editorial original articles review articles case reports

100 Pages·2017·3.55 MB·English

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ne EDITORIAL High Blood Pressure in Pre-Adolescents and
nli Adolescents in Petrópolis: Prevalence and Correlation
N o Artificial Intelligence and Machine Learning in with Overweight and Obesity
S Cardiology - A Change of Paradigm
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2 | I REVIEW ARTICLES
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8 ORIGINAL ARTICLES
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9- Effects of Hypoxia on Heart Rate Variability in Healthy
35 Profile of Patients Hospitalized for Heart Failure in Individuals: A Systematic Review
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Ju Reperfusion and eNOS/iNOS Expression
y / Case Report: Catheter-related interatrial septum
Ma Association between Erectile Dysfunction and Quality endocarditis caused by Candida parapsilosis
3 | of Life in Patients with Coronary Artery Disease
er Takotsubo Cardiomyopathy with Extracorporeal
b Evaluation of Endothelial Function in Pre-Menopausal Membrane Oxygenation (ECMO) Requirement After
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u Women with Coronary Arterial Disease Atrial Myxoma Surgery
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SUMMARY
• Editorial
Artificial Intelligence and Machine Learning in Cardiology - A Change of Paradigm .................................................. 187
Claudio Tinoco Mesquita
• Original Articles
Profile of Patients Hospitalized for Heart Failure in Tertiary Care Hospital ................................................................... 189
Milton Ricardo Poffo, Amberson Vieira de Assis, Maíra Fracasso, Ozir Miguel Londero Filho, Sulyane Matos de Menezes
Alves, Ana Paula Bald, Camila Bussolo Schmitt, Nilton Rogério Alves Filho
Matricial Support and Arterial Hypertension Control ......................................................................................................... 199
Clóvis Hoepfner, Morgana Longo, Andressa de Oliveira Coiradas, Laíssa Mara Rodrigues Teixeira
Gallic Acid and Cyclosporine Mixture and their Effects on Cardiac Dysfunction Induced by Ischemia/Reperfusion
and eNOS/iNOS Expression ..................................................................................................................................................... 207
Mohammad Badavi, Najmeh Sadeghi, Mahin Dianat, Alireza Samarbafzadeh
Association between Erectile Dysfunction and Quality of Life in Patients with Coronary Artery Disease ............... 219
André Tabosa, Dinaldo Cavalcanti de Oliveira, Vitor H. Stangler, Henrique Araújo, Vitor Nunes, Maria Isabel
Gadelha, Danielle A. G. C. Oliveira, Emmanuelle Tenório
Evaluation of Endothelial Function in Pre-Menopausal Women With Coronary Arterial Disease ............................. 227
Wilma Karlla dos Santos Farias, Tania Pavão Oliveira Rocha, Jorgileia Braga de Melo, Erika Joseth Nogueira da Cruz
Fonseca, Darci Ramos Fernandes, Leticia Prince Pontes, Maria Valneide Gomes Andrade, José Albuquerque de Figueiredo
Neto
Assessment of Bioactive Compounds, Physicochemical Composition, and In Vitro Antioxidant Activity of
Eggplant Flour ............................................................................................................................................................................. 235
Mauara Scorsatto, Aline de Castro Pimentel, Antonio Jorge Ribeiro da Silva, Kebba Sabally, Glorimar Rosa, Gláucia
Maria Moraes de Oliveira
High Blood Pressure in Pre-Adolescents and Adolescents in Petrópolis: Prevalence and Correlation with Overweight
and Obesity .................................................................................................................................................................................. 243
Flavio Figueirinha e Gesmar Volga Haddad Herdy

• Review Articles
Effects of Hypoxia on Heart Rate Variability in Healthy Individuals: A Systematic Review ......................................... 251
André Luiz Musmanno Branco Oliveira, Philippe de Azeredo Rohan, Thiago Rodrigues Gonçalves, Pedro Paulo da
Silva Soares
