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European Heart Journal Open logoLink to European Heart Journal Open
. 2026 Jun 17;6(4):oeag100. doi: 10.1093/ehjopen/oeag100

Overview of methodology and characteristics of national acute coronary syndrome registries in high-income countries: a scoping review

Justine Chan 1,2,3, Natalie Ward 4,5, Judith Finn 6,7,8,9, Adil Rajwani 10,11,12, Jing Pang 13,14, Mikhail Alexander 15, Khang Duong Nguyen 16,17, Jyoti Sharma 18,19,20,21, Carl Schultz 22,23, Gerald F Watts 24,25, Markus P Schlaich 26,27,28, Christopher M Reid 29,30, Graham S Hillis 31,32,✉,b
PMCID: PMC13322397  PMID: 42388334

Abstract

Aims

The role of clinical quality registries is to collect structured observational data in routine clinical practice to monitor the quality of care provided to specific patient populations. There is currently no standardized methodology of how to establish registry platforms. The objective of this scoping review is to provide an overview of the methodology and characteristics of established national acute coronary syndrome registries.

Methods and results

Three electronic databases were searched to identify national registries in high-income countries collecting routine clinical data on adult patients with suspected and/or diagnosed acute coronary syndrome. Articles published from the year 2000 onwards that described the protocol and/or quantitative results of such registries located in 25 countries with the largest gross domestic product were included. There were 24 countries with an established national registry, of which nine are currently active. Inclusion criteria varied across these registries, with a predominant focus on either a suspected or confirmed diagnosis of acute coronary syndrome or myocardial infarction. The primary clinical outcomes measured were all-cause mortality and major adverse cardiovascular events during hospitalization, as well as at 30-day and/or 1 year time points. The main sources of follow-up data were hospital discharge records and administrative data.

Conclusion

Globally, acute coronary syndrome clinical quality registries share similar fundamental objectives of monitoring and improving or sustaining the highest quality of care. However, there is considerable variation in the design of national registries and better harmonization of fundamental issues, such as who is included, core data, and key outcomes, would be beneficial.

Keywords: Acute coronary syndrome, Myocardial infarction, Clinical quality registry, Quality improvement, Scoping review

Graphical Abstract

Graphical Abstract.

For image description, please refer to the figure legend and surrounding text.

Introduction

Cardiovascular disease (CVD) is the leading cause of death globally, with ischaemic heart disease (IHD) being the primary contributor to premature mortality around the world.1,2 Acute coronary syndromes (ACS) are the largest subset of IHD and encompass both unstable angina (UA) and myocardial infarction (MI).3–6 Over the past 20 years, there has been a steep decline in age-standardized mortality rates associated with ACS in high-income countries (HIC).1 Nevertheless, survivors of ACS still have a significantly higher mortality risk than the general population.1,2 Therefore, patient clinical quality registries (CQR) at the local, national, and/or multinational levels have been established to collect real-world observational data related to treatment, management, and outcomes7–9 of high-risk diseases, such as ACS.4–6

The primary purpose of disease-specific CQR is to improve health-related outcomes at both the individual and population levels.8–10 They are also designed to explore the association between specific interventions and patient outcomes.7–9 In many well-established ACS registries, it is evident that the scope, rationale, and objectives have been clearly defined to achieve this purpose.11–15 Therefore, the main aim of ACS registries is to objectively measure the quality of care delivered to hospitalized patients and subsequently implement quality improvement (QI) strategies to improve short- and long-term patient outcomes.11–15 Routine clinical information is collected and captured throughout the ACS patient journey from admission to discharge, including key variables, such as demographic data, investigations, and treatments.11–15 As a result of successful implementation of such CQR, the global landscape of health services research and scientific research in acute cardiovascular (CV) medicine has dramatically changed in recent years.8

There is no international framework or guidelines for the establishment, management, and governance structure of ACS CQR, though the general characteristics of ACS registry design have been previously summarized from a global perspective.16 Therefore, the overall aim of this scoping review (ScR) is to provide an overview of the methodology of contemporary national ACS registries in HIC. Specifically, we will summarize the objectives, design, and outcome measures of these established registries to inform and improve the development of current and future ACS registries.

