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\begin{document}

\title{Incidence, Pre-hospital Delay and Prognosis of Acute Myocardial
Infarction in Hungary: Population Data from the Hungarian Myocardial
Infarction Registry}



\author[1]{András Jánosi}%
\author[2]{Ferenc, Péter Pach}%
\author[2]{Gergely Erdős}%
\author[3]{Gabor Csato}%
\author[3]{György Pápai}%
\author[4]{Péter Andréka}%
\affil[1]{Gyorgy Gottsegen Hungarian Institute of Cardiology}%
\affil[2]{Institute of Advanced Studies Koszeg}%
\affil[3]{National Emergency Service}%
\affil[4]{Gottsegen Gyorgy Orszagos Kardiologiai Intezet}%


\vspace{-1em}



  
  \date{May 23, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Aim: To examine the incidence and treatment of acute myocardial
infarction (AMI) as well as 30-day and 1-year prognoses of patients in
three major regions of Hungary by analysing data from the country's
continuous and mandated infarction registry. Methods and results: The
total population of Hungary is currently 9.8 million: 39\% live in the
eastern region (ER), 31\% in the Central region (CR) and 30\% in the
western region (WR). These regions exhibited significant differences in
income and people exposed to poverty. Population over 30 years, the
age-standardised incidence of AMI was 177.5 (175.7--179.3) per 100,000
person-year. During hospital treatment, 82.5\%--84.6\% of patients with
ST-elevation (STEMI) and 54.8\%--81.8\% without ST-elevation (NSTEMI)
underwent PCI. The total ischaemic time was shortest in WR:221 minutes.
In the STEMI group, the 30-day mortality rates of males were lowest in
the WR (p = 0.03). If PCI was performed, mortality rates for both sexes
were lowest in the WR (p \textless{} 0.01; p = 0.04). The 1-year
mortality rate in the male population who received PCI was lowest in the
WR. In the NSTEMI group, the 30-day mortality rate exhibited no
differences. Regarding 1-year mortality, those who underwent PCI in the
WR showed the lowest mortality. Conclusion: The major regions of Hungary
exhibited significant differences regarding the prehospital delay, the
incidence, treatment and mortality of AMI. Logistic regression analysis
confirmed the independent prognostic significance of the region on the
30-day mortality of patients with STEMI (Hazard ratio = 0.88, p =
0.0114).%
\end{abstract}%



\sloppy


\textbf{Incidence, Pre-hospital Delay and Prognosis of Acute Myocardial
Infarction in Hungary: Population Data from the Hungarian Myocardial
Infarction Registry}

Andr\selectlanguage{ngerman}ás Jánosi\textsuperscript{1}, M.D., Ferenc Péter
Pach\textsuperscript{2}, Gergely Erd\selectlanguage{polish}ő\selectlanguage{english}s\textsuperscript{2}, G\selectlanguage{ngerman}ábor
Csató\textsuperscript{3} , György Pápai\textsuperscript{3} , Péter
Andréka\textsuperscript{1}

\textsuperscript{1}Gottsegen National Cardiovascular Centre, Budapest,
Hungary; \textsuperscript{2}Institute of Advanced Studies, K\selectlanguage{polish}ő\selectlanguage{english}szeg,
Hungary, \textsuperscript{3} National Ambulance Service, Budapest,
Hungary

Correspondence:

Professor Andr\selectlanguage{ngerman}ás Jánosi, M.D.

