Comparison of management and outcomes of ST-segment elevation myocardial infarction patients in Estonia, Hungary, Norway, and Sweden according to national ongoing registries

Abstract

Aims

Describe the characteristics, management and outcomes of hospitalized ST-segment elevation myocardial infarction (STEMI) patients according to national ongoing myocardial infarction registries in Estonia, Hungary, Norway, and Sweden.

Methods and results

Country-level aggregated data was used to study baseline characteristics, use of in-hospital procedures, medications at discharge, in-hospital complications, 30-day and 1-year mortality for all patients admitted with STEMI during 2014–2017 using data from EMIR (Estonia; n = 4584), HUMIR (Hungary; n = 23 685), NORMI (Norway; n = 12 414, data for 2013–2016), and SWEDEHEART (Sweden; n = 23 342). Estonia and Hungary had a higher proportion of women, patients with hypertension, diabetes, and peripheral artery disease compared to Norway and Sweden. Rates of reperfusion varied from 75.7% in Estonia to 84.0% in Sweden. Rates of recommendation of discharge medications were generally high and similar. However, Estonia demonstrated the lowest rates of dual antiplatelet therapy (78.1%) and statins (86.5%). Norway had the lowest rates of beta-blockers (80.5%) and angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers (61.5%). The 30-day mortality rates ranged between 9.9% and 13.4% remaining lowest in Sweden. One-year mortality rates ranged from 14.8% in Sweden and 16.0% in Norway to 20.6% in Hungary and 21.1% in Estonia. Age-adjusted lethality rates were highest for Hungary and lowest for Sweden.

Conclusion

This inter-country comparison of data from four national ongoing European registries provides new insights into the risk factors, management and outcomes of patients with STEMI. There are several possible reasons for the findings, including coverage of the registries and variability of baseline-characteristics’ definitions that need to be further explored.

ST-segment elevation myocardial infarction, Registry study, Real-world evidence, Mortality

Introduction

Randomized controlled trials have well established the value of guideline-indicated medications as well as reperfusion- and revascularization therapies in improving the prognosis of patients with ST-segment elevation myocardial infarction (STEMI).¹ However, numerous country-, region-, and hospital-level observational studies have demonstrated variability in the application of these evidence-based recommendations.^2–4

The Euro Heart Survey 2009 snapshot study⁵ showed large variations in the rates and methods of reperfusion treatment across Europe. For instance, in countries of Eastern and Southern Europe, up to a half of STEMI patients were reported not to receive any reperfusion therapy. Another recent European Society of Cardiology (ESC) initiated descriptive study revealed that although in Europe primary percutaneous coronary intervention (PCI) was the preferred reperfusion method, thrombolysis was still widely used in some countries.⁶

A major barrier in creating a systematic knowledge of inter-country variations in management and outcomes of STEMI has been the lack of comparable non-selective registry data. For instance, the recent ESC EuroObservational Research Programme for acute coronary syndromes STEMI registry⁷ has received criticism concerning data quality, representativeness and case-coverage. With that in mind, the ESC recently launched the EuroHeart project⁸ that aims to aid the continuous assessment of cardiovascular care in Europe using a common technological and dataset infrastructure.

The acute myocardial infarction (AMI) registries in Estonia (EMIR, Estonian Myocardial Infarction Registry), Hungary (HUMIR, Hungarian Myocardial Infarction Registry), Norway (NORMI, Norwegian Myocardial Infarction Registry), and Sweden (SWEDEHEART, Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies) are among the few national registries in Europe with ongoing data registration and high case coverage. These countries also belong to the higher and lower end of the spectrum of ischaemic heart disease mortality in Europe: Estonia and Hungary are among the countries with the higher, while Norway and Sweden have considerably lower rates (Table 1).⁹ Meanwhile in Estonia and Hungary the health expenditure of national gross domestic product is much lower than that in Norway and Sweden. All the countries involved have contributed to establishing their STEMI networks and through endorsing of the ESC guidelines and developing local practice instructions have invested in improving AMI management.

