Cardiac murmurs in children.

BACKGROUND: Approximately 50% of children experience a cardiac murmur at some point in their lives; <1% of these murmurs are attributed to congenital heart disease (CHD). Cardiac murmur might be the first clinical sign of a significant CHD in children. Despite careful routine medical examinations at birth, approximately 50% of CHD cases could remain unrecognised. OBJECTIVE: Cardiovascular symptoms and signs could be specific or non-specific in neonates and children with heart murmurs. Knowledge about red flags in history and physical examinations, and syndromic associations of common CHDs are important. Auscultatory skills to identify systolic, diastolic and continuous murmurs and heart sounds are essential. Differential diagnosis should be formulated based on the location of maximum intensity of murmurs. Younger infants and children with pathological murmurs and red-flag signs should be promptly referred to local paediatric cardiology services for further investigations. DISCUSSION: Significant skill and knowledge are required for the identification of critical murmurs and associated cardiovascular problems. This review provides a simplified comprehensive update on cardiac murmurs and associated conditions in neonates and children.

Voice reduction in cardiac auscultation sounds with reference signals measured from vocal resonators.

This study proposes the use of vocal resonators to enhance cardiac auscultation signals and evaluates their performance for voice-noise suppression. Data were collected using two electronic stethoscopes while each study subject was talking. One collected auscultation signal from the chest while the other collected voice signals from one of the three voice resonators (cheek, back of the neck, and shoulder). The spectral subtraction method was applied to the signals. Both objective and subjective metrics were used to evaluate the quality of enhanced signals and to investigate the most effective vocal resonator for noise suppression. Our preliminary findings showed a significant improvement after enhancement and demonstrated the efficacy of vocal resonators. A listening survey was conducted with thirteen physicians to evaluate the quality of enhanced signals, and they have received significantly better scores regarding the sound quality than their original signals. The shoulder resonator group demonstrated significantly better sound quality than the cheek group when reducing voice sound in cardiac auscultation signals. The suggested method has the potential to be used for the development of an electronic stethoscope with a robust noise removal function. Significant clinical benefits are expected from the expedited preliminary diagnostic procedure.

Simulation-guided auscultatory training before graduation is associated with better auscultatory skills in residents.

INTRODUCTION: A growing body of scientific evidence shows that simulation-guided auscultatory training can significantly improve the skills of medical students. Nevertheless, it remains to be elucidated if this training has any long-term impact on auscultatory skills. We sought to ascertain whether there were differences in heart and lung auscultation among residents who received simulation-guided auscultatory training before graduation vs. those who did not. MATERIALS AND METHODS: A total of 43 residents were included in the study; 20 of them entered into Cardiology specialty school (C) and 23 of them entered into Internal and Occupational Medicine specialty schools (M) at the University of Trieste. Based on the history of simulation-guided auscultatory training before graduation (yes = Y; no = N), four groups were formed: CY, CN, MY, and MN. Residents were evaluated in terms of their ability to recognize six heart and five lung sounds, which were reproduced in a random order with the Kyoto-Kagaku patient simulator. Associations between history of simulation training, specialty choice and auscultatory skills were evaluated with Kruskal-Wallis test and logistic regression analysis. RESULTS: Auscultatory skills of residents were associated with simulation-guided training before graduation, regardless of the specialty chosen. Simulation-guided training had a higher impact on residents in Medicine. Overall, heart and lung sounds were correctly recognized in 41% of cases. Logistic regression analysis showed that simulation-guided training was associated with recognition of aortic stenosis, S2 wide split, fine crackles, and pleural rubs. Specialty choice was associated with recognition of aortic stenosis as well as aortic and mitral regurgitation. DISCUSSION: History of simulation-guided auscultatory training was associated with better auscultatory performance in residents, regardless of the medical specialty chosen. Choice of Cardiology was associated with better scores in aortic stenosis as well as aortic and mitral regurgitation. Nevertheless, overall auscultatory proficiency was quite poor, which suggests that simulation-guided training may help but is probably still too short.