Methods

Protocol and registration

This review was conducted in accordance with ScR guidelines by the Joanna Briggs Institute (JBI)17,18 and has been written in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRIMSA-ScR).19 The protocol for this ScR was prospectively registered with the Open Sciences Framework on 7 November 2024.20

Eligibility criteria

To be included in this ScR, eligible journal articles needed to report on the methodology of CQR focusing on routine clinical data obtained from adult patients diagnosed with suspected and/or confirmed diagnosis of ACS (see Supplementary material online, Table S1). Suspected ACS was defined as signs and symptoms suggestive of an acute coronary event, and ACS is a confirmed diagnosis of UA, ST elevation MI (STEMI), or non-STEMI (NSTEMI).3–6 The search was restricted to national CQR from 25 countries with the largest gross domestic product (GDP).21 The search was further limited to original articles published in peer-reviewed journals from year 2000 onwards with full-text availability in English.

Search strategy

A literature search was conducted according to predefined search strategies (see Supplementary material online, Table S2) in databases of MEDLINE, CINAHL, and Embase on 7 July 2025 and updated on 22 April 2026.

Selection of sources of evidence

All journal articles identified by the search strategy were imported into Covidence. Hand searching of grey literature was also conducted to identify any potentially missing national ACS CQR not identified during the initial search. Duplicate articles were automatically removed by Covidence. Initially, a single reviewer (J.C.) screened all titles and abstracts against eligibility criteria. Duplicate records were manually removed during the screening stage. All eligible studies identified during the screening stage were then further assessed at a full-text stage by two reviewers (J.C. and N.W.). Any disagreements between the independent reviewers were resolved by discussion, and where there was ongoing disagreement or uncertainty, a third independent reviewer made the final decision (G.S.H.). If there were multiple publications for a single national CQR, only the earliest journal article describing the methodology was included. To confirm the methodology of CQR, additional contemporary journal articles were sought. The full-text articles identified at this stage were included for data extraction.

Data charting process, data items, and synthesis of results

A standardized data extraction form was generated to determine the year of establishment of the CQR, methodology of data collection, objectives, and health outcomes measured (see Supplementary material online, Table S3). Methodology and characteristics were captured directly from journal articles, annual reports, and registry websites into a data extraction form in Microsoft Excel.

Results

Selection of sources of evidence

The initial literature search identified 10 407 journal articles (Figure 1). A total of 78 articles fulfilled the eligibility criteria; however, 31 articles were excluded due to data collection from regional and/or multinational ACS registries, incomplete methodology presented, and multiple publications from a single national registry. Therefore, 48 national ACS CQR were included in this ScR (see Supplementary material online, Table S4).

Figure 1.

For image description, please refer to the figure legend and surrounding text.

Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews flowchart.

Identified registries

All HIC were identified as having an established national ACS registry, with Ireland being the exception (Figure 2). Some of these national registries (9/24) are currently active, i.e. data collection is ongoing at the time of ScR publication. However, it is noted that only CQR with published peer-reviewed original articles were included in this ScR.

Figure 2.

For image description, please refer to the figure legend and surrounding text.

Global overview of national acute coronary syndrome clinical quality registries in 25 countries with the largest gross domestic product.

Patient consent and enrolment

Some registries required mandatory data collection of eligible patients (n = 4/48), of which all are partially or fully funded by their national government (Table 1; Supplementary material online, Table S5). The majority of national registries required informed written consent from eligible patients (n = 37/48). Additionally, enrolment of ACS patient cohorts varied across registries, with a predominant focus on either suspected diagnosis of ACS (n = 10/48) or MI diagnoses alone (n = 29/48).

Table 1.