Gottsegen National Cardiovascular Centre

1096 Haller street 29, Budapest, Hungary

Phone: +361299-8100, ext. 513

Fax: +361299-8181

E-mail: andras.janosi@gokvi.hu

Personal e-mail: janosiandrasdr@gmail.com

\textbf{Summary}

\textbf{Aim} : To examine the incidence and treatment of acute
myocardial infarction (AMI) as well as 30-day and 1-year prognoses of
patients in three major regions of Hungary by analysing data from the
country's continuous and mandated infarction registry. \textbf{Methods
and results} : The total population of Hungary is currently 9.8 million:
39\% live in the eastern region (ER), 31\% in the Central region (CR)
and 30\% in the western region (WR). These regions exhibited significant
differences in income and people exposed to poverty. Population over 30
years, the age-standardised incidence of AMI was 177.5 (175.7--179.3)
per 100,000 person-year. During hospital treatment, 82.5\%--84.6\% of
patients with ST-elevation (STEMI) and 54.8\%--81.8\% without
ST-elevation (NSTEMI) underwent PCI. The total ischaemic time was
shortest in WR:221 minutes. In the STEMI group, the 30-day mortality
rates of males were lowest in the WR (p = 0.03). If PCI was performed,
mortality rates for both sexes were lowest in the WR (p \textless{}
0.01; p = 0.04). The 1-year mortality rate in the male population who
received PCI was lowest in the WR. In the NSTEMI group, the 30-day
mortality rate exhibited no differences. Regarding 1-year mortality,
those who underwent PCI in the WR showed the lowest
mortality.\textbf{Conclusion} : The major regions of Hungary exhibited
significant differences regarding the prehospital delay, the incidence,
treatment and mortality of AMI. Logistic regression analysis confirmed
the independent prognostic significance of the region on the 30-day
mortality of patients with STEMI (Hazard ratio = 0.88, p = 0.0114).



\textbf{Introduction}

One of the earliest population-based surveys regarding the incidence and
treatment of myocardial infarction was initiated and co-ordinated by the
World Health Organisation approximately 30 years ago (1). Over the past
two decades, many European and Far Eastern countries have launched
registries covering the entire population (2-5), and several comparative
international studies have been performed (6-9). Due to the varying
methodologies of these registries, the comparative evaluation of data
has only been possible with certain limitations (10). Following these
instances, the European Society of Cardiology initiated the creation of
a system that applies a uniform methodology, currently in its pilot
phase (11). Such an infarction registry has been available in Hungary
since 2014, which is both nationwide and mandated (Hungarian Myocardial
Infarction Registry=HUMIR) i.e., in-depth research on the quality
parameters of infarction care is possible (12). The mechanisms and
funding of healthcare systems are significantly different across
countries. Several studies report that depending on an individual's
health insurance, social situation, educational background and several
other factors, extreme inequalities may occur in the healthcare received
between--- and even within---certain countries (13-15). According to the
statistical system of the European Union, Hungary can be divided into
three major socio-economic regions---west Hungary, central Hungary and
east Hungary---which exhibit significant sociological and economic
differences. According to the data of the Hungarian Central Statistical
Office, the GDP per capita is 6,073, 3,581 and 2,722 EUR in the central
(CR), western (WR) and eastern (ER) regions, respectively. The
proportions of those exposed to poverty and social exclusion are nearly
identical in the CR and WR in the total population (22.4\% vs. 22.5\%);
however, this rate is significantly higher in the ER (30.4\%). The
regions and their population data are presented in \textbf{Figure 1} .
The aim of this investigation was to compare the incidence, prehospital
delay, clinical data, hospital treatment and prognoses of acute
myocardial infarction (AMI) in three socio-economically distinct regions
of Hungary by analysing data from the national and mandated myocardial
infarction registry.

\textbf{Method}

This study was approved by the Medical Research Council
(34858-3/2019/EKU). The Hungarian Myocardial Infarction Registry (HUMIR)
is a prospective and comprehensive disease registry for patients with
AMI. Since 1 January 2010, this online registry has collected personal
and clinical data on consecutive patients treated for AMI events in
Hungary, a Central European country with 9.8 million residents and a
centralised healthcare system. The registry was operated on a voluntary
basis between 2010 and 2013; however, by law, registration of all
patients with myocardial infarction in the HUMIR has been mandatory for
all healthcare providers since 1 January 2014 (statute CCXLVI/2013 of
Hungary). Data capture covered 178 structured categories, including
prehospital data, medical history, hospital treatment and coronary
interventions. The data were recorded in the online database by
healthcare professionals and administrators based on hospital
documentation, and the information was continuously monitored and
validated online. Outcome data---including vital status and repeated
hospitalisation---were regularly received from the electronic database
of the Hungarian Health Care Insurance Fund and National Central
Statistical Office.