Evaluation of a digitally enhanced cardiac auscultation learning method in Cameroon: results of a controlled study.

BACKGROUND: Cardiac auscultation is an efficient and effective diagnostic tool, especially in low-income countries where access to modern diagnostic methods remains difficult. This study aimed to evaluate the effect of a digitally enhanced cardiac auscultation learning method on medical students' performance and satisfaction. METHODS: We conducted a double-arm parallel controlled trial, including newly admitted 4th -year medical students enrolled in two medical schools in Yaoundé, Cameroon and allocated into two groups: the intervention group (benefiting from theoretical lessons, clinical internship and the listening sessions of audio recordings of heart sounds) and the control group (benefiting from theoretical lessons and clinical internship). All the participants were subjected to a pretest before the beginning of the training, evaluating theoretical knowledge and recognition of cardiac sounds, and a post-test at the eighth week of clinical training associated with the evaluation of satisfaction. The endpoints were the progression of knowledge score, skills score, total (knowledge and skills) score and participant satisfaction. RESULTS: Forty-nine participants (27 in the intervention group and 22 in the control group) completed the study. The knowledge progression (+ 26.7 versus + 7.5; p ˂0.01) and the total progression (+ 22.5 versus + 14.6; p ˂ 0.01) were higher in the intervention group with a statistically significant difference compared to the control group. There was no significant difference between the two groups regarding skills progression (+ 25 versus + 17.5; p = 0.27). Satisfaction was higher in general in the intervention group (p ˂ 0.01), which recommended this method compared to the control group. CONCLUSION: The learning method of cardiac auscultation reinforced by the listening sessions of audio recordings of heart sounds improves medical students' performances (knowledge and global - knowledge and skills) who find it satisfactory and recommendable. TRIAL REGISTRATION: This trial has been registered the 29/11/2019 in the Pan African Clinical Trials Registry ( http://www.pactr.org ) under unique identification number PACTR202001504666847 and the protocol has been published in BMC Medical Education.

Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning.

OBJECTIVE: To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and pathologic murmurs. METHODS: We prospectively enrolled children under age 18 being evaluated by the Division of Pediatric Cardiology. Parents provided consent for a deidentified recording of their child's heart sounds with a digital stethoscope. Innocent murmurs were validated by a pediatric cardiologist and pathologic murmurs were validated by echocardiogram. To augment our collection of normal heart sounds, we utilized a public database of pediatric heart sound recordings (Oliveira, 2022). We propose two novel approaches for this audio classification task. We train a vision transformer on either Markov transition field or Gramian angular field image representations of the frequency spectrum. We benchmark our results against a ResNet-50 CNN trained on spectrogram images. RESULTS: Our final dataset consisted of 366 normal heart sounds, 175 innocent murmurs, and 216 pathologic murmurs. Innocent murmurs collected include Still's murmur, venous hum, and flow murmurs. Pathologic murmurs included ventricular septal defect, tetralogy of Fallot, aortic regurgitation, aortic stenosis, pulmonary stenosis, mitral regurgitation and stenosis, and tricuspid regurgitation. We find that the Vision Transformer consistently outperforms the ResNet-50 on all three image representations, and that the Gramian angular field is the superior image representation for pediatric heart sounds. We calculated a one-vs-rest multi-class ROC curve for each of the three classes. Our best model achieves an area under the curve (AUC) value of 0.92 ± 0.05, 0.83 ± 0.04, and 0.88 ± 0.04 for identifying normal heart sounds, innocent murmurs, and pathologic murmurs, respectively. CONCLUSION: We present two novel methods for pediatric heart sound classification, which outperforms the current standard of using a convolutional neural network trained on spectrogram images. To our knowledge, we are the first to demonstrate multi-class classification of pediatric murmurs. Multiclass output affords a more explainable and interpretable model, which can facilitate further model improvement in the downstream model development cycle and enhance clinician trust and therefore adoption.

Improved recovery of cardiac auscultation sounds using modified cosine transform and LSTM-based masking.