Table 1

Background information for Estonia, Hungary, Norway, and Sweden for 2014–2017

	Estonia	Hungary	Norway	Sweden
Average number of inhabitants, milliona	1.32	9.84	5.23	9.93
Average life expectancy at birth, yearsa
Men	73.0	72.4	80.5	80.9
Women	81.9	79.4	84.2	83.9
Standardized death rate of all-causesb	1263.5	1473.2	943.3	926.2
Standardized death rate of IHD (ICD I20–I25)b	272.5	384.3	93.0	124.1
Health expenditure of GDP, %c	6.4	7.2	10.4	10.9
Number of PCI hospitals	5	20	7d	29
Number of primary PCI centres with 24/7 service	2	19	6	12
Inhabitants per primary PCI centre, million	0.66	0.52	0.87	0.83

AMI, acute myocardial infarction; GDP, gross domestic product; ICD, international classification of diseases, 10th revision; IHD, ischaemic heart diseases; PCI, percutaneous coronary intervention.

^a

Source: Eurostat (https://ec.europa.eu/eurostat).

^b

Per 100 000 population, average for years 2014–2016 (Eurostat).

^c

Presented for year 2017 (Organization for Economic Co-operation and Development).

^d

One hospital with percutaneous coronary intervention facilities performs only elective procedures.

The purpose of this study was to describe the baseline characteristics, management, as well as short-and long-term outcomes of STEMI patients in Estonia, Hungary, Norway, and Sweden with the use of data from national ongoing AMI registries between 2014 and 2017.

Methods

Description of registries

EMIR is a national government-funded mandatory registry established in 2012. Data are reported electronically via a web-based standardized form for all hospitalized AMI cases [International classification of diseases 10th revision (ICD-10) codes I21–I22]. The dataset and definitions conform to the Cardiology Audit and Registration Data Standards.¹⁰ Data validity is subject to routine error checking. According to the routine annual internal auditing against the data collected for reimbursement purposes to be presented to the national Health Insurance Database, the case coverage is over 95%.

HUMIR is a national registry collecting data on consecutive AMI patients and data are reported via a web-based form. Data capture covers 178 structured variables, including those regarding prehospital data, previous medical history, hospital medications, and coronary interventions. The registry database included 92% of all AMI cases in 2017 as compared to the national healthcare provider reimbursement dataset. The data are continuously checked and validated by six part-time dedicated personnel. Outcome data, including vital status and repeated hospitalizations, are regularly received from the electronic database of the national healthcare insurance provider.

NORMI is a government funded mandatory registry established in 2013. It collects data on all hospitalized AMI patients. The registry enrolls annually about 12 000 patients admitted to Norwegian hospitals. The registry contains information on sex, age, known risk factors, medical history and previous medication, symptoms and clinical findings on arrival, treatment, complications while in hospital, and medications upon discharge. The registry has >90% case coverage and a high degree of completeness and accuracy.¹¹

SWEDEHEART is a national registry that includes all consecutive patients >18 years of age admitted to a coronary care unit or other specialized facility with symptoms suggestive of AMI. The SWEDEHEART registry started 1995 and enrolls annually about 18 000 patients and contains data on more than 100 variables such as baseline characteristics, medication on admission, in-hospital therapies, complications, and medication at discharge. Continuous monitoring evaluates the correctness of data entered in the registry with the medical records yearly (agreement is about 96%).¹² The coverage of AMI hospitalizations in SWEDHEART during the study period ranged from 84.3% to 88.1% and is about 96% for patients under the age of 80 years and about 80% for elderly patients.¹³

By using the unique personal identification number for residents in each country, further cross-matching with other nation-wide registries enable analysis of follow-up data on e.g. ICD-codes, vital status and cause of death.

Study population

The background information of the four countries involved is presented in Table 1.

