹⁴Cardiology Department, Djerba Hospital, Medenine, Tunisia, ¹⁵Cardiology Department, Taher Sfar University Hospital, Mahdia, Tunisia, ¹⁶Cardiology Department B, Fattouma Bourguiba University Hospital, Monastir, Tunisia, ¹⁷Cardiology Department, Ibn El Jazzar University Hospital, Kairouan, Tunisia, ¹⁸Cardiology Department, Military Hospital, Bizerte, Tunisia, ¹⁹Cardiology Department</footnote>
Ouechtati, Bennour, Hammami, Jabeur, Zairi, Drissa, Addad, Milouchi, Mourali, Ben Slima, Bezdah, Neffati, Ben Ameur, Kraiem, Kachboura, Kammoun, Zakhama, Ibn Hadj Amor, Ben Hamda, Messoudi, Ben Hlima, Dahmani, Gamra, Ibn Elhadj, Denguir, Ghorbel, Mechri, Ernez Hajri, Mebazaa, Ben Dhaou, Trigui, Fehri and Abdessalem. This is an open-access article distributed under the terms of the [Creative Commons Attribution License (CC BY)](https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

A, Fattouma Bourguiba University Hospital, Monastir, Tunisia, ²⁰Cardiology Department, Taher Maamouri University Hospital, Nabeul, Tunisia, ²¹Cardiology Department, Gabes Hospital, Gabes, Tunisia, ²²Cardiology Department, Kasserine Hospital, Kasserine, Tunisia, ²³Cardiology Department, Tatouine Hospital, Tatouine, Tunisia, ²⁴Cardiology Department, Farhat Hached University Hospital, Sousse, Tunisia, ²⁵Department of Anesthesia and Critical Care, Lariboisière Hospital, Paris, France, ²⁶Preventive Department, Habib Bourguiba Hospital, Sfax Tunisia, ²⁷Cardiology Department, Pasteur Clinic, Tunis, Tunisia

Cardiovascular disease (CVD) is a major health burden worldwide, yet gender-specific data from the Middle East and North Africa (MENA) region remain scarce. The Middle East African Registry of Women with Cardiovascular Disease enrolled adult patients with coronary heart disease (CHD), heart failure (HF), atrial fibrillation (AF), or valvular heart disease (VHD) across Tunisia between May and July 2023. Of 15,366 patients, 37.6% were women. Compared with men, women were older, had lower socioeconomic status, and presented with more obesity, hypertension, diabetes, dyslipidemia, and sedentary lifestyle but smoked less. CHD was less frequent in women, while AF and VHD were more prevalent. Women underwent fewer coronary angiographies and percutaneous interventions, experienced longer delays, and received fewer guideline-based therapies, including dual antiplatelet agents and high-intensity statins. Among HF patients, women more often had preserved ejection fraction and higher hospitalization rates. These results highlight persistent gender inequities in CVD care in Tunisia.

KEYWORDS

cardiovascular disease, cardiovascular risk factors, women, heart failure, atrial fibrillation, coronary heart disease, valvular heart disease

## Introduction

Numerous studies have uncovered substantial disparities in cardiovascular health between men and women, as well as among different subsets of women (1-4). Despite this, a lack of data exists regarding the distinct features of cardiovascular disease in women within the Middle East North Africa (MENA) region (5, 6). This research gap has led to the underdiagnosis, undertreatment, and under-research of prevalent cardiovascular diseases (CVD), such as coronary heart disease (CHD), including ST-elevation myocardial infarction (STEMI), non-ST-elevation myocardial infarction (NSTEMI), and chronic coronary syndrome (CCS), heart failure (HF) with different phenotypes [preserved ejection fraction (HFpEF), mildly reduced (HFmrEF) or reduced ejection fraction (HFrEF)], valvular heart disease (VHD), and atrial fibrillation (AF), specifically in women.