Patient consent and enrolment

Acronym Funding Consent Type of ACS Enrolment
Government Industry Research grant Cardiovascular organization NGO Signed Waiver Opt out Unknown Suspected STEMI NSTEMI UA Mandatory Consecutive Snapshota
ARGEN-IAM-ST ☑ ☑ ☑ ☑
ACACIA ☑ ☑ ☑ ☑ ☑ ☑
CONCORDANCE ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
Belgium STEMI Database ☑ ☑ ☑ ☑
BRACE ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
ACCEPT ☑ ☑ ☑ ☑
CANRACE ☑ ☑ ☑ ☑
C-ACS I, II ☑ ☑ ☑ ☑ ☑ ☑
China-PEACE ☑ ☑ ☑ ☑ Random representative sample
CAMI ☑ ☑ ☑ ☑ ☑
CCC-ACS ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
USIC ☑ ☑ ☑ ☑ ☑ ☑
FAST-MI ☑ ☑ ☑ ☑ ☑ ☑ ☑
ACOS Unknown ☑ ☑ ☑ ☑ ☑
CREATE ☑ ☑ ☑ ☑
One ACS Registry ☑ ☑ ☑ ☑ ☑
BLITZ ☑ ☑ ☑ ☑ ☑ ☑ ☑
BLITZ-2 ☑ ☑ ☑ ☑ ☑
BLITZ-4 ☑ ☑ ☑ ☑ ☑ ☑
MANTRA ☑ ☑ ☑ ☑ ☑ ☑ ☑
EYESHOT ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
JAMIR ☑ ☑ ☑ ☑ ☑ ☑
RENASICA II ☑ ☑ ☑ ☑
RENASICA III ☑ ☑ ☑ ☑
RENASCA IMSS ☑ ☑ ☑ ☑ ☑ ☑
FORCE-ACS ☑ ☑ ☑ ☑ ☑ ☑
PL-ACS ☑ ☑ ☑ ☑ ☑ ☑ ☑
AMI-PL ☑ ☑ ☑ ☑ ☑ ☑
RusACSR ☑ ☑ ☑ ☑ ☑
STARS-1 Program ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
STARS-2 Program ☑ ☑ ☑ ☑ ☑ ☑ ☑
KAMIR ☑ ☑ ☑ ☑ ☑ ☑
KorMI ☑ ☑ ☑ ☑ ☑ ☑
KAMIR-NIH ☑ ☑ ☑ ☑ ☑ ☑ ☑
DESCARTES ☑ ☑ ☑ ☑ ☑ ☑
MASCARA ☑ ☑ ☑ ☑ ☑ ☑
DIOCLES ☑ ☑ ☑ ☑ ☑
SWEDEHEART ☑ ☑ ☑ ☑ ☑
AMIS Plus ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
TURK-AKS ☑ ☑ ☑ ☑ ☑ ☑
TURKMI ☑ ☑ ☑ ☑ ☑ ☑ ☑
PRAIS-UK ☑ ☑ ☑ ☑ ☑ ☑ ☑
MINAP ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
ACTION Registry–GWTG ☑ ☑ ☑ ☑ ☑ ☑ ☑

Objectives

The primary objective for all CQR was to describe clinical characteristics, management, and outcomes of their patient cohort (Table 2). Many registries also aimed to quantify clinician and/or hospital adherence to local ACS guidelines (n = 25/48). Furthermore, they frequently focused on prospective (n = 42/48) and longitudinal (n = 21/48) monitoring of quality of care.

Table 2.