The study included all consecutive cases admitted with STEMI registered in the EMIR, HUMIR and SWEDEHEART during a 4-year period during 1 January 2014 to 31 December 2017. The data for NORMI were available for the period from 1 January 2013 to 31 December 2016. The diagnosis of STEMI was based on the ESC third universal definition of myocardial infarction.¹⁴

The study complies with the Declaration of Helsinki and is approved by the local ethics committee of each country: Research Ethical Committee of the University of Tartu, Estonia (253/T-13); Hungarian Medical Research Council (34858-3/2019/EKU); the Regional Committee for Medical and Health Research Ethics North in Norway (REK 2016/170); and the regional ethics committee in Stockholm, Sweden (2012/60-31/2).

Variables included

The registries were asked to provide data on demographic variables (age, sex), cardiovascular risk factors [body mass index (BMI), smoking, hypertension, diabetes, hyperlipidaemia, chronic kidney failure], and previous cardiovascular disease (previous AMI, heart failure, stroke, peripheral vascular disease). Hospital presentation variables included out-of-hospital cardiac arrest, systolic heart rate, blood pressure, heart rhythm, as well as Killip class. Features of in-hospital management included reperfusion therapy, time from onset of symptoms to reperfusion, coronary angiography, revascularization (PCI and/or coronary artery bypass crafting) during the index episode, and echocardiography. Discharge medications assessed were aspirin, dual-antiplatelet therapy (aspirin and clopidogrel/prasugrel/ticagrelor), oral anticoagulants, beta-blockers, angiotensin-converting enzyme inhibitors (ACEI)/angiotensin II receptor blockers (ARB), and statins. In-hospital complications were re-infarction, cardiac arrest, and severe bleeding. Mortality data included data on 30 days and 1 year.

The percentage of missing values across the included variables can be found in the Supplementary material online, Table S1. The EMIR, HUMIR, and NORMI had no loss of follow-up in respect to vital status. In SWEDEHEART, the follow-up data for vital status was available until 30 June 2018. The cohort of 2014–2016 had no loss of follow-up. However, the cohort of 2017 had a considerable rate of missingness of vital status. For SWEDEHEART, the 30-day and 1-year mortality analysis was restricted to the cohort of 2014–2016 without a meaningful impact on the rates anticipated.

Definition of variables

The definitions of selected variables and the assessment of comparability are displayed in the Supplementary material online, Table S2. The comparativeness of the definitions across the registries was assessed during joint discussions and indicates the general agreement reached. Overall, the definitions were fairly harmonious throughout the registries. However, differences were observed in the definition of hypertension, hyperlipidaemia, and previous heart failure.

Statistical analysis

Data were aggregated at country level and compared as such. Categorical variables were expressed as percentages with 95% confidence intervals, and continuous variables as means and standard deviations, or as medians and interquartile ranges.

Country-level patient baseline characteristics as predictors of reperfusion were estimated by logistic regression where the model included variables that were available in all countries: patient demographics (age and gender), risk factors (BMI, smoking, hypertension, diabetes, hyperlipidaemia), and previous cardiovascular diseases (AMI, chronic heart failure, stroke, and peripheral artery disease). The rate of missing values of these baseline characteristics included in the model varied from <0.1% to 34.8% (Supplementary material online, Table S1) and tended to be more often missing for older patients and those who died during hospitalization (Supplementary material online, Table S3). In order to perform a logistic regression analysis on the full set of cases in each country a chained multiple imputation with 20 datasets was used. Age, gender, BMI, smoking, hypertension, diabetes mellitus, hyperlipidaemia, previous myocardial infarction, heart failure, stroke, and peripheral artery disease was used for value estimation.

In order to further explore the differences in the 30-day and 1-year mortality rates between the registries, a direct age-adjusted standardization of lethality rates was performed. With the aim to use a reference population where the risk profile would not be markedly different from the individual countries a reference was created using the study cohorts from the four involved countries.¹⁵

Analyses were performed using the Stata statistical software version 11 and 16, R statistical software package version 3.6.0 and SPSS for mac version 26.

Results

During the study period, 64 025 STEMI patients were registered: 4584 in EMIR, 23 685 in HUMIR, 12 414 in NORMI, and 23 342 in SWEDEHEART.