## Methods

The Middle East African Registry Women CardioVascular Disease (MEA-WCVD) registry is a prospective observational multicentric international study. This publication will focus on the available Tunisian cohort across all governorates of Tunisia, including both public and private health sectors.

The enrolment for the MEA-WCVD registry [ClinicalTrials.gov](https://ClinicalTrials.gov) ID NCT05869214 was conducted in Tunisia from 10 May 2023 to 25 July 2023 and involved a one-shot visit.

The study protocol was in accordance with the Helsinki Convention, and the ethical considerations and registry approval

were obtained from the south Tunisian Persons' Protection Committee (PPC SUD N°0496/2023) (7).

Eligible patients are all incoming adult patients (≥18 years) with a confirmed diagnosis of the following CVDs: HF, CHD, AF, or VHD, who were admitted to participating centers during the study period.

All patients provided informed consent, and data were collected and stored in a certified health database, managed by our Contract Research Organization (CRO) (Eshmoun, Tunisia). All data were entered into an electronic data capture system with built-in validation rules to minimize entry errors.

Data included patients' demographics, medical history, diagnoses, pharmacological and device therapies focusing on accessibility to health facilities, insurance, time delay to optimal medical therapy, and adherence to guideline-oriented management.

Data were assessed using a standardized questionnaire administered at the time of patient enrolment.

We excluded patients with incomplete medical records or those who declined participation.

The main goal of this paper is to report gender-based disparities in CVD management in Tunisia.

## Results

### Baseline characteristics

Among the 15,366 included patients [CHD *n* = 7,870 (51.2%), HF *n* = 3,857 (25.1%), AF *n* = 2,715 (17.7%), and VHD *n* = 924 (6%)], 37.6% (*n* = 5,773) were female. CHD was significantly lower [2,238 (38.8%) vs. 5,632 (58.7%), *p* < 10<sup>-3</sup>], and AF and VHD were
significantly higher [AF, 1,580 (27.4%) vs. 1,135 (11.8%), *p* < 10<sup>-3</sup>; VHD, 546 (9.5%) vs. 378 (3.9%), *p* < 10<sup>-3</sup>] in women and did not differ in HF [1,409 (24.4%) vs. 2,448 (25.5%), *p* = 0.124].

In the overall population, compared with men, women were older {67 years old [IQR = (59–76) vs. 64 years old [IQR = (56–71)], *p* = <10<sup>-3</sup>}, had lower educational level [none or only elementary school certificate 4,341 (75.6%) vs. 4,313 (45.1%), *p* < 10<sup>-3</sup>], lower income (<150 euro per month) [2,752 (47.9%) vs. 2,052 (21.5%), *p* < 10<sup>-3</sup>], relied more on financial family support [4,087 (70.8%) vs. 1,746 (28.2%), *p* < 10<sup>-3</sup>], and had more basic medical insurance [1,529 (26.6%) vs. 1,940 (20.3%), *p* < 10<sup>-3</sup>] (Figure 1).

## Clinical presentation

Regarding CV risk factors (CVRF), women were more obese [1,458 (25.3%) vs. 905 (9.4%), *p* < 10<sup>-3</sup>] with higher

prevalences of hypertension [3,587 (62.1%) vs. 4,694 (48.9%), *p* < 10<sup>-3</sup>], diabetes [2,549 (44.2%) vs. 3,883 (40.5%), *p* < 10<sup>-3</sup>], dyslipidemia [1,934 (33.5%) vs. 2,897 (30.2%), *p* < 10<sup>-3</sup>], and sedentary lifestyle [<1 h physical activity per week: 3,599 (62.7%) vs. 4,531 (47.5%), *p* < 10<sup>-3</sup>] and were less smokers [125 (2.2%) vs. 2,750 (28.7%), *p* < 10<sup>-3</sup>]. These differences in CVRF were almost the same in CHD and HF (Figure 1).