Methods of Endothelial Function Assessment: Description and Applications ................................................................ 262
Amanda Sampaio Storch, João Dario de Mattos, Renata Alves, Iuri dos Santos Galdino, Helena Naly Miguens Rocha
• Case Reports
Case Report: Catheter-related interatrial septum endocarditis caused by Candida parapsilosis ................................... 274
Gustavo Neves de Araújo, Felipe H. Valle, Douglas M. Freitas, Felipe Martins Lampa, Miguel Gus, Luis E. Rohde
Takotsubo Cardiomyopathy with Extracorporeal Membrane Oxygenation (ECMO) Requirement After Atrial Myxoma
Surgery ......................................................................................................................................................................................... 277
Fernando Garagoli, Aníbal Arias, Vadim Kotowicz, Arturo Cagide, César Belziti
ISSN 2359-4802 / IJCS ONLINE: ISSN 2359-5647
Editor Guilherme Vianna e Silva (Interventionist Cardiology Area) – Texas Heart
Institute, USA
Cláudio Tinoco Mesquita – Hospital Universitário Antônio Pedro (HUAP),
Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, RJ – Brazil João Augusto Costa Lima (Integrative Imaging Area) – Johns Hopkins
Hospital – Baltimore, USA
Lauro Casqueiro Vianna (Multiprofessional Area) – Faculdade de Educação
Associated Editors
Física, Universidade de Brasília (UnB), Brasília, DF – Brazil
Clério Francisco Azevedo Filho (Cardiovascular Imaging Area) – Miguel Mendes (Ergometric and Cardiac Rehabilitation Area) – Sociedade
Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ - Brazil Portuguesa de Cardiologia, Portugal
Gláucia Maria Moraes de Oliveira (Clinical Cardiology Area) – Departamento Ricardo Mourilhe-Rocha (Heart Failure and Myocardiopathy Area) –
de Clínica Médica, Faculdade de Medicina (FM), Universidade Federal do Hospital Universitário Pedro Ernesto, Universidade do Estado do Rio de
Rio de Janeiro (UFRJ), Rio de Janeiro, RJ - Brazil Janeiro (UERJ), Rio de Janeiro, RJ - Brazil
EDITORIAL BOARD Leonardo Silva Roever Borges – Departamento de Pesquisa Clínica,
Universidade Federal de Uberlândia (UFU), MG – Brazil
Brazil Leopoldo Soares Piegas – Fundação Adib Jatene, Instituto Dante Pazzanese
de Cardiologia (IDPC/FAJ), São Paulo, SP - Brazil
Andréia Biolo – Faculdade de Medicina, Universidade Federal do Rio Grande
Luís Alberto Oliveira Dallan – Serviço Coronariopatias, Instituto do Coração
do Sul (UFRGS), Porto Alegre, RS – Brazil
(INCOR), São Paulo, SP - Brazil
Angelo Amato Vincenzo de Paola – Escola Paulista de Medicina (EPM),
Marcelo Iorio Garcia – Clínica de Insuficiência Cardíaca, Universidade Federal
Universidade Federal de São Paulo (UNIFESP), São Paulo, SP – Brazil
do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ – Brazil
Antonio Cláudio Lucas da Nóbrega – Centro de Ciências Médicas,
Marcelo Westerlund Montera – Centro de Insuficiência Cardíaca, Hospital
Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, RJ – Brazil
Pró Cardíaco (PROCARDIACO), Rio de Janeiro, RJ – Brazil
Ari Timerman – Unidades de Internação, Instituto Dante Pazzanese de
Marcio Luiz Alves Fagundes – Divisão de Arritmia e Eletrofisiologia, Instituto
Cardiologia (IDPC), São Paulo, SP - Brazil
Nacional de Cardiologia Laranjeiras (INCL), Rio de Janeiro, RJ – Brazil
Armando da Rocha Nogueira – Departamento de Clínica Médica, Marco Antonio Mota Gomes - Fundação Universitária de Ciências da Saúde
Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ - Brazil Governador Lamenha Filho (UNCISAL), Maceió, AL - Brazil
Carísi Anne Polanczyk – Hospital de Clínicas de Porto Alegre, Universidade Marco Antonio Rodrigues Torres – Departamento de Medicina Interna,
Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS – Brazil Hospital de Clínicas de Porto Alegre, Porto Alegre, RS – Brazil
Carlos Eduardo Rochitte – Departamento de Cardiopneumologia, Hospital Marcus Vinicius Bolivar Malachias – Instituto de Pesquisas e Pós-
das Clínicas da Faculdade de Medicina da Universidade de São Paulo graduação (IPG), Faculdade de Ciências Médicas de Minas Gerais
(HCFMUSP), São Paulo, SP – Brazil (FCMMG), Belo Horizonte, MG – Brazil