The patients in Hungary and Norway were younger than in Estonia and Sweden (Table 2). Hungary had the highest proportion of patients under the age of 60 years (36.4%). Although Sweden reported a lower case-coverage for over 80-years-old patients, the proportion of this patient group was still highest (27.6%) across the registries. Proportion of current smokers was lowest in Sweden (25.1%) and highest in Norway (38.0%). Estonia and Hungary reported compared to Norway and Sweden higher rates of women, as well as patients with hypertension, diabetes, stroke and peripheral artery disease. Estonia also reported high rates of hyperlipidaemia.

Table 2

Baseline characteristics

	EMIR (n = 4584)	HUMIR (n = 23 685)	NORMI (n = 12 414)	SWEDEHEART (n = 23 342)
Demography
Age, mean (SD)	69.2 (12.9)	64.7 (13.1)	66.4 (13.7)	69.3 (13.0)
<60 years, % (95% CI)	25.2 (24.0–26.5)	36.4 (35.8–37.0)	32.6 (31.8–33.5)	23.1 (22.6–23.7)
60–69 years, % (95% CI)	27.2 (25.9–2.5)	28.6 (28.0–29.2)	26.9 (26.2–27.7)	23.1 (22.6–23.7)
70–79 years, % (95% CI)	23.1 (21.9–24.3)	21.0 (20.4–21.5)	20.4 (19.7–21.1)	26.9 (26.3–27.4)
80+ years, % (95% CI)	24.4 (23.3–25.7)	14.0 (13.6–14.5)	20.0 (19.3–20.7)	27.6 (27.0–28.2)
Men, % (95% CI)	61.4 (60.0–62.8)	61.6 (60.9–62.2)	70.8 (70.0–71.6)	69.2 (68.6–69.8)
Risk factors
BMI, median (IQR)	28 (25–31)	27 (24–31)	26 (24–29)	26 (24–29)
Current smoker, % (95% CI)	34.5 (33.1–35.9)	32.0 (30.3–33.2)	38.0 (37.1–38.8)	25.1 (24.6–25.7)
Hypertension, % (95% CI)	78.6 (77.4–79.8)	73.9 (73.3–74.5)	39.2 (38.3–40.0)	49.4 (48.7–40.0)
Diabetes mellitus, % (95% CI)	20.6 (19.5–21.8)	28.3 (27.7–28.9)	13.9 (13.3–14.5)	18.9 (18.4–19.4)
Hyperlipidaemia, % (95% CI)	66.1 (64.7–67.5)	28.7 (28.1–29.4)	22.5 (21.8–23.3)	23.2 (22.7–23.8)
CKD (eGFR < 60), % (95% CI)	NC	16.3 (15.8–16.7)	21.7 (21.0–22.5)	24.0 (23.4–24.6)
Previous CVD
Myocardial infarction, % (95% CI)	16.0 (15.0–17.1)	13.7 (13.3–14.2)	14.2 (13.6–14.9)	18.9 (18.3–19.3)
Heart failure, % (95% CI)	28.1 (26.8–29.4)	8.7 (8.4–9.1)	3.4 (3.1–3.8)	9.2 (8.8–9.5)
Stroke, % (95% CI)	9.7 (8.9–10.6)	7.7 (7.3–8.0)	5.6 (5.2–6.0)	6.8 (6.5–7.1)
Peripheral artery disease, % (95% CI)	8.6 (7.8–9.5)	10.2 (9.7–10.6)	6.0 (5.6–6.4)	4.1 (3.9–4.4)
Presentation
Prehospital cardiac arrest, % (95% CI)	NC	5.3 (5.0–5.6)	7.2 (6.7–7.7)	4.8 (4.5–5.1)
Heart rate, median (IQR)	78 (66–91)	80 (70–94)	77 (65–90)	77 (65–91)
Systolic BP, median (IQR)	138 (119–155)	130 (120–152)	133 (115–151)	140 (120–160)
Killip class II–IV, % (95% CI)	28.0 (26.7–29.3)	10.5 (10.1–10.9)	NC	9.5 (9.1–9.9)

BMI, body mass index; BP, blood pressure; CI, confidence interval; CKD, chronic kidney disease; CVD, cardiovascular disease; eGFR, estimated glomerular filtration rate; IQR, interquartile range; NC, data not collected; SD, standard deviation.