## Management and outcomes

Regarding CHD, compared with men, women presented less likely with STEMI [373 (16.7%) vs. 1,520 (27.1%), *p* < 10<sup>-3</sup>] and more likely with either NSTEMI [940 (42.2%) vs. 2,276 (40.6%), *p* = 0.198] or CCS [916 (41.1%) vs. 1,812 (32.2%), *p* = 10<sup>-3</sup>]. In the acute coronary syndrome (ACS) setting, women were more likely either with no [432 (19.3%) vs. 659 (11.7%), *p* < 10<sup>-3</sup>] or

<figure><img src="image_4.png" /></figure>
delayed time to coronary angiography [>48 h: 765 (34.2%) vs. 1,694 (30.1%), *p* < 10⁻³] (Figure 1).

Women were less likely to undergo percutaneous coronary intervention (PCI) [no PCI: 45 (12.1%) vs. 111 (7.3%), *p* = 0.003] and less radial access [1,598 (71.7%) vs. 4,544 (81.2%), *p* < 10⁻³].

Although revascularization delay was almost the same in the STEMI setting [delay <12 h: 258 (69.4%) vs. 1,128 (74.4%), *p* = 0.05], women received less dual antiplatelet therapy (DAPT), less P2Y12 inhibitors [clopidogrel: 1,166 (52.3%) vs. 3,162 (56.5%), *p* = 10⁻³] and less high-intensity statins [1,559 (70%) vs. 4,294 (76.7%), *p* < 10⁻³].

Regarding HF, compared with men, women presented more likely with preserved ejection fraction [HFpEF: 479 (34%) vs. 388 (15.8%), *p* < 10⁻³; HFmrEF: 354 (25.1%) vs. 570 (23.3%), *p* = 0.197; and HFrEF: 563 (40%) vs. 1,477 (60.3%), *p* < 10⁻³], less ischemic etiology [537 (38.1%) vs. 1,497 (60.9%), *p* < 10⁻³], and more valvular, hypertensive, and arrythmia causes [161 (11.4%) vs. 188 (7.7%), 268 (19%) vs. 154 (6.3%), and 153 (10.9%) vs. 135 (5.5%), *p* < 10⁻³ respectively].

In the HFrEF subgroup, guideline-oriented medical therapy compared equally in angiotensin-converting enzyme inhibitors (ACE)/angiotensin receptor blockers (ARB) [407 (72.3%) vs. 1,097 (74.3%), *p* = 0.364], beta-blockers [477 (84.7%) vs. 1,269 (85.9%), *p* = 0.493], and mineralocorticoid receptor antagonists (MRA) [342 (60.7%) vs. 910 (61.6%), *p* = 0.720]. However, access to more costly drugs including sacubitril–valsartan and SGLT2 inhibitors was lower in women [25 (4.4%) vs. 101 (6.8%), *p* = 0.044, and 178 (31.6%) vs. 530 (35.9%), *p* = 0.07, respectively].

Women were more prone to have HF hospitalization, the last year before inclusion [360 (64.1%) vs. 873 (59.1%), *p* = 0.043].

Discussion and conclusions

This large Tunisian registry outlined the fact that compared with men, women with CVD presented unexpectedly with more CVRF aside from tobacco. They had low or unstable financial resources or no basic health insurance. In the CHD setting, access to coronary angiography, PCI, and optimal medical therapy was significantly lower and delayed. In the HF setting, compared with the NATURE-HF registry (8), guideline-oriented therapies improved in both genders. New pillars are still less prescribed and especially in women. This may explain the higher rate of HF hospitalization in women with HFrEF.