The aim of the registry is two-fold: to provide quality assurance for
patient care and to build a database for research. All hospitals
offering acute care participate in the programme, registering
approximately 15,000 AMI cases annually; in 2021, the database contained
122,774 patients and 134,986 events. The National Health Insurance Fund
is responsible for the financing of healthcare services, whereas acute
inpatient care is funded by implementing a system similar to the
American Diagnosis Related Groups (16). The diagnosis and treatment
protocol for AMI are in line with the current European guidelines (17);
thus, the treatment of myocardial infarction with ST-elevation (STEMI)
cases is performed at centres prepared for invasive interventions. In
Hungary, the capital has six invasive centres and the remaining regions
of the country have 14. The operating principles of the centres in the
capital and country differ to a certain extent; the six centres in the
capital treat patients from the CR between 8 a.m. and 6 p.m. based on a
regional principle. Between 6 p.m. and 8 a.m., these centres care for
all patients in the region, whereas there is 24/7 care available in all
countryside centres. According to the professional protocol for
infarction care, the patient has to be transferred directly to a care
centre providing cardiac catheterisation in the case of STEMI; if this
is not possible, pharmacological anti-thrombotic therapy has to be
introduced. In daily clinical practice, pharmacological
revascularisation (thrombolysis) is rarely performed (0.1-0.3\% of all
cases).

In the case of myocardial infarction without ST-elevation (NSTEMI), the
decision concerning the necessity of invasive treatment is based on the
patient's prognosis (e.g., GRACE score). Between 1 January 2016, and 31
December 2018, a total of 42,793 AMI cases were registered in the HUMIR
database, with 18,435 being STEMI cases. During the 2-year interval
(between 1 January 2017 and 31 December 2018), the emergency care data
of 6,878 patients treated for myocardial infarction were also available;
thus, in this patient cohort, it was possible to examine the time
interval between the onset of symptoms and the reopening of the culprit
vessel (total ischaemic time, TIT). The time interval between the onset
of symptoms and the calling of emergency services was examined, along
with the different time intervals of the emergency care process: arrival
to location (T1), treatment on-site (T2) and time interval between
transferring the patient from the original location to the hospital
(T3). Time values were indicated by median time and quartiles, and we
analysed the all-cause mortality of all cases observed until 30 November
2019. The R statistical programme package (version 3.6.3;
https://www.r-project.org/about.html) was used for data processing; in
the descriptive statistical analysis, we represented the distribution of
category variables by frequency (and proportion value) and continuous
variables by mean value (distribution) and median treatment time
(quartiles). For the comparative analysis of the examined groups, we
applied the Wilcoxon test for continuous variables in two-sample cases
and the Kruskal--Wallis test in multiple-sample cases; for categorical
variables, the Chi-squared test was used (WHO No. 95). For categorical
variables, regional differences were evaluated using the Chi-squared and
accompanying post-hoc test. The calculations of age-standardised rates
in the particular regions were calculated by applying the direct method
based on the official WHO guidelines. For the standard age group
distribution, we applied the European age standard. When analysing
fatalities, we used the stratified Cox-PH regression model (18). Because
one of the major conditions of the applicability of the Cox regression
model was not met (with the help of the Schoenfeld test, we determined
that the risk ratios of the examined factors were not time-independent),
the time variable was divided into three parts based on 30 and 365 days.
Thus, this study aimed to determine the risk ratios of individual
factors.

\textbf{Results}

\emph{Completeness of registration}

During the years included in the study (2016, 2017 and 2018), 90.2\%,
93.8\% and 93.6\% of events treated and funded as infarction diagnoses
appeared in the registry database, respectively.

\emph{Number and geographical distribution of invasive centres in
Hungary}

There are six invasive centres in the CR and seven in each of the other
two regions, with 418,000 inhabitants per centre in the WR, 505,000 in
the CR and 545,000 in the ER.

\emph{Patient characteristics}

The average age, sex ratio, events included in the medical history and
comorbidities of patients treated for different types of infarction are
summarised in \textbf{Table 1} . In the case of STEMI, patients in the
CR were significantly older than those in the WR and ER. Compared with
the other two regions, prior infarction was most common in the CR,
whereas stroke was the most common prior disease in the ER; both
hypertension and peripheral artery disease were more common in the WR
and ER than in the CR. The incidence of diabetes was significantly
higher in the WR than in the other two regions.

In the NSTEMI group, patients were again oldest and prior myocardial
infarction was most common in the CR. Regarding comorbidities,
statistically significant differences in incidence were not clinically
important, except the incidence of peripheral artery disease, in which a
3\% lower incidence was found in the WR than in the other regions.