Objectives

Acronym Objectives
Measure quality of care Hospital benchmarking Describe clinical characteristics, management, and outcomes Monitor longitudinal changes in care Risk stratification Adherence to guidelines Platform for registry-based trials Platform for sub-registries Platform for biobank
ARGEN-IAM-ST ☑ ☑ ☑
ACACIA ☑ ☑ ☑
CONCORDANCE ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
Belgium STEMI Database ☑ ☑ ☑ ☑ ☑
BRACE ☑ ☑ ☑
ACCEPT ☑ ☑ ☑
CANRACE ☑ ☑
C-ACS I, II ☑ ☑ ☑
China-PEACE ☑ ☑ ☑ ☑
CAMI ☑ ☑ ☑
CCC-ACS ☑ ☑ ☑ ☑
USIC ☑ ☑ ☑
FAST-MI ☑ ☑ ☑ ☑
ACOS ☑
CREATE ☑
One ACS Registry ☑
BLITZ ☑
BLITZ-2 ☑ ☑
BLITZ-4 ☑ ☑ ☑
MANTRA ☑ ☑
EYESHOT ☑ ☑ ☑
JAMIR ☑
RENASICA II ☑ ☑
RENASICA III ☑ ☑ ☑ ☑
RENASCA IMSS ☑
FORCE-ACS ☑ ☑ ☑ ☑ ☑ ☑ ☑
PL-ACS ☑ ☑ ☑ ☑
AMI-PL ☑ ☑
RusACSR ☑ ☑
STARS-1 Program ☑ ☑ ☑
STARS-2 Program ☑ ☑ ☑
KAMIR ☑ ☑ ☑
KorMI ☑ ☑ ☑
KAMIR-NIH ☑ ☑
DESCARTES ☑
MASCARA ☑
DIOCLES ☑
SWEDEHEART ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
AMIS Plus ☑ ☑ ☑ ☑ ☑ ☑
TURK-AKS ☑
TURKMI ☑ ☑ ☑
PRAIS-UK ☑ ☑
MINAP ☑ ☑ ☑ ☑ ☑ ☑ ☑
ACTION Registry–GWTG ☑ ☑ ☑ ☑ ☑ ☑

Data collection

The majority of ACS registries were designed to collect data prospectively (Table 3). Telephone interviews were frequently used to determine patient outcomes post discharge for ‘active’ follow-up (n = 17/48). By contrast, in registries with ‘passive’ follow-up, patient outcomes were investigated predominantly at either or both 1 month (n = 6/14) and 1 year (n = 8/14).

Table 3.

Data collection

Acronym Registry data collection Data entry Type of follow-up Sources of data Outcome and/or follow-up time points
Prospective Retrospective Data dictionary Soft Hard Active Passive Primary care records Tertiary care records Telephone None 1 month 6 months 1 year 2 years Other
ARGEN-IAM-ST ☑ ☑ ☑ ☑ ☑ ☑
ACACIA ☑ Unknown ☑ ☑ ☑ ☑
CONCORDANCE ☑ ☑ ☑ ☑ ☑ ☑ ☑
Belgium STEMI Database ☑ ☑ N/A ☑ ☑
BRACE ☑ ☑ N/A ☑ ☑
ACCEPT ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
CANRACE ☑ ☑ N/A ☑ ☑
C-ACS I, II ☑ ☑ ☑ ☑ ☑ ☑
China-PEACE ☑ ☑ N/A ☑ ☑
CAMI ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ 18 months
CCC-ACS ☑ ☑ N/A ☑ ☑
USIC ☑ ☑ N/A ☑ ☑
FAST-MI ☑ ☑ ☑ ☑ ☑ ☑ Up to 10 years
ACOS ☑ ☑ N/A ☑ ☑
CREATE ☑ Unknown ☑ ☑ ☑
One ACS Registry ☑ ☑ N/A ☑ ☑
BLITZ ☑ ☑ ☑ ☑ ☑
BLITZ-2 ☑ ☑ ☑ ☑ ☑
BLITZ-4 ☑ ☑ ☑ ☑ ☑ ☑
MANTRA ☑ ☑ ☑ ☑ ☑ ☑
EYESHOT ☑ ☑ N/A ☑ ☑
JAMIR ☑ ☑ ☑ ☑ ☑
RENASICA II ☑ ☑ N/A ☑ ☑
RENASICA III ☑ ☑ ☑ ☑ ☑ ☑
RENASCA IMSS ☑ ☑ N/A ☑ ☑
FORCE-ACS ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ 3 years
PL-ACS ☑ ☑ ☑ ☑ ☑ 3 years
AMI-PL ☑ ☑ ☑ ☑ ☑ 5 years
RusACSR ☑ ☑ ☑ ☑ ☑ ☑
STARS-1 Program ☑ ☑ ☑ ☑ ☑ ☑ ☑
STARS-2 Program ☑ ☑ ☑ ☑ ☑
KAMIR ☑ ☑ ☑ ☑ ☑
KorMI ☑ ☑ ☑ ☑ ☑
KAMIR-NIH ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ 3 years
DESCARTES ☑ ☑ ☑ ☑ ☑ ☑ ☑
MASCARA ☑ ☑ ☑ ☑ ☑ ☑ ☑
DIOCLES ☑ ☑ ☑ ☑ ☑
SWEDEHEART ☑ ☑ ☑ ☑ ☑ ☑ ☑
AMIS Plus ☑ ☑ ☑ ☑ ☑ ☑ ☑ 3 months
TURK-AKS ☑ Unknown N/A ☑ ☑
TURKMI ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
PRAIS-UK ☑ ☑ ☑ ☑ ☑
MINAP ☑ ☑ ☑ ☑ ☑ ☑ ☑
ACTION Registry–GWTG ☑ ☑ ☑ N/A ☑ ☑