The rates of reperfusion ranged from 75.7% in Estonia to 84.0% in Sweden (Table 3). The country-level multivariate analysis including patient baseline characteristics showed similar results across the registries where younger patients with risk factors and less previous cardiovascular diseases received more often reperfusion therapy (Supplementary material online, Table S4). The reperfusion method of choice was primary PCI and the rate of thrombolysis ranged between 0.5% and 13.2%. The use of angiography through the countries was above 80% with Sweden demonstrating the highest numerical rates of 93.0%. The proportion of patients undergoing PCI ranged from 72.8% in Estonia to 89.1% in Sweden.

Table 3

Comparison of in-hospital management

	EMIR (n = 4584)	HUMIR (n = 23 685)	NORMI (n = 12 414)	SWEDEHEART (n = 23 342)
Reperfusion, % (95% CI)	75.7 (74.4–76.9)	82.0 (81.3–82.3)	79.4 (78.7–80.1)	84.0 (83.5–84.4)
Thrombolysis, % (95% CI)	12.4 (11.5–13.4)	0.5 (0.4–0.5)	13.2 (12.6–13.8)	3.2 (3.0–3.4)
Primary PCI, % (95% CI)	63.4 (62.0–64.8)	80.6 (80.1–81.1)	66.2 (65.4–67.0)	77.3 (76.8–77.9)
Time to reperfusion, median (IQR)	236 (165–375)	295 (181–655)	NC	198 (124–475)
Coronary angiography, % (95% CI)	80.4 (79.2–81.5)	83.1 (82.6–83.5)	84.6 (83.9–85.2)	93.0 (92.7–93.4)
PCI, % (95% CI)	72.8 (71.5–74.1)	81.3 (80.8–81.8)	77.8 (77.1–78.6)	89.1 (88.7–89.5)
CABG, % (95% CI)	1.0 (0.8–1.3)	NC	1.5 (1.3–1.7)	2.0 (1.8–2.2)
LVEF assessment by echocardiography, % (95% CI)	91.7 (90.9–92.5)	79.6 (79.1–80.1)	79.5 (78.8–80.2)	86.9 (86.2–87.1)
LVEF ≥50%, % (95% CI)	42.3 (40.8–43.8)	39.5 (38.8–40.1)	39.3 (38.4–40.1)	47.6 (46.9–48.2)
LVEF 40–49%, % (95% CI)	29.1 (27.7–30.5)	23.2 (22.6–23.7)	32.9 (32.1–33.7)	26.8 (26.2–27.4)
LVEF 30–39%, % (95% CI)	20.7 (19.5–22.0)	12.3 (11.9–12.8)	*	17.0 (16.5–17.5)
LVEF <30%, % (95% CI)	7.2 (6.4–7.9)	4.6 (4.3–4.9)	7.3 (6.8–7.7)	7.7 (7.3–8.0)

*, error in the database; CABG, coronary artery bypass grafting; CI, confidence interval; IQR, interquartile range; LVEF, left ventricular ejection fraction; NC, data not collected; PCI, percutaneous coronary intervention.

Rates of recommended medications at discharge were generally high and similar across the registries (Table 4). However, Estonia had the lowest rates of dual antiplatelet therapy (78.1%) and statins (86.5%). Norway had the lowest rates of beta-blockers (80.5%) and ACEI/ARB (61.5%).