\emph{Incidence of STEMI and NSTEMI in the investigated regions}

The age-standardised incidence (confidence intervals) of AMI in the
population over 30 years per 100,000 person-years was 177.5
(175.7--179.39). There were some differences among regions: WR: 171.4
(168.3-174.5), CR: 179.1 (175.9--182.4), ER: 181 (178.2--183.9).

\emph{Ratios of invasive treatments for different types of myocardial
infarction per region}

The ratios of invasive treatments were significantly greater for STEMI
than for NSTEMI in all regions. The percentages of revascularisation
performed in the STEMI group in the WR, CR and ER were 83.0\%, 82.5\%
and 84.6\%, respectively; in the NSTEMI group, revascularisation was
performed in 54.8\%, 55.7\% and 58.8\% of patients, respectively. In the
ER, the ratio of revascularisation was significantly higher than in the
other two regions (p \textless{} 0.05).

\emph{Patient delay, prehospital response time and types of infarction
per region}

Patient delay and emergency care times were available for 6,878 patients
treated for infarction; 3,264 (47.5\%) were hospitalised for STEMI
(median times are summarised in \textbf{Table 2} according to diagnosis
and regional division). For both types of infarction, the time interval
between T1 and T2 was longest in the CR, whereas T3 was the shortest in
this region. The median emergency care times were longest in the CR for
the STEMI group and the ER for the NSTEMI group (\textbf{Figure 2 a-b}
). TIT was examined in the 3,264 patients with STEMI treated with PCI;
unfortunately, this time interval significantly exceeded the optimal
value in all three regions. Similar TIT values were observed in the WR
and CR (221 and 225 min, respectively), and it was 262 min in the ER.
Patient delay was determined in minutes per region (q1; q3): WR, 91
(37.25; 265.5); CR, 97 (34.0; 265.5) and ER, 111 (39.5; 292.5). More
than 40\% of the TIT was caused by patient delay.

\emph{Ratios of pharmacological treatment for secondary prevention per
region}

\textbf{Figure 3} shows the pharmacological treatment for secondary
prevention recommended upon hospital discharge per region. The
recommended ratio of the drugs for both types of infarction and in all
three regions was high. The rates of RAAS inhibitor treatment for STEMI
were significantly lower in the ER than in the CR (78.7\% vs. 83.6\%),
but the ratios for beta-blocker therapy were lower in the WR than in the
other two regions for both types of infarction.

\emph{Follow-up duration and 30-day and 1-year mortality data for both
myocardial infarction per region}

Patients were followed up for a total of 678 ± 431 days; all-cause
mortality data are summarised in \textbf{Table 3} . All-cause mortality
rates for both sexes and both types of infarction were lower when PCI
was performed on the patient. In numerous cases, the analysis confirmed
more favourable mortality data in the WR. Regarding the STEMI group,
male patients and patients who underwent PCI, mortality was lowest in
the WR at both examined times (p = 0.03, p \textless{} 0.01). In female
patients of the same group---independent of treatment received (PCI vs.
no PCI)---mortality was lowest in the WR at both examined times; a
significant difference was only found in the 1-year mortality rate of
patients treated via PCI (p = 0.04).

No statistically significant differences were observed regarding the
30-day mortality rate of the NSTEMI group among the three regions;
however, the lowest values were detected in the ER in males and the WR
in females. At the 1-year checkpoint, females who underwent PCI in the
WR exhibited significantly lower mortality values than in the CR (p
\textless{} 0.01). Upon comparison between females in the STEMI and
NSTEMI groups at the 30-day checkpoint, mortality rate was higher in the
STEMI group than in the NSTEMI group. The mortality rate among males
showed no differences between the STEMI and NSTEMI groups; however, at
the 1-year checkpoint, the NSTEMI group had a higher mortality rate than
the STEMI group for both sexes (males vs. females, NSTEMI: 22.3\% vs.
17.2\%; STEMI; 28.2\% vs. 26.1\%).

\emph{Comparison of Kaplan--Meier survival curves and Cox regression
analysis of mortality data}

\textbf{Figures} \textbf{4} and \textbf{5} show the survival curves of
patients with NSTEMI and STEMI. Considering confidence intervals, we
found that the differences among the regions were borderline significant
in the NSTEMI group, whereas the 1-year survival of the STEMI group
(\textbf{Figure 4} ) was significantly better in the WR. As several
factors influence survival, multivariate analysis was also performed
using Cox regression analysis. During multiple factor analysis, age,
sex, prior ischaemic events (infarction or stroke), presence of
comorbidities, revascularisation performed during treatment and region
of settlement were considered.