These recent findings highlight the need for healthcare stakeholders to develop and execute strategies to combat the burden of CVD among women in the MEA region. In Tunisia, several initiatives aim to reduce disparities in cardiovascular care, including national screening programs for hypertension and diabetes, expanded access to primary care in underserved areas, and policy efforts to improve emergency cardiovascular services. However, barriers remain, particularly in access to specialized care and invasive procedures. A national Tunisian registry focusing on secondary cardiovascular prevention with a follow-

up of patients with CHD is currently underway, and we intend to report these outcomes in a subsequent publication.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by the south Tunisian Persons’ Protection Committee (PPC SUD N°0496/2023). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

SCha: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. LA: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – review & editing. SChe: Conceptualization, Investigation, Methodology, Supervision, Validation, Visualization, Writing – review & editing. IBK: Conceptualization, Data curation, Investigation, Methodology, Project administration, Validation, Visualization, Writing – review & editing. OH: Data curation, Investigation, Resources, Validation, Visualization, Writing – review & editing. AG: Conceptualization, Data curation, Investigation, Methodology, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing. SB: Conceptualization, Data curation, Investigation, Methodology, Resources, Visualization, Writing – review & editing. HaT: Conceptualization, Funding acquisition, Investigation, Project administration, Resources, Visualization, Writing – review & editing. OA: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Resources, Visualization, Writing – review & editing. MA: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Visualization, Writing – review & editing. MB: Data curation, Funding acquisition, Investigation, Methodology, Resources, Validation, Writing – review & editing. HBA: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Writing – review & editing. AB: Conceptualization, Data curation, Funding acquisition, Resources, Supervision, Writing – review & editing. FE: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – review & editing. EA: Conceptualization, Methodology, Supervision, Validation, Visualization, Writing – review & editing. HoT: Data curation, Formal analysis, Investigation, Methodology, Resources, Visualization, Writing – review & editing. HM: Data curation,
Funding acquisition, Methodology, Project administration, Validation, Writing - review & editing. TJ: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Supervision, Visualization, Writing - review & editing. YA: Conceptualization, Data curation, Funding acquisition, Project administration, Supervision, Visualization, Writing - review & editing. AA: Data curation, Funding acquisition, Project administration, Software, Validation, Visualization, Writing - review & editing. GR: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Visualization, Writing - review & editing. HGar: Conceptualization, Formal analysis, Investigation, Resources, Supervision, Visualization, Writing - review & editing. OZ: Conceptualization, Data curation, Funding acquisition, Resources, Validation, Visualization, Writing - review & editing. MG: Conceptualization, Data curation, Funding acquisition, Methodology, Resources, Visualization, Writing - review & editing. RT: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Software, Visualization, Writing - review & editing. BT: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing - review & editing. SH: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Validation, Visualization, Writing - review & editing. RO: Conceptualization, Data curation, Formal analysis, Funding acquisition, Resources, Software, Validation, Visualization, Writing - review & editing. SAN: Conceptualization, Data curation, Funding acquisition, Methodology, Supervision, Visualization, Writing - review & editing. SS: Conceptualization, Data curation, Investigation, Methodology, Supervision, Visualization, Writing - review & editing. SD: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Visualization, Writing - review & editing. SI: Data curation, Formal analysis, Funding acquisition, Methodology, Resources, Supervision, Writing - review & editing. EK: Conceptualization, Data curation, Methodology, Validation, Visualization, Writing - review & editing. AC: Conceptualization, Data curation, Investigation, Methodology, Supervision, Visualization, Writing - review & editing. MoD: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Software, Visualization, Writing - review & editing. AmM: Conceptualization, Data curation, Methodology, Validation, Visualization, Writing - review & editing. TL: Conceptualization, Data curation, Funding acquisition, Resources, Visualization, Writing - review & editing. ER: Conceptualization, Data curation, Investigation, Resources, Validation, Writing - review & editing. SG: Data curation, Formal analysis, Funding acquisition, Methodology, Visualization, Writing - review & editing. NL: Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - review & editing. HL: Conceptualization, Data curation, Investigation, Methodology, Resources, Visualization, Writing - review & editing. ZT: Conceptualization, Data curation, Funding acquisition, Resources, Validation, Visualization, Writing - review & editing. SAY: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Validation, Visualization, Writing - review & editing. FB: Conceptualization, Data curation, Funding acquisition,