Table 4

Recommendation of medications at discharge

	EMIR (n = 4052)	HUMIR (n = 21 568)	NORMI (n = 11 269)	SWEDEHEART (n = 21 430)
Aspirin, % (95% CI)	92.0 (91.1–92.8)	95.7 (95.4–95.9)	96.3 (95.9–96.6)	92.3 (91.9–92.6)
Dual antiplatelet treatment, % (95% CI)	78.1 (76.8–79.2)	92.4 (92.1–92.8)	90.2 (89.6–90.7)	83.1 (82.6–83.6)
Oral anticoagulants, % (95% CI)	10.5 (9.5–11.5)	5.9 (5.6–6.3)	13.7 (13.0–14.3)	11.2 (10.8–11.6)
Beta-blockers, % (95% CI)	84.4 (83.3–85.5)	87.0 (86.5–87.5)	80.5 (79.7–81.1)	88.8 (88.4–89.2)
Statins, % (95% CI)	86.5 (85.4–87.5)	91.8 (91.5–92.2)	90.1 (89.5–90.6)	92.1 (91.8–92.5)
ACEI/ARB, % (95% CI)	78.0 (76.7–79.2)	83.9 (83.4–84.4)	61.5 (60.6–62.4)	84.6 (84.2–85.1)

ACEI/ARB, angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers; CI, confidence interval.

In crude analysis, the 30-day mortality rates were similar in Estonia, Hungary, and Norway with rates ranging between 12.4% and 13.4% and somewhat lower in Sweden with 9.9% (Table 5). The 1-year mortality rates ranged from 14.8% in Sweden and 16.0% in Norway to 20.6% in Hungary and 21.1% in Estonia.

Table 5

Crude rates of short- and long-term outcomes

	EMIR	HUMIR	NORMI	SWEDEHEART
In-hospital complications	(n = 4584)	(n = 23 685)	(n = 12 414)	(n = 23 342)
Reinfarction, % (95% CI)	0.5 (0.3–0.7)	1.0 (0.85–1.16)	1.1 (0.9–1.2)	0.9 (0.8–0.10)
Cardiac arrest, % (95% CI)	11.7 (10.8–12.7)	6.7 (6.35–7.0)	6.4 (6.0–6.8)	5.1 (4.8–5.4)
Severe bleeding, % (95% CI)	2.0 (1.9–2.2)	1.2 (1.1–1.4)	1.4 (1.2–1.6)	1.0 (1.0–2.0)
Mortality	(n = 4584)	(n = 23 685)	(n = 12 414)	(n = 17 293)a
30 days, % (95% CI)	13.4 (12.4–14.4)	13.3 (12.9–13.7)	12.4 (11.8–13.0)	9.9 (9.4–10.3)
1 year, % (95% CI)	21.1 (19.9–22.3)	20.6 (20.1–21.1)	16.0 (15.4–16.7)	14.8 (14.3–15.4)

CI, confidence interval.

^a

Data for 2014–2016.

Direct age-standardized lethality rates were highest for Hungary for 30 days as well as for 1 year, while Sweden had the lowest respective rates (Table 6). Estonia and Norway had similar 30-day lethality rates but the 1-year rate was higher in Estonia.

Table 6

Age-standardized 30-day and 1-year lethality rates

	EMIR	HUMIR	NORMI	SWEDEHEART
30 days, % (95% CI)	11.8 (10.9–12.9)	15.2 (14.6–15.7)	12.0 (11.4–12.6)	8.8 (8.4–9.2)
1 year, % (95% CI)	18.7 (17.5–19.9)	23.3 (22.7–24.0)	15.5 (14.8–16.2)	13.1 (12.5–13.6)

CI, confidence interval.

Discussion

This unique collaboration study of four ongoing European national registries describes the baseline characteristics, in-hospital management, and recommendation of discharge medications as well as short- and long-term outcomes of an unselected cohort of patients with STEMI.

Conducting inter-country comparison studies on the real-world management and outcomes of AMI patients based on national registries is a fairly novel approach. There are several crucial issues to be addressed. The reported annual case coverage of the registries was over 90% for Estonia, Hungary, and Norway and somewhat lower for Sweden, especially for the over 80-year-old patients. Yet, Sweden had the highest rate of over 80-year-old patients across the registries supporting the comparability of the data. Another feature to be accounted for is the comparability of the variable definitions. While the definitions concerning management and outcomes were mostly harmonious, the definitions of such baseline characteristics as hypertension, hyperlipidaemia, and previous chronic heart failure differed across registries and suggested that Estonia and Hungary could be more prone to detect and report underlying cardiovascular risk factors. The reasons for it could be multifactorial, for instance reimbursement issues in Estonia. It calls for caution in interpreting the data on management practices and outcomes in inter-country registry research.