In the STEMI group, age and history of stroke, comorbidities, diabetes
mellitus and peripheral artery disease significantly worsened survival
rates throughout the entire follow-up period, whereas the survival rates
of patients who received PCI treatment were significantly better than of
those who did not receive invasive treatment at all checkpoints. In the
NSTEMI group, age and history of stroke, diabetes mellitus and
peripheral artery disease significantly worsened patient outcomes
throughout the entire follow-up period, whereas PCI treatment
significantly lowered their mortality rates. When analysing both types
of infarction together, age and history of stroke, diabetes mellitus and
peripheral artery disease were confirmed to have a negative impact on
survival rate, whereas PCI treatment showed a positive effect.

Logistical regression analysis confirmed several factors influencing
survival (\textbf{Figures 6 and} 7); among them, the region with
independent importance: 30-day mortality; in the case of STEMI, the risk
of death in the WR was 12\% lower than in the ER (Hazard ratio = 0.88, p
= 0.01144). At the 1-year checkpoint the region did not influence
survival. Analysis of the 1-year survival data of the NSTEMI group
showed that the mortality risk of patients living in the CR was 13.9\%
lower than those in the ER (Hazard ratio = 0.861; p = 0.0218).

\textbf{Discussion}

The Seven Countries Study is a significant milestone in epidemiological
research on cardiovascular diseases. The study, which included seven
countries, was the first to confirm that the incidence of coronary
disease was significantly different among countries (19), with the
incidence of the disease is exceptionally high in Finland. Further
research also revealed a significant difference between the WR and ER of
Finland (20). Knowledge of the shocking extent of this difference, as
well as local initiative, resulted in the launch of the North Karelia
Project, which eventually demonstrated that the incidence of myocardial
infarction could be decreased by the population-level control of the
risk factors (21). Several publications appeared following these
classical studies, whose authors called attention to regional
differences regarding the incidence and treatment of myocardial
infarction (13, 22-29). Upon examining the same problem, several
articles underlined the role of the social environment of the population
(30-33).

In a meta-analysis of several studies, Manrique-Garcia et al. (14) found
that the incidence of myocardial infarction was influenced both by the
social and economic status of the population, as well as their
educational background, i.e. the incidence of myocardial infarction was
higher in underprivileged people. Israeli authors compared the hospital
treatment data of Israeli-born and immigrant patients treated for
myocardial infarction, along with their short- and long-term mortality
rates. Israeli-born citizens showed a higher ratio of revascularisation
for STEMI, whereas their short- and long-term mortality rates were
lower. Among the immigrant patients, the highest 10-year mortality rates
were detected in those who migrated from Yemen, Southern Europe and the
Balkans; the prognoses of Central European and Pakistani immigrants
showed no differences (34). For the complex examination of infarction
care, continuous registers were created in several European countries
(2, 3, 5), enabling quality assurance for care, as well as monitoring of
changes in treatment. Based on population data, it has become possible
to compare data from different countries (6, 8, 9); nevertheless, when
evaluating the data, methodological differences pose a problem (10).

The European Society of Cardiology initiated a European registry
programme to uniformly follow major cardiological diseases in 2019,
called Unified Registries On Heart Care Evaluation and Randomised Trials
(11). In the present study, we compared the data of the three major
regions of Hungary with respect to the incidence of myocardial
infarction, patients' clinical data, emergency care and prognosis. Both
types of infarction were most common (42.9\% and 36.3\% of all
cardiovascular events), and the incidence of myocardial infarction was
highest in the ER. Compared with US data from 2008, the incidence of
myocardial infarction for the total population was higher in Hungary:
177.5\% vs. 168 per 100,000 person-years (35). Stroke and peripheral
artery disease were also the most common diseases in the medical history
of patients living in the ER, wherein TIT was longest (262 min). Delays
until revascularisation were primarily caused by patient delay as the
most unfavourable values in emergency care were found in the CR (in the
case of T1 and T2 values). The revascularisation ratio was 84.6\% in the
STEMI group and 58.8\% in the NSTEMI group.