Carlos Vicente Serrano Júnior – Faculdade de Medicina da Universidade de Maria Eliane Campos Magalhães – Departamento de Especialidades Médicas,
São Paulo, Instituto do Coração (InCor), São Paulo, SP – Brazil Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ – Brazil
Cláudio Gil Soares de Araújo – Instituto do Coração Edson Saad, Universidade Mário de Seixas Rocha – Unidade Coronariana, Hospital Português,
Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ - Brazil Salvador, BA – Brazil
Cláudio Pereira da Cunha – Departamento de Clínica Médica, Universidade Maurício Ibrahim Scanavacca – Unidade Clínica de Arritmia, Instituto do
Federal do Paraná (UFPR), Paraná, PR – Brazil Coração do Hospital das Clínicas da FMUSP, São Paulo, SP – Brazil
Cláudio Tinoco Mesquita – Hospital Universitário Antônio Pedro (HUAP), Nadine Oliveira Clausell – Faculdade de Medicina, Universidade Federal do
Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, RJ – Brazil Rio Grande do Sul (UFRGS), Porto Alegre, RS – Brazil
Denílson Campos de Albuquerque – Faculdade de Ciências Médicas, Nazareth de Novaes Rocha – Centro de Ciências Médicas, Universidade
Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ – Brazil Federal Fluminense, UFF - Rio de Janeiro, RJ – Brazil
Denizar Vianna Araujo – Departamento de Clínica Médica, Universidade do Nelson Albuquerque de Souza e Silva – Departamento de Clínica
Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ – Brazil Médica, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro,
RJ – Brazil
Esmeralci Ferreira – Hospital Universitário Pedro Ernesto (HUPE),
Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, RJ - Brazil Paola Emanuela Poggio Smanio – Seção Médica de Medicina Nuclear,
Instituto Dante Pazzanese de Cardiologia (IDPC) São Paulo, SP - Brazil
Evandro Tinoco Mesquita – Hospital Universitário Antônio Pedro (HUAP),
Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, RJ – Brazil Paulo Cesar Brandão Veiga Jardim – Liga de Hipertensão Arterial,
Universidade Federal de Goiás (UFGO), Goiânia, GO – Brazil
Fernando Nobre – Faculdade de Medicina de Ribeirão Preto (FMRP),
Ronaldo de Souza Leão Lima – Pós-Graduação em Cardiologia, Universidade
Universidade de São Paulo, São Paulo, SP – Brazil
Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ – Brazil
Gabriel Blacher Grossman – Serviço de Medicina Nuclear, Hospital Moinhos
Salvador Manoel Serra – Setor de Pesquisa Clínica, Instituto Estadual de
de Vento, Porto Alegre, RS – Brazil
Cardiologia Aloysio de Castro (IECAC), Rio de Janeiro, RJ – Brazil
Henrique César de Almeida Maia – Governo do Distrito Federal (GDF),
Sandra Cristina Pereira Costa Fuchs – Departamento de Medicina Social,
Brasília, DF - Brazil
Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre,
Humberto Villacorta Júnior – Hospital Universitário Antônio Pedro (HUAP), RS – Brazil
Universidade Federal Fluminense (UFF), Niterói, Rio de Janeiro, RJ – Brazil
Tiago Augusto Magalhães – Ressonância Magnética e Tomografia Cardíaca,
Iran Castro – Fundação Universitária de Cardiologia (FUC), Instituto de Hospital do Coração (HCor), São Paulo, SP – Brazil
Cardiologia do Rio Grande do Sul (IC), Porto Alegre, RS – Brazil
Walter José Gomes – Departamento de Cirurgia, Universidade Federal de
João Vicente Vitola – Quanta Diagnóstico e Terapia (QDT), Curitiba, PR – Brazil São Paulo (UFESP), São Paulo, SP – Brazil
José Geraldo de Castro Amino – Sessão Clínica, Instituto Nacional de Washington Andrade Maciel – Serviço de Arritmias Cardíacas, Instituto
Cardiologia (INC), Rio de Janeiro, RJ – Brazil Estadual de Cardiologia Aloysio de Castro (IECAC), Rio de Janeiro, RJ – Brazil
José Márcio Ribeiro – Clínica Médica (Ambulatório), União Educacional Vale Wolney de Andrade Martins – Centro de Ciências Médicas, Universidade
do Aço (UNIVAÇO), Ipatinga, MG - Brazil Federal Fluminense (UFF), Niterói, Rio de Janeiro, RJ – Brazil
Exterior Guilherme Vianna e Silva – Texas Heart Institute, Texas – USA
Amalia Peix – Instituto de Cardiología y Cirugía Cardiovascular, Havana – Cuba Horacio José Faella – Hospital de Pediatría S.A.M.I.C. “Prof. Dr. Juan P.
Amelia Jiménez-Heffernan – Hospital Juan Ramón Jiménez, Huelva – Spain Garrahan”, Caba – Argentina