Methodology, Validation, Visualization, Writing - review & editing. EsB: Conceptualization, Data curation, Formal analysis, Software, Supervision, Visualization, Writing - review & editing. HR: Conceptualization, Data curation, Funding acquisition, Resources, Supervision, Validation, Visualization, Writing - review & editing. IBA: Conceptualization, Data curation, Formal analysis, Methodology, Resources, Supervision, Visualization, Writing - review & editing. SAb: Conceptualization, Data curation, Investigation, Resources, Validation, Visualization, Writing - review & editing. KO: Conceptualization, Data curation, Investigation, Resources, Software, Supervision, Visualization, Writing - review & editing. AH: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Supervision, Writing - review & editing. ABH: Conceptualization, Data curation, Funding acquisition, Investigation, Validation, Visualization, Writing - review & editing. WO: Conceptualization, Data curation, Investigation, Methodology, Visualization, Writing - review & editing. EmB: Conceptualization, Data curation, Funding acquisition, Resources, Software, Validation, Writing - review & editing. RH: Conceptualization, Data curation, Investigation, Methodology, Writing - review & editing, Visualization. MJ: Data curation, Funding acquisition, Methodology, Resources, Validation, Visualization, Writing - review & editing. IZ: Data curation, Methodology, Project administration, Validation, Visualization, Writing - review & editing. MaD: Conceptualization, Data curation, Funding acquisition, Project administration, Supervision, Writing - review & editing. FA: Conceptualization, Investigation, Methodology, Project administration, Resources, Validation, Writing - review & editing. SM: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Software, Supervision, Writing - review & editing. MM: Conceptualization, Data curation, Investigation, Methodology, Project administration, Software, Supervision, Writing - review & editing. HBS: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing - review & editing. LB: Data curation, Formal analysis, Project administration, Software, Supervision, Validation, Writing - review & editing. EN: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Software, Validation, Writing - review & editing. YB: Conceptualization, Data curation, Investigation, Methodology, Project administration, Resources, Supervision, Writing - review & editing. SoK: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Software, Supervision, Visualization, Writing - review & editing. SaK: Conceptualization, Data curation, Investigation, Project administration, Resources, Supervision, Validation, Writing - review & editing. IK: Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing - review & editing. LZ: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Writing - review & editing. Hl: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing - review & editing. KB: Data curation, Funding acquisition, Investigation, Methodology, Project administration, Writing - review & editing. YM: Conceptualization, Data curation,
Funding acquisition, Resources, Software, Supervision, Validation, Writing - review & editing. NB: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Resources, Writing - review & editing. RD: Conceptualization, Data curation, Formal analysis, Investigation, Project administration, Resources, Software, Supervision, Writing - review & editing. HGam: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Resources, Software, Validation, Writing - review & editing. ZI: Conceptualization, Data curation, Funding acquisition, Methodology, Resources, Software, Supervision, Writing - review & editing. HD: Conceptualization, Data curation, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing - review & editing. CG: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing - review & editing. NM: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Software, Supervision, Visualization, Writing - review & editing. SE: Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing - review & editing. AIM: Conceptualization, Data curation, Investigation, Methodology, Project administration, Software, Supervision, Writing - review & editing. FBD: Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Writing - review & editing. MT: Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Writing - review & editing. WF: Conceptualization, Data curation, Funding acquisition, Investigation, Resources, Supervision, Validation, Writing - review & editing. SaA: Writing - review & editing, Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Software, Supervision, Validation, Visualization.

## Funding

The author(s) declare that financial support was received for the research and/or publication of this article. The MEA-WCVD

registry was initiated and supported by the Tunisian Society of Cardiology and Cardiovascular Surgery (STCCCV) as a national initiative aimed at collecting comprehensive data on women with cardiovascular disease. The registry was conducted under the auspices of the STCCCV and utilized a certified electronic health database to ensure the accuracy and integrity of the collected data. The data management and operational oversight were carried out by our Contract Research Organization (CRO), Eshmoun Clinical Research, based in Tunisia, which ensured compliance with ethical standards and data protection regulations throughout the study.

## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

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