Obtaining accurate cardiac auscultation signals, including basic heart sounds (S1 and S2) and subtle signs of disease, is crucial for improving cardiac diagnoses and making the most of telehealth. This research paper introduces an innovative approach that utilizes a modified cosine transform (MCT) and a masking strategy based on long short-term memory (LSTM) to effectively distinguish heart sounds and murmurs from background noise and interfering sounds. The MCT is used to capture the repeated pattern of the heart sounds, while the LSTMs are trained to construct masking based on the repeated MCT spectrum. The proposed strategy's performance in maintaining the clinical relevance of heart sounds continues to demonstrate effectiveness, even in environments marked by increased noise and complex disruptions. The present work highlights the clinical significance and reliability of the suggested methodology through in-depth signal visualization and rigorous statistical performance evaluations. In comparative assessments, the proposed approach has demonstrated superior performance compared to recent algorithms, such as LU-Net and PC-DAE. Furthermore, the system's adaptability to various datasets enhances its reliability and practicality. The suggested method is a potential way to improve the accuracy of cardiovascular diagnostics in an era of rapid advancement in medical signal processing. The proposed approach showed an enhancement in the average signal-to-noise ratio (SNR) by 9.6 dB at an input SNR of - 6 dB and by 3.3 dB at an input SNR of 10 dB. The average signal distortion ratio (SDR) achieved across a variety of input SNR values was 8.56 dB.

Improved cardiac auscultation competency interweaving visual, auditory, and tactile stimuli: a preliminary study.

Methods:   A pilot randomized controlled trial was conducted at our institution's simulation center with 32 first year medical students from a single medical institution. Participants were randomly divided into two equal groups and completed an educational module the identification and pathophysiology of five common cardiac sounds. The control group utilized traditional education methods, while the interventional group incorporated multisensory stimuli. Afterwards, participants listened to randomly selected cardiac sounds and competency data was collected through a multiple-choice post-assessment in both groups. Mann-Whitney U test was used to analyze the data. Results: Data were analyzed using the Mann-Whitney U test. Diagnostic accuracy was significantly higher in the multisensory group (Mdn=100%) compared to the control group (Mdn=60%) on the post-assessment (U=73.5, p<0.042). Likewise, knowledge acquisition was substantially better in the multisensory group (Mdn=80%) than in the control group (Mdn=50%) (U= 49, p<0.031). Conclusions: These findings suggest the incorporation of multisensory stimuli significantly improves cardiac auscultation competency. Given its cost-effectiveness and simplicity, this approach offers a viable alternative to more expensive simulation technologies like the Harvey simulator, particularly in settings with limited resources. Consequently, this teaching modality holds promise for global applicability, addressing the worldwide deterioration in cardiac auscultation skills and potentially leading to better patient outcomes. Future studies should broaden the sample size, span multiple institutions, and investigate long-term retention rates.

Accurate Localization of First and Second Heart Sounds via Template Matching in Forcecardiography Signals.

Cardiac auscultation is an essential part of physical examination and plays a key role in the early diagnosis of many cardiovascular diseases. The analysis of phonocardiography (PCG) recordings is generally based on the recognition of the main heart sounds, i.e., S1 and S2, which is not a trivial task. This study proposes a method for an accurate recognition and localization of heart sounds in Forcecardiography (FCG) recordings. FCG is a novel technique able to measure subsonic vibrations and sounds via small force sensors placed onto a subject's thorax, allowing continuous cardio-respiratory monitoring. In this study, a template-matching technique based on normalized cross-correlation was used to automatically recognize heart sounds in FCG signals recorded from six healthy subjects at rest. Distinct templates were manually selected from each FCG recording and used to separately localize S1 and S2 sounds, as well as S1-S2 pairs. A simultaneously recorded electrocardiography (ECG) trace was used for performance evaluation. The results show that the template matching approach proved capable of separately classifying S1 and S2 sounds in more than 96% of all heartbeats. Linear regression, correlation, and Bland-Altman analyses showed that inter-beat intervals were estimated with high accuracy. Indeed, the estimation error was confined within 10 ms, with negligible impact on heart rate estimation. Heart rate variability (HRV) indices were also computed and turned out to be almost comparable with those obtained from ECG. The preliminary yet encouraging results of this study suggest that the template matching approach based on normalized cross-correlation allows very accurate heart sounds localization and inter-beat intervals estimation.