Charalampos Tsoumpas – University of Leeds, Leeds – England James A. Lang – Des Moines University, Des Moines – USA
Chetal Patel – All India Institute of Medical Sciences, Delhi – Indian James P. Fisher – University of Birmingham, Birmingham – England
Edgardo Escobar – Universidad de Chile, Santiago – Chile João Augusto Costa Lima – Johns Hopkins Medicine, Baltimore – USA
Enrique Estrada-Lobato – International Atomic Energy Agency, Vienna – Austria Massimo Francesco Piepoli – Ospedale “Guglielmo da Saliceto”,
Erick Alexanderson – Instituto Nacional de Cardiología - Ignacio Chávez, Piacenza – Italy
Ciudad de México – México Raffaele Giubbini – Università degli Studi di Brescia, Brescia – Italy
Fausto Pinto – Universidade de Lisboa, Lisboa - Portugal Ravi Kashyap – International Atomic Energy Agency, Vienna – Austria
Ganesan Karthikeyan – All India Institute of Medical Sciences, Delhi – Indian Shekhar H. Deo – University of Missouri, Columbia - USA
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International Journal of Cardiovascular Sciences. 2017;30(3):187-188
187
EDITORIAL
Artificial Intelligence and Machine Learning in Cardiology - A Change of Paradigm
Claudio Tinoco Mesquita
Professor do Departamento de Medicina Clínica do Hospital Universitário Antônio Pedro, Universidade Federal Fluminense (UFF), Niterói, RJ – Brazil
A robot may not injure a human being or, through inaction, quality of the electrocardiographic signal for interpretation
allow a human being to come to harm. and learning, which highlights one of the essential
First Law of Robotics - Isaac Asimov
characteristics of Machine Learning, that is the need for
accurate and reproducible information for the formation
We are experiencing a change paradigm in modern life. of databases.2,3 As databases are usually produced from
With the presence of computers and intelligent machines patients selected for their basic condition, one of the
everywhere, the predictions of science-fiction books from most important points for development is the creation of
years ago gradually become reality; these are the times broader and generalizable databases that do not induce
of pervasive computing. Among the computational biases in the interpretation of findings, point in which
most frequently mentioned tools in clinical studies and industry is heavily investing at the moment.2
seen with enthusiasm by the scientific community is the In echocardiography, many studies are evaluating the
Artificial Intelligence and consequently the machines use of Machine Learning in image interpretation, such
that learn, which is best quoted in its original English as the Narula et al.4 who, through a database of patients
form, Machine Learning. In general Artificial Intelligence with hypertrophic cardiomyopathy and individuals with
is defined as the constellation of items (algorithms, physiological hypertrophy who were submitted to Speckle
robotics, neural networks) that allow a software to have Tracking, were able to create a computer system based
intelligence properties that are comparable to those of a on Machine Learnig that reached to assist inexperienced
human being, among them learning from databases with echocardiographers in distinguishing between the two
minimal human interference.1 conditions with excellent accuracy. Tajik,5 in an enthusiastic
Obermeyer and Emanuel recently wrote an editorial editorial, pointed out that Machine Learning should reduce
stating that Machine Learning has become widespread and or even eliminate the intra- and interobserver variability
imperative for solving complex problems in the various of echocardiographic exams and greatly reduce cognitive
fields of science, and in the medical field its use will errors. At this point the use of artificial intelligence comes
transform the practice.2 The use of artificial intelligence is across medical ethics, because the doubts that can occur
evolving increasingly in cardiology and there are already in cases of errors may be linked to the attribution of
excellent examples in several areas. Using a sophisticated responsibilities: did the doctor fail or did the software fail?