A third of patients in all countries were current smokers with the peak rate of 38% in Norway. Even though the definitions in EMIR and HUMIR favoured the reporting of hypertension and hyperlipidaemia and a valid inter-registry comparison was hindered, it has to be considered that these countries have previously reported higher prevalence of elevated blood pressure and cholesterol in the general population.¹⁶ Similarly, to the Euro Heart Survey 2009 snapshot,⁵ our study suggested higher rates of diabetes as well as previous cardiovascular diseases as stroke and peripheral vascular disease among patients in Estonia and Hungary compared to their northern counterparts. Thus, the differences in the definitions probably only partly explain the higher rates of hypertension and hyperlipidaemia and a true higher risk factor profile in Estonian and Hungarian patients does exist. Furthermore, this study highlights the high prevalence of modifiable risk factors in the relatively young AMI population of Hungary.

Although there were some fluctuations in the overall rates of reperfusion, revascularization and recommendation of discharge medications, the management of STEMI patients was more harmonious than might be expected from the socioeconomic backgrounds of the involved countries or suggested by the Euro Heart Survey 2009 snapshot.⁵ Rates of reperfusion varied between 76% and 84% and primary PCI was the reperfusion method of choice. Yet the data suggest a customized STEMI management network in each country. For instance, the number of primary PCI centres per million inhabitants was one and a half times higher in Hungary than in Norway and Sweden. Norway, due to its geographical peculiarities, had opted for a centralized STEMI network where only a small number of hospitals performed primary PCI and rates of thrombolysis were similar with Estonia. So, despite of the national adaptations of STEMI networks it is clear that the guidelines-based management of STEMI is endorsed in the involved countries. Furthermore, the existence of a national AMI registry has been shown to enhance the quality of care of this high-risk group of patients.¹⁷ Whether these ranges of variability of management can be applied to other European countries remains to be studied.

The lower rates of dual antiplatelet therapy and statins is an area of quality improvement in Estonia. Interestingly, despite reporting the highest rate of hyperlipidaemia, Estonia showed the lowest rate of statin recommendation upon discharge. The pattern of medication use in Norway rather demonstrates a selective practice pattern than overall lower adherence to guidelines as indeed beta-blockers and ACEI/ARB have a stronger evidence base in case of AMI with reduced left ventricular ejection fraction.¹ The causes of these management practices could be addressed in the future research.

Our study highlights the importance of efficient secondary prevention interventions for AMI patients in all countries involved. That includes developing a comprehensive cardiac rehabilitation programme and ensuring systematic follow-up for AMI patients.¹⁸ While Sweden has managed to establish a country-wide multidisciplinary high-quality cardiac rehabilitation programme,¹⁹ the other three countries involved in the study have yet to meet this need in a systematic manner. For instance, Norway has reported suboptimal attainment of secondary preventive treatment targets in patients with AMI²⁰ and Estonia has shown a low adherence to secondary prevention medications.²¹

As with all registry studies, the outcomes and mortality data must be interpreted with caution. As expected, the 30-day and 1-year mortality rates were higher compared to the ones reported by randomized controlled trials²² and selective registries,^5,23 which further supports the representativeness of the real-world data in this study. The crude 30-day mortality was similar for Estonia, Norway and Hungary but somewhat lower in Sweden. However, the age-adjusted lethality rate was highest for Hungary indicating an unfavourable prognosis in this relatively young AMI population with high rates of modifiable risk factors despite the high rate of use of primary PCI and evidence-based medications. Concerning the Norwegian cohort, due to the relatively younger age and favourable risk factor profile, it might have been expected that it would have similar short-term mortality as the Swedish one. One explanation for this finding could be a lower rate of reperfusion and a higher relative use of thrombolysis instead of primary PCI in Norway. However, it has to be considered, that in Norway the rate of patients with prehospital cardiac arrest was numerically higher than in Sweden (7.2% vs. 4.8%). This finding deserves further research as the reasons for it could for instance be longer prehospital delay times or differences in the registry coverages. These questions should be addressed in future research.