Murmur identification and outcome prediction in phonocardiograms using deep features based on Stockwell transform.

Traditionally, heart murmurs are diagnosed through cardiac auscultation, which requires specialized training and experience. The purpose of this study is to predict patients' clinical outcomes (normal or abnormal) and identify the presence or absence of heart murmurs using phonocardiograms (PCGs) obtained at different auscultation points. A semi-supervised model tailored to PCG classification is introduced in this study, with the goal of improving performance using time-frequency deep features. The study begins by investigating the behavior of PCGs in the time-frequency domain, utilizing the Stockwell transform to convert the PCG signal into two-dimensional time-frequency maps (TFMs). A deep network named AlexNet is then used to derive deep feature sets from these TFMs. In feature reduction, redundancy is eliminated and the number of deep features is reduced to streamline the feature set. The effectiveness of the extracted features is evaluated using three different classifiers using the CinC/Physionet challenge 2022 dataset. For Task I, which focuses on heart murmur detection, the proposed approach achieved an average accuracy of 93%, sensitivity of 91%, and F1-score of 91%. According to Task II of the CinC/Physionet challenge 2022, the approach showed a clinical outcome cost of 5290, exceeding the benchmark set by leading methods in the challenge.

Fetal Heart Rate Auscultation, 4th Edition.

Intermittent auscultation (IA) is an evidence-based method of fetal surveillance during labor for birthing people with low-risk pregnancies. It is a central component of efforts to reduce the primary cesarean rate and promote vaginal birth (American College of Obstetricians and Gynecologists, 2019; Association of Women's Health, Obstetric and Neonatal Nurses, 2022a). The use of intermittent IA decreased with the introduction of electronic fetal monitoring, while the increased use of electronic fetal monitoring has been associated with an increase of cesarean births. This practice monograph includes information on IA techniques; interpretation and documentation; clinical decision-making and interventions; communication; education, staffing, legal issues; and strategies to implement IA.

Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms.

One in every four newborns suffers from congenital heart disease (CHD) that causes defects in the heart structure. The current gold-standard assessment technique, echocardiography, causes delays in the diagnosis owing to the need for experts who vary markedly in their ability to detect and interpret pathological patterns. Moreover, echo is still causing cost difficulties for low- and middle-income countries. Here, we developed a deep learning-based attention transformer model to automate the detection of heart murmurs caused by CHD at an early stage of life using cost-effective and widely available phonocardiography (PCG). PCG recordings were obtained from 942 young patients at four major auscultation locations, including the aortic valve (AV), mitral valve (MV), pulmonary valve (PV), and tricuspid valve (TV), and they were annotated by experts as absent, present, or unknown murmurs. A transformation to wavelet features was performed to reduce the dimensionality before the deep learning stage for inferring the medical condition. The performance was validated through 10-fold cross-validation and yielded an average accuracy and sensitivity of 90.23 % and 72.41 %, respectively. The accuracy of discriminating between murmurs' absence and presence reached 76.10 % when evaluated on unseen data. The model had accuracies of 70 %, 88 %, and 86 % in predicting murmur presence in infants, children, and adolescents, respectively. The interpretation of the model revealed proper discrimination between the learned attributes, and AV channel was found important (score 0.75) for the murmur absence predictions while MV and TV were more important for murmur presence predictions. The findings potentiate deep learning as a powerful front-line tool for inferring CHD status in PCG recordings leveraging early detection of heart anomalies in young people. It is suggested as a tool that can be used independently from high-cost machinery or expert assessment.