learning system to electrocardiographic interpretation, Experiences with the use of autopilots in aviation may serve
Li et al. achieved that electrocardiographic patterns as a basis for the ethical discussion that will occur, given that
were automatically recognized with an accuracy of 88% there is always at least one human being responsible for the
for the classification of abnormal rhythms(3). One of the flight even when using the modern devices of commercial
most important limitations of the system studied was the aviation. Obermeyer and Emanuel2 point out that there will
be a massive reduction in the need for doctors in situations
where computers can be fed directly by digital information
Keywords
such as radiology and pathology because the large amount
Artificial Intelligence/trends; Computer Systems/ of digital information available will allow the formation
trends; Machine Learning/trends; Cardiovascular Diseases; of reliable databases that will lead to a performance of the
Echocardiography/trends; NucleAR Medicine/trends. machines superior to the human.
Mailing Address: Cláudio Tinoco Mesquita
Hospital Universitário Antônio Pedro. Rua Marquês do Paraná, 303 – Centro. Postal Code: 24033-900 – Niterói, RJ – Brazil
E-mail: [email protected]
DOI: 10.5935/2359-4802.20170027 Manuscript received March 13, 2017; revised manuscript April 12, 2017; accepted April 12, 2017.
Int J Cardiovasc Sci. 2017;30(3):187-188 Mesquita
Editorial Artificial intelligence and machine learning in cardiology 188
When artificial intelligence is employed in more complex bias of clinicians and reduce intra and interobserver
clinical contexts, there is a still longer way to go. Austin et al.6 variability, allowing to interpret the exams faster and
used a Machine Learning and data mining system to with greater accuracy, as observed in studies in which
evaluate and classify patients with heart failure and found the diagnostic interpretation of the examination by the
that although the system was superior to conventional computer is similar to that of the experts.10 We generally
methods for predicting heart failure with preserved ejection agree with this view and consider that the support to
fraction, there were no advantages over the traditional make the clinical decision and the improvement of
logistic regression. Liu et al.7 developed a system based on diagnostic and prognostic performances should be
Machine Learning for prediction of adverse coronary events encouraged and supported by physicians of the various
in patients with chest pain in the emergency room and specialties. The frequent concern about the eventual
compared it with the TIMI score. Although the performance replacement of the physician by the machines is not
of the new system is reliable for predicting mortality substantiated by the facts. The medical profession is
and cardiac events in 30 days, the authors themselves of a complexity and subjectivity that makes the task
acknowledge that clinical decisions are dependent on factors impossible in its entirety by the machines, at least at
that still can not be fully incorporated into the machines, one the present stage of knowledge. The proper use of
of which is the physicians experience.7 computing allows for not only the improved of medical
In nuclear cardiology Arsanjani et al.8 evaluated performance but also the quest for solidarity among
the use of the Machine Learning tool to predict patients with successful experiences in creating social
myocardial revascularization from myocardial perfusion networks for patients.11
scintigraphy data, finding an accuracy comparable Only the study of the profound impact for the
or even superior to that of experienced examiners in development and use of these tools can bring the answers
the interpretation of the scintigraphic examination. to the questions that are now in the minds of doctors and
Garcia et al.,9 in an excellent review on the subject, their patients. The International Journal of Cardiovascular
point out that clinical decision support and artificial Sciences encourages its readers and contributors to send
intelligence systems serve as warnings for the cognitive scientific papers on the subject for publication.