Outcomes

The main outcome measured in all ACS CQR was all-cause mortality during hospitalization (Table 4). Major adverse cardiovascular events (MACE) were also measured during hospitalization (n = 45/48) and/or after discharge (n = 30/48). The primary source of outpatient outcomes was by tertiary hospital discharge records, and in a few registries through administrative data linkage to government mortality records (n = 7/48).

Table 4.

Outcomes

Acronym Type of outcomes Measurable outcomes Administrative data linkage
Inpatient Outpatient All-cause mortality Major adverse cardiovascular events Medication adherence Quality of life Referral to cardiac rehabilitation Hospitalization records Mortality records Pharmaceutical records
ARGEN-IAM-ST ☑ ☑ ☑ ☑
ACACIA ☑ ☑ ☑ ☑ ☑ ☑
CONCORDANCE ☑ ☑ ☑ ☑ ☑ ☑ ☑
Belgium STEMI Database ☑ ☑
BRACE ☑ ☑ ☑
ACCEPT ☑ ☑ ☑ ☑ ☑
CANRACE ☑ ☑ ☑
C-ACS I, II ☑ ☑ ☑ ☑ ☑
China-PEACE ☑ ☑ ☑
CAMI ☑ ☑ ☑ ☑ ☑
CCC-ACS ☑ ☑ ☑
USIC ☑ ☑ ☑
FAST-MI ☑ ☑ ☑ ☑ ☑ ☑
ACOS ☑ ☑ ☑
CREATE ☑ ☑ ☑ ☑
One ACS Registry ☑ ☑ ☑
BLITZ ☑ ☑ ☑ ☑
BLITZ-2 ☑ ☑ ☑ ☑
BLITZ-4 ☑ ☑ ☑ ☑ ☑ ☑
MANTRA ☑ ☑ ☑ ☑
EYESHOT ☑ ☑ ☑
JAMIR ☑ ☑ ☑ ☑
RENASICA II ☑ ☑ ☑
RENASICA III ☑ ☑ ☑ ☑
RENASCA IMSS ☑ ☑ ☑
FORCE-ACS ☑ ☑ ☑ ☑ ☑ ☑
PL-ACS ☑ ☑ ☑ ☑
AMI-PL ☑ ☑ ☑ ☑ ☑ ☑
RusACSR ☑ ☑ ☑
STARS-1 Program ☑ ☑ ☑ ☑
STARS-2 Program ☑ ☑
KAMIR ☑ ☑ ☑ ☑ ☑
KorMI ☑ ☑ ☑ ☑
KAMIR-NIH ☑ ☑ ☑ ☑ ☑
DESCARTES ☑ ☑ ☑ ☑
MASCARA ☑ ☑ ☑ ☑
DIOCLES ☑ ☑ ☑ ☑
SWEDEHEART ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑ ☑
AMIS Plus ☑ ☑ ☑ ☑ ☑ ☑ ☑
TURK-AKS ☑ ☑
TURKMI ☑ ☑ ☑ ☑ ☑ ☑
PRAIS-UK ☑ ☑ ☑ ☑
MINAP ☑ ☑ ☑ ☑ ☑
ACTION Registry–GWTG ☑ ☑ ☑

Discussion

This ScR summarized the methodology and characteristics of established national ACS CQR in HIC, specifically focusing on their design, objectives, and outcomes. Since 2000, all 25 countries with the highest GDP had established national ACS registries, except for Ireland. Currently, nine of these national registries are actively collecting data.11–13,22–27 The remaining national registries are either no longer operational or captured data at specific ‘snapshots’ in time.