Insuficiencia cardíaca secundaria a cardiopatías congénitas y adquiridas en edades pediátricas / Heart Failure Secondary to Congenital and Acquired Heart Disease in the Pediatric Age Group

Introducción: Las cardiopatías congénitas son causa frecuente de insuficiencia cardíaca mientras las cardiopatías adquiridas resultan menos frecuentes. La expresión clínica difiere en gran manera de la población adulta y representa la emergencia cardiovascular más frecuente en pediatría. El diagnóstico es completamente clínico, y el tratamiento está encaminado a corregir la causa que la origina. Objetivo: Actualizar conceptos, fisiopatología, manifestaciones clínicas, y tratamiento de la insuficiencia cardíaca en pediatría. Métodos: Se revisaron las bases de datos Medline, PubMed, SciELO y plataforma Springerlink, disponibles desde Infomed; desde el año 2000 hasta 2020, en idioma español e inglés. Análisis y síntesis de la información: La insuficiencia cardíaca es un síndrome clínico resultado de disfunción ventricular, sobrecarga de presión o volumen, independiente o en combinación, que conlleva a signos y síntomas característicos. La identificación de su causa, el diagnóstico precoz y el tratamiento oportuno mejoraran el pronóstico de los pacientes aquejados. Conclusiones: La insuficiencia cardíaca en edad pediátrica representa una compleja afección de causas multifactoriales. El diagnóstico puede hacerse con el método clínico, complementándose con los diferentes exámenes. El tratamiento médico farmacológico o no, se encamina a tratar la causa, además de nuevas terapias en desarrollo prometedoras en el futuro(AU)

Introduction: Congenital heart disease is a frequent cause of heart failure while acquired heart disease is less frequent. The clinical expression differs greatly from the adult population and represents the most frequent cardiovascular emergency in pediatrics. Diagnosis is completely clinical and treatment is aimed at correcting the cause. Objective: To update concepts, pathophysiology, clinical manifestations and treatment of heart failure in pediatrics. Methods: The databases Medline, PubMed, SciELO and Springerlink platform, available from Infomed, were reviewed from 2000 to 2020, in Spanish and English. Analysis and synthesis of the information: Heart failure is a clinical syndrome resulting from ventricular dysfunction, pressure or volume overload, independently or in combination, leading to characteristic signs and symptoms. Identification of its cause, early diagnosis and timely treatment improve the prognosis of afflicted patients. Conclusions: Heart failure in pediatric age represented a complex condition with multifactorial causes. The diagnosis can be made with the clinical method, complemented with different examinations. Pharmacological or non-pharmacological medical treatment is aimed at treating the cause, in addition to promising new therapies under development in the future(AU)

Scimitar syndrome: is the adult always asymptomatic?

INTRODUCTION: Scimitar syndrome (CS) is a rare congenital cardiac malformation that occurs in 2/100,000 live births with a 2:1 predominance in females, it belongs to the group of partial anomalous pulmonary venous connections, which has numerous described variations, being a subtype that constitutes only 3-5% of congenital cardiac anomalies. It is classified as a heart disease with increased pulmonary and cyanogenic flow, its diagnosis is usually early, but we will highlight the importance of attention to this pathology in adult patients without a previous diagnosis. CASE REPORT: Female patient, 39 years old, with dyspnea for 3 years, with progressive worsening of functional class. On physical examination, pulmonary auscultation was normal with 98% saturation. On cardiac auscultation, regular rhythm, with fixed split S2 and ejective systolic murmur 2+/4+ in the middle right sternal border. A chest X-ray was performed during the investigation, which showed a slightly arched tubular structure towards the right atrium with dextrocardia. In transthoracic echocardiogram evidenced anomalous pulmonary venous connections: the right pulmonary veins drain into the right atrium at the mouth of the inferior vena cava, with free flow, and the left into the left atrium. . Ostium secundum interatrial communication of 13.5 mm with bidirectional flow, significant dilation of the right cavities, with right ventricular myocardium with mild hypertrophy, with preserved function. PSVD 51mmHg and hypoplastic right pulmonary artery. DISCUSSION SC is a rare disease characterized by anomalous venous drainage from the lung directly into the inferior vena cava. The disease may be associated with right pulmonary hypoplasia, dextrocardia, cardiac abnormalities, and systemic pulmonary collaterals. The present case report draws attention to the late discovery of a congenital heart disease, with the patient already symptomatic and with possible important hemodynamic repercussions, highlighting the importance of always evaluating the clinical picture of dyspnea and heart failure in adults during the routine investigation. the presence of a congenital heart disease.