References
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Nucl Med. 2017;58(3):357-8. Risk stratification for prediction of adverse coronary events in emergency
department chest pain patients with a machine learning score compared
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189
ORIGINAL ARTICLE
Profile of Patients Hospitalized for Heart Failure in Tertiary Care Hospital
Milton Ricardo Poffo,1 Amberson Vieira de Assis,1 Maíra Fracasso,1 Ozir Miguel Londero Filho,1 Sulyane Matos de
Menezes Alves,1 Ana Paula Bald,2 Camila Bussolo Schmitt,2 Nilton Rogério Alves Filho3
Instituto de Cardiologia de Santa Catarina,1 São José, SC; Universidade do Sul de Santa Catarina,2 Palhoça, SC; Universidade do Sul de Santa Catarina,3
Florianópolis, SC − Brazil
Abstract
Background: Heart failure is a highly prevalent disease, responsible for many admissions and high mortality rates
in our country. The treatment influences patient's mortality and quality of life.
Objective: To identify and compare the clinical and epidemiological survivor's and non-survivor's profiles and
treatment of patients hospitalized with heart failure with the international literature.
Methods: Cross-sectional, retrospective study of 816 survivors and non-survivors with heart failure. All patients
had their clinical and epidemiological, laboratory and echocardiographic data and treatment recorded.
Results: Most patients were in functional class III/IV. Mean age was 66.5 ± 13.8 years. Half of the patients were
men and 88.3% were Caucasians. In-hospital mortality was 11,2%. Highly mortality was associated with old age,
Caucasian ethnicity, high functional class, readmissions, prolonged hospitalization, presence of coronary artery
disease, chronic atrial fibrillation, severe mitral regurgitation, restrictive diastolic dysfunction, renal dysfunction,
and elevated natriuretic peptide levels, as well as with patients who had pulmonary embolism, acute coronary
syndrome, pulmonary infection or required dialysis during hospitalization. The use of angiotensin-converting
enzyme inhibitors or angiotensin-receptor blockers at admission was significantly higher among survivors.
Conclusion: In-hospital mortality was high when compared to international averages, but it was similar to other Brazilian
referral services. Numerous higher severity indicators were observed in the non-survivor group. (Int J Cardiovasc Sci.
2017;30(3):189-198)
Keywords: Heart Failure / mortality; Prevalence; Hospitalization; Restrospective Studies.
Introduction the treatment of acute myocardial infarction (AMI),
systemic arterial hypertension (SAH) and even HF,
Heart Failure (HF) is the common final pathway of
which increase survival and, consequently, promote an
most heart diseases, and is one of the major current
increase in its prevalence.1,4
clinical challenges in health.1 Approximately 23 million
In the United States, approximately 550,000 new
individuals have HF, and 2 million new cases are
cases are diagnosed annually, being the fifth most
diagnosed every year worldwide,2 being the main cause
of hospitalization in patients older than 60 years of age frequent cause of hospitalization.5 In Brazil, according
in Brazil.3 to data from the Unified Health System Department
of Informatics (DATASUS), in 2012, approximately
The prevalence of HF has been increasing in recent
years worldwide,4 and has become a serious public 238,000 hospitalizations occurred due to HF, with
health problem.3 The reasons for this include the 26,000 deaths, accounting for a mortality rate of 9.5%
aging of the population and therapeutic advances in during hospitalization.6 The BREATHE (Brazilian
Mailing Address: Milton Ricardo Poffo
Instituto de Cardiologia de Santa Catarina. Rua Adolfo Donato da Silva, s/n, Praia Comprida. Postal Code: 88.103-901, São José, SC − Brazil.