Thirteen CQR had a publicly available protocol, published either in a peer-reviewed journal or on a website.11–13,15,23–26,28–32 Patient cohorts varied across registries, with some enrolling patients with suspected ACS,28,33–37 while others focused on MI alone.14,15,22,25,31,32,38–53 Regardless, the main objective for all registries was to report on clinical characteristics, management, and outcomes of their patient cohort. Some registries also adopted a specific focus on measuring ‘quality of care’, as well as others that support clinical research, including implementation of registry-based randomized clinical trials (RCT).

The main outcome measured for all CQR was all-cause mortality during initial hospitalization. However, few registries explicitly defined in-hospital MACE outcomes,24,28,29,54–56 and these definitions varied. Instead of common MACE endpoints used in CV RCT, such as recurrent MI, stroke, CV death, UA, and heart failure,57 several other complications were also included as outcomes. These included individual and/or composite endpoints of stent thrombosis, cardiogenic shock, acute renal failure, and more. Regardless of the chosen outcomes, they were predominantly measured at either or both 30-days and 1-year. To do so, many well-established and government-mandated registries linked their registry platform to administrative datasets to allow comprehensive data capture.11,12,14,24,26,30,38,42,43

There are several limitations to this ScR. Firstly, the focus on national ACS CQR in 25 countries with the largest GDP may mean that the findings are not representative. It may also reduce heterogeneity in aspects such as infrastructure, linkage capacity, and data quality. Despite this, clear differences in design were observed. These might, however, be greater if CQR from middle- and lower-income countries were also considered. In addition, given the focus on HIC, we determined that an overview of registry design through a ScR was more appropriate than a systematic review. Furthermore, only national ACS registries with published literature written in the English language were included. This may have resulted in journal articles being missed during the initial database search, though the key findings are unlikely to have been affected.

It is also important to acknowledge the evolution of ACS registries over the last few decades: from often relatively small and short-term or periodic datasets, derived from a single or a limited number of mainly tertiary hospitals and focusing primarily on acute MI (or indeed STEMI) to frequently much larger and more representative, long-term, or permanent QI programmes. These changes reflect a greater awareness of the importance of measuring performance and reducing variation in practice to improve outcomes, as well as the increasing availability of digital data capture and linkage to outcomes, including patient-reported outcomes. The focus of this ScR on national CQR to some degree mitigates the impact of these temporal shifts, but it is likely that some countries without active registries have implemented national ACS QI programmes that do not publish their results in peer-reviewed journals and are therefore outside the remit of this ScR. Likewise, details regarding the informatics and technical infrastructure of individual registries are important but may evolve over time and were seldom specifically reported; therefore, they are beyond the scope of this review.

Conclusions

It is evident that the design and implementation of national ACS CQR vary. While this is, to some extent, inevitable to accommodate specific national requirements and health infrastructure, and flexibility is necessary, it may limit international collaboration and comparison. Future registries should be encouraged therefore to align as much as possible with successful existing registries and QI programmes. Likewise, while better harmonization may be complex, the development of some fundamental principles agreed by national and international CV societies would encourage co-operation. These might include agreement on key patient cohorts to include (even as subsets of larger populations), clear definitions based on existing international guidance, and a focus on including all patients meeting these criteria to minimize bias and reduce heterogeneity across the ACS registry landscape. Furthermore, concrete recommendations for a minimum core dataset, including clinical characteristics, as well as standardized key outcome measures would also be beneficial. Such co-operation will facilitate internationally comparable, collaborative QI strategies and increase the opportunities for large-scale, registry-based clinical research in patients with ACS, both of which will drive improved outcomes.

Supplementary Material

oeag100_Supplementary_Data

Contributor Information

Justine Chan, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; School of Population Health, Curtin University, Kent Street, Bentley, WA 6102, Australia; Dobney Hypertension Centre, Royal Perth Hospital Research Foundation, Medical School, The University of Western Australia, Level 3, MRF Building, Rear 50 Murray Street, Perth, WA 6000, Australia.