\textbf{Limitations of the study}

We examined regional differences in the care and prognosis of patients
treated for myocardial infarction. The differences found are apt to draw
attention to the importance of the issue. At the same time, however,
there are exceptionally large socio-economic differences within large
regions (university town vs. hard-to-reach village), so it is necessary
to analyse data from smaller territorial units to examine access to
modern care.

\textbf{Conclusion}

Among the three included regions of Hungary, significant differences
were detected in the incidence of AMI, TIT of patients with STEMI and
their mortality rates. Additionally, logistic regression analysis
confirmed the independent prognostic significance of the region
regarding 30-day mortality; however, further research is necessary to
explore the data of smaller regional units with respect to infarction
treatment, with particular regard to accessing up-to-date care and
secondary prevention.

Acknowledgments: We would like to thank all participants of HUMIR and
Editage (www.editage.com) for English language editing.

Conflict of Interest: none declared.

Data availability: The data from HUMIR that support the findings of this
study are available on reasonable request to the corresponding author.

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Title and table legends:

Table 1. Regional distributions of different type of myocardial
infarctions, medical history, and comorbidities

Legend: In the right column of the results table, the p-value of the
Chi-squared test is represented, i.e. whether the value of the examined
factors (e.g. the ratio of myocardial infarction) depends on the value
of another factor (e.g. in the present case, the region). We then added
the post-hoc test results after the p-value in brackets (regionally
differentiating between leftover tag values and p-values to show whether
the given region is significantly different in terms of frequency from
the whole).

Table 2. Patient delay, prehospital response time and types of
infarction per region

Table 3. 30-day and 1-year mortality of men and women in different types
of myocardial infarction treated with and without PCI, per region

Legend: The first p value belongs to the chi-squre test, while in
brackets the results of the post hoc tests are to be found

Title and figure legends:

Figure 1. The regions and their population data

Legend: WR: Western Region, CR: Central Region, ER: Eastern Region

Figure 2.a Time intervals of the emergency care process, NSTEMI

Legend: Arrival to location (T1), treatment on-site (T2) and time
interval between transferring the patient from the original location to
the hospital (T3)

Figure 2.b Time intervals of the emergency care process, STEMI

Legend: Arrival to location (T1), treatment on-site (T2) and time
interval between transferring the patient from the original location to
the hospital (T3)

Figure 3. Pharmacological treatment for secondary prevention recommended
upon hospital discharge per region.

Legend: WR: Western Region, CR: Central Region, ER: Eastern Region,
RAAS: renin--angiotensin--aldosterone system, PI: platelet inhibitors

Figure 4. Kaplan--Meier survival curves by regions, NSTEMI

Legend: Survival probabilities (lines and dots) and their confidence
intervals (vertical sections) are represented, per region

Figure 5. Kaplan--Meier survival curves by regions, STEMI

Legend: Survival probabilities (lines and dots) and their confidence
intervals (vertical sections) are represented, per region

Figure 6. Results of Cox Proportional Hazards Regression Model, NSTEMI

Legend: First column contains names of variables (the factors examined),
second column shows the mortality period, third and fourth column show
hazard ratio (HR) values in diagram and in tabulated formats (hazard
ratio denoted by with square and their confidence intervals denoted by
horizontal lines), fifth column shows the probability (P) values (a
variable was significant where P value was below 0.05, it is denoted by
0)

Figure 7. Results of Cox Proportional Hazards Regression Model, STEMI

Legend: First column contains names of variables (the factors examined),
second column shows the mortality period, third and fourth column show
hazard ratio (HR) values in diagram and in tabulated formats (hazard
ratio denoted by with square and their confidence intervals denoted by
horizontal lines), fifth column shows the probability (P) values (a
variable was significant where P value was below 0.05, it is denoted by
0)

\textbf{Hosted file}

\verb`Table 1.docx`  available at \url{https://authorea.com/users/423131/articles/528672-incidence-pre-hospital-delay-and-prognosis-of-acute-myocardial-infarction-in-hungary-population-data-from-the-hungarian-myocardial-infarction-registry}

\textbf{Hosted file}

\verb`Table 2.docx`  available at \url{https://authorea.com/users/423131/articles/528672-incidence-pre-hospital-delay-and-prognosis-of-acute-myocardial-infarction-in-hungary-population-data-from-the-hungarian-myocardial-infarction-registry}

\textbf{Hosted file}

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