E-mail: [email protected]
DOI: 10.5935/2359-4802.20170044 Manuscript received March 02, 2016; revised manuscript March 24, 2016; accepted January 31, 2017.
Int J Cardiovasc Sci. 2017;30(3):189-198 Poffo et al.
Original Article Heart failure in cardiology hospital 190
Registry of Acute Heart Failure) trial identified an (ICD-10) compatible with HF, namely: I11, I13, I50 and
in-hospital mortality of 12.6%.7 I57, were included in the study. Patients with a clinical,
Many comorbidities associated with HF worsen its echocardiographic and laboratory picture incompatible
prognosis. Atrial fibrillation (AF) affects approximately with this comorbidity, in addition to those whose medical
20% to 30% of patients with acute HF.8 The prevalence of records were incomplete, were excluded.
renal failure in outpatients with HF may reach 29.6%,9 being Patient selection was performed by checking the
a marker of poor prognosis.10 Moreover, hyponatremia, electronic medical record system (Micromed®). Aiming at
elevated levels of Type B Natriuretic Peptide (BNP), a more adequate analysis, the patients were divided
multiple hospitalizations, and associated lung disease are into two groups: Group I, of survivors and Group II, of
also predictors of poor prognosis.11 non-survivors. The final sample analyzed 816 patients
(724 survivors and 92 non-survivors), as shown in figure 1.
Currently, there are six classes of therapeutic measures
capable of reducing all-cause mortality in HF patients, Data collection was performed using the Micromed®
considered by global guidelines as class I indication system in Laboratório Bioclínico São José and the ICSC
measures.12 However, in Brazil, medications introduced Echocardiography Service. Clinical-demographic data,
during the in-hospital phase often do not follow the current such as age, gender, ethnicity, functional class, presence
guidelines, which may contribute to the high morbidity, of comorbidities, complications during hospitalization,
mortality, and economic costs of this syndrome.7 mortality and prescribed medications were analyzed.
The laboratory tests analyzed were urea, creatinine,
Despite the recent advances in the treatment of HF, the
sodium, potassium, BNP, and hemoglobin. Among the
mortality among patients that are hospitalized with this
echocardiographic data, left ventricular ejection fraction
syndrome in Brazil is still high. The objective of this study
(Simpson's method), left ventricular systolic diameter, left
was to identify and compare the clinical-epidemiological
ventricular diastolic diameter, valvular heart disease, and
profile and the treatment received by survivors and
left ventricular relaxation alterations were analyzed.
non-survivors hospitalized with heart failure to the
international literature data. As the study was retrospective, the demographic data
were collected by searching the Micromed® system.
Methods The patient’s ethnicity was the self-declared one when the
patient or the companion was registered at the institution.
This is an observational, cross-sectional, and The existence of SAH and diabetes was obtained from data
retrospective study of patients with HF who survived found in the electronic medical record (evolution data,
or not after being admitted at Instituto de Cardiologia de previous diagnoses, and medication use).
Santa Catarina (ICSC) between June 2010 and May 2014. This study was approved by the Research Ethics
Patients older than 18 years admitted during the study Committee (REC) of ICSC, under registration number
period according to the International Code of Diseases 045475/2015.
841 patients 25 excluded
(1011 admissions)
16 due to
724 survivors 117 deaths missing data
92 included
9 no diagnosis
25 excluded
Figure 1 – Patient selection flow chart