Natalie Ward, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Dobney Hypertension Centre, Royal Perth Hospital Research Foundation, Medical School, The University of Western Australia, Level 3, MRF Building, Rear 50 Murray Street, Perth, WA 6000, Australia.

Judith Finn, Prehospital Resuscitation and Emergency Care Research Unit (PRECRU), Curtin School of Nursing, Curtin University, Building 609, 7 Parker Place, Bentley, WA 6104, Australia; St John Western Australia, 209 Great Eastern Highway, Belmont, WA 6104, Australia; School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia; Medical School, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

Adil Rajwani, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Medical School, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia; Curtin University, Kent Street, Bentley, WA 6102, Australia.

Jing Pang, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Medical School, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

Mikhail Alexander, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia.

Khang Duong Nguyen, School of Population Health, Curtin University, Kent Street, Bentley, WA 6102, Australia; Interventional Cardiology Department, University Medical Center, 215 Hong Bang Street, Ward 11, District 5, Ho Chi Minh City, Vietnam.

Jyoti Sharma, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Dobney Hypertension Centre, Royal Perth Hospital Research Foundation, Medical School, The University of Western Australia, Level 3, MRF Building, Rear 50 Murray Street, Perth, WA 6000, Australia; Centre for Cardio-Metabolic Research in Africa (CARMA), Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg 7505, South Africa; Division of Medical Microbiology, Department of Laboratory-Medicine and Pathology, Faculty of Health Sciences, Walter Sisulu University, Private Bag: X1, Mthatha, 5117, Eastern Cape Province, South Africa.

Carl Schultz, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Medical School, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

Gerald F Watts, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Medical School, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

Markus P Schlaich, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Dobney Hypertension Centre, Royal Perth Hospital Research Foundation, Medical School, The University of Western Australia, Level 3, MRF Building, Rear 50 Murray Street, Perth, WA 6000, Australia; Neurovascular Hypertension & Kidney Disease Laboratory, Baker Heart and Diabetes Institute, PO Box 6492, Melbourne, VIC 3004, Australia.

Christopher M Reid, School of Population Health, Curtin University, Kent Street, Bentley, WA 6102, Australia; School of Public Health & Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, VIC 3004, Australia.

Graham S Hillis, Cardiology Department, Royal Perth Hospital, 197 Wellington Street, Perth, WA 6000, Australia; Medical School, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia.

Data availability

The data underlying this article are available in the article and in its online supplementary material.

Supplementary material

Supplementary material is available at European Heart Journal Open online.

Author contributions

Justine Chan (Conceptualisation, Formal Analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing), Natalie Ward (Investigation, Methodology, Supervision, Writing – review & editing), Judith Finn (Conceptualisation, Methodology, Supervision, Writing – review & editing), Adil Rajwani (Writing – review & editing), Jing Pang (Writing – review & editing), Mikhail Alexander (Writing – review & editing), Khang Duong Nguyen (Writing – review & editing), Jyoti Sharma (Writing – review & editing), Carl Schultz (Writing – review & editing), Gerald F. Watts (Writing – review & editing), Markus P. Schlaich (Conceptualisation, Supervision, Writing – review & editing), Christopher Reid (Conceptualisation, Supervision, Writing – review & editing), Graham S. Hillis (Conceptualisation, Methodology, Supervision, Writing – original draft, Writing – review & editing)

Funding

This work was supported by the Dr Neil Cumpston Cardiovascular Grant administered by the Royal Perth Hospital Research Foundation. J.C. is supported by a Researcher Training Scholarship from the Western Australian Future Health Research and Innovation Fund, administered through Curtin University and East Metropolitan Health Services. J.F. is supported by a National Health and Medical Research Council (NHMRC) Investigator Grant. J.P. is supported by an NHMRC Investigator Grant.

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Associated Data

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Supplementary Materials

oeag100_Supplementary_Data

Data Availability Statement

The data underlying this article are available in the article and in its online supplementary material.


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