René Théophile Hyacinthe Laënnec (1781-1826). Doscientos años del uso del estetoscopio. Una breve reseña / René Théophile Hyacinthe Laënnec (1781-1826). Two hundred years of the stethoscope. A brief overview

Se han cumplido doscientos años desde la publicación en la que se dio a conocer la aplicación clínica del estetoscopio. Esta fue realizada en 1819 por René Théophile Hyacinthe Laënnec. El Dr. Laënnec vivió su infancia en la efervescencia social de la Revolución francesa y estudió Medicina en París, donde se graduó en 1804. Su experiencia clínica en el Hospital Necker culminó con la invención del estetoscopio en 1816. Tres años después, la publicación de su obra maestra De l'auscultation médiate enfatizó un enfoque clínico-patológico más racional, en especial, para el entendimiento de las enfermedades cardiorrespiratorias. Sin duda, el Dr. Laënnec revolucionó la medicina al perfeccionar el arte de la semiología torácica, que permitió al médico transformar los sonidos que escuchaba en una imagen, la cual podía visualizar.Con ocasión del bicentenario de este trascendental hito de la medicina moderna, se recuerda su historia

Two hundred years have passed since the publication that revealed the clinical use of the stethoscope. René Théophile Hyacinthe Laënnec published it in 1819. Laënnec spent his childhood in the social effervescence of the French Revolution and studied medicine in Paris, where he graduated in 1804. His clinical experience at Necker Hospital peaked with the invention of the stethoscope in 1816. Three years later, he published his masterpiece De L'Auscultation Médiate, which underlined a more rational clinical-pathological approach, especially in the understanding of cardiopulmonary diseases. Undoubtedly, Laënnec revolutionized medicine by perfecting the art of thoracic semiology, which allowed him to translate the sounds he heard into an image that could be visualized.In the bicentennial of the invention of such fundamental milestone in modern medicine, the purpose of this article is to go over its history

Semiologia Cardiovascular: As Personalidades por Detrás dos Epônimos / Cardiovascular Semiotics: The Personalities Behind the Eponyms

Desde seus primórdios, a medicina sempre se baseou na observação de sinais e achados específicos de pacientes doentes. A semiologia é, portanto, um estudo milenar. A semiologia cardíaca, apesar de mais recente, é mais complexa no seu aprendizado devido à dificuldade na interpretação dos achados auscultatórios. Austin Flint, Rivero Carvallo, Antonio Valsalva e Adolf Kussmaul foram alguns dos diversos médicos que se dedicaram ao estudo acadêmico da semiologia cardíaca e se eternizaram na área médica através de epônimos na cardiologia. Uma seleção dos principais e mais icônicos epônimos em cardiologia se faz necessária para complementar e destacar a importância do conhecimento do exame físico cardiovascular à beira do leito e a interpretação de seus possíveis achados, principalmente em uma era da medicina envolvida com tantas inovações tecnológicas na área de imagem. O objetivo deste artigo de revisão é abordar aspectos históricos de epônimos cardiológicos selecionados e a importância desses epônimos na prática médica atual, especialmente para aqueles em treinamento que desejam se aprofundar no estudo da semiotécnica cardiovascular

Avaliação do desempenho de dois aparelhos automáticos de medida da pressão arterial com ou sem alteração do ritmo cardíaco / Evaluation of the performance of two automatic devices for measurement of blood pressure with or without alteration of heart rhythm