The 1-year mortality rate in Estonia and Hungary was numerically about 6% higher than in Sweden and the age-adjusted lethality rate in Hungary was almost twice as high as in Sweden. To some extent a higher long-term mortality might have been expected for Estonia as the rates of modifiable risk factors were high and the rates for reperfusion, double-antiplatelet treatment and statins were lower than in the other counties. However, both for 30-day and 1-year mortality differences between Hungary and Sweden were striking as the rates of reperfusion and prescription of medications for secondary prevention did not differ substantially.

The underlying causes for the mortality differences across the countries involved clearly need more research as the reasons for these disparities are multifactorial including differences in age distribution, risk factor profiles and management during the hospital stay as well as different socioeconomic backgrounds, post-AMI depression and anxiety, adherence to secondary prevention medications and participation in organized secondary prevention programmes.

Limitations

This study has several limitations. Firstly, data were not available for direct inter-country statistical comparison and was compared as aggregated country-level data. Secondly, although the data presented are the best of unselected real-world data that each involved country had available, a full case-coverage was not achieved. Furthermore, due to a delay in the linkage between national registries, the Swedish cohort of 2017 lacked a considerable proportion of data on vital status and had to be excluded from the mortality and lethality analysis. However, based on the available data a considerable impact on the results was not expected. Thirdly, as with all registries, there are gaps in the completeness of data, especially for baseline characteristics. The patterns of missingness across variables in different registries are often complex and involve among other reasons the completeness of health records and training of data enterers that is challenging to capture with statistical analysis. In the current study country-level multiple imputation was used to correct for missingness in the multivariate model. However, we choose to present the rates of baseline characteristics and management as originally captured in the registries. Fourthly, the multivariate model for studying the country-level determinants of reperfusion did not include renal function, Killip class and out of hospital cardiac arrest as not all registries collected these variables. Fifthly, there were differences in the definitions of some baseline characteristics like hypertension, hyperlipidaemia, and heart failure as well as delay to reperfusion. Lastly, we compared the use of procedures and prescription of discharge medications in all patients, regardless of contraindications or guideline indications. This is in keeping with our aim to feature any management variation, rather than to benchmark according to reaching the quality of care standards.

Conclusions

This inter-country descriptive comparison of data from four national ongoing European registries provides new insights into real-life differences in risk factors, management and outcomes of patients with STEMI. There are several possible reasons for the findings, including differences in underlying expected mortality in the populations, inclusion-criteria and coverage of the registries and variable definitions that need to be further explored.

Supplementary material

Supplementary material is available at European Heart Journal – Quality of Care and Clinical Outcomes online.

Acknowledgements

The authors would like to acknowledge all the professionals who have contributed to the founding and every-day functioning of the registries involved in this study.

Funding

This work was supported by the Estonian Research Council [PRG435] and South-Eastern Norway Regional Health Authority [2017086].

Data availability

The data from EMIR, HUMIR, and SWEDEHEART that support the findings of this study are available on reasonable request to the corresponding author. For NORMI, the data are available from the Norwegian Institute of Public Health. Restrictions apply to the availability of the data as these were used under license for this study.

Conflict of interest: M.B. has received lecturing fees from Astra-Zeneca and Boehringer Ingelheim RCV GmbH & Co KG and consultancy fees from AMGEN and Novo Nordisk. R.E. has received an institutional grant from AstraZeneca and is employed by Bayer AB, but reports no conflict of interest related to this work. T.J. reports grants from MSD and Novartis and Karolinska Institutet has received reimbursement from Astra-Zeneca, Bayer, MSD, Novartis and Sanofi for lecturing and consultancy. T.M. reports personal fees from AstraZeneca and Sanofi outside the submitted work. All other authors have declared no conflict of interest.