A mortalidade cardiovascular aumenta com a elevação da pressão arterial; sua aferição deve ser precisa e pode ser feita com aparelhos manuais ou automáticos. Estes equipamentos têm seu uso difundido por serem de fácil manuseio e custo acessível. Em decorrência da tecnologia da oscilometria, conceitos devem ser compreendidos e divulgados, entre eles a validação, realizada por meio de protocolos. Diretrizes americanas, brasileiras e outros autores apontam limitações na utilização do método oscilométrico, devido a alterações nos valores pressóricos que podem ser influenciados por rigidez arterial e arritmia cardíaca. Objetivos: Comparar valores de pressão arterial obtidos por dois aparelhos oscilométricos (um detecta arritmia cardíaca, outro não) àqueles obtidos com esfigmomanômetro de mercúrio; descrever o desempenho destes aparelhos. Método: A amostra por conveniência foi composta por 101 voluntários (51 homens e 50 mulheres; 52 com fibrilação atrial e 49 com ritmo cardíaco sinusal) e cada um foi submetido a oito aferições da pressão arterial em ambos os braços. Foram realizadas 808 aferições da pressão arterial, 404 utilizando o método auscultatório concomitantemente por dois observadores, com manômetro de mercúrio, e mais 404 utilizando o método oscilométrico por outro observador. Para medida oscilométrica utilizou-se dois esfigmomanômetros automáticos e para auscultatório um manômetro de mercúrio. Os dados foram coletados por uma equipe de quatro profissionais de saúde devidamente capacitados. Resultados: A coleta de dados ocorreu entre novembro de 2014 e agosto de 2015. Dos 101 participantes, 52 apresentavam fibrilação atrial e 49 ritmo cardíaco sinusal. A média de idade foi 69,57 anos. A circunferência de braço variou entre 21,50 e 41,00 cm. O esfigmomanômetro com recurso de detecção de arritmia cardíaca não exibiu esse sinal em 46,2% das medidas, no entanto houve associação significante entre a aparição deste sinal e o pulso apical irregular, auscultado no início do procedimento. Houve 26 ocorrências de duas tentativas de insuflação, sendo 18 pelo aparelho que detecta arritmia cardíaca e oito com o que não detecta. A concordância entre observadores atingiu um nível adequado. Conclusão: Ambos aparelhos automáticos apresentaram, de modo global, bom desempenho na amostra estudada, o que não diminui a necessidade de submetê-los a estudo de validação em indivíduos com ritmo cardíaco irregular.(AU)

Cardiovascular mortality increases due to high blood pressure; its measurement must be accurate and manual or automatic devices can be used. Such devices have widespread use because they are easy to handle and affordable. Due to the oscillometric technology, concepts must be understood and disclosed, including validation performed by means of protocols. American and Brazilian guidelines, and other authors point out limitations in the use of the oscillometric method, due to changes in blood pressure values which may be influenced by arterial stiffness and cardiac arrhythmia. Objectives: To compare blood pressure values obtained by two oscillometric devices (one detects cardiac arrhythmia, the other does not) to those obtained with mercury sphygmomanometer; to describe the performance of these devices. Methods: This convenience sample consisted of 101 volunteers (51 men and 50 women, 52 with atrial fibrillation and 49 with sinus rhythm) each one was subjected to eight measurements of blood pressure in both arms. It were performed 808 blood pressure measurements, 404 using auscultation with mercury manometer by two observers simultaneously, and 404 using the oscillometric method by another observer. Two automatic sphygmomanometers were used for oscillometric measurement, a mercury manometer for the auscultation. Data were collected by a team of four properly trained health professionals. Results: Data collection took place from November 2014 to August 2015. There were 101 participants, 52 had atrial fibrillation and 49 had sinus rhythm. The average age was 69.57 years. The arm circumference ranged from 21.50 to 41.00 cm. The sphygmomanometer cardiac arrhythmia detector did not show that sign in 46.2% of measures, however there was a significant association between the appearance of this signal and the irregular apical pulse, auscultation at the beginning of the procedure. There were 26 times of two attempts to inflation, 18 by the device that detected cardiac arrhythmia and eight which did not. The agreement among observers reached an appropriate level. Conclusion: Both automatic devices showed, at large, good performance in the sample studied which does not diminish the need to subject them to validation study in patients with irregular heart rhythm.(AU)