Evaluation of children with heart murmurs

Recognizing cardiac murmurs in childhood: a survey of physicians' approaches and knowledge levels

OBJECTIVE

This study aimed to assess physicians' approach to cardiac murmurs and their level of knowledge about this sign, which is a crucial finding in childhood cardiac anomalies.

METHODS

The study intended to include all family physicians in the Adıyaman province of Turkey, but ultimately 150 out of 210 physicians participated and was completed with a percentage response rate of 71%. Participants were asked about their approach to cardiac murmurs, answered knowledge questions, and completed a questionnaire on demographic characteristics. Subsequently, eight heart sounds were played, and participants were asked to identify the nature of each sound.

RESULTS

Family medicine specialists (all scores were p < 0.001) and physicians who completed a pediatric internship lasting over a month (knowledge score p = 0.012, behavioral score p = 0.021, recording score p = 0.01) demonstrated significantly higher knowledge, approach, and recording scores. Age and years in the profession showed a negative correlation with recording scores.

CONCLUSIONS

The study highlights the significant impact of various factors such as gender, specialization, internship duration, experience, and theoretical knowledge on the ability to recognize and approach cardiac murmurs. These findings underscore the importance of incorporating these factors into medical education and development programs, especially those aimed at improving cardiac examination skills.

Major congenital heart defects are rarely diagnosed after newborns' hospital discharge with modern screening

AIM

Our aim was to assess undiagnosed congenital heart defects (CHD) after newborns' hospital discharge in patients with a murmur or CHD suspicion, to find out the signs that predict CHDs and to estimate the costs of the examinations.

METHODS

We reviewed retrospective medical records of patients (n = 490) referred for the evaluation of CHD suspicion during 2017-2018.

RESULTS

The median age of the patients was 2.5 (IQR 0.5-7.4) years. Sixty-three (13%) patients had an abnormal echocardiography. Neither ductal-dependent nor cyanotic CHDs were found. Cardiac interventions were performed for 14 out of 63 (22%) patients. Clinical signs indicating CHDs were murmur grade ≥3 (10/11 [91%] vs. 53/479 [11%], p < 0.001) and harsh murmur (15/44 [34%] vs. 48/446 [11%], p < 0.001). Abnormal electrocardiography did not indicate CHD (8/40 [20%] vs. 55/447 [12%], p = 0.165). The total cost of the examinations was 259 700€. The share of the cost of studies assessed as benign was 59%.

CONCLUSION

Only a few CHDs were found after newborn hospital discharge among patients who received foetal and newborn screening and were examined due to CHD suspicion. The high number of benign murmurs in children leads to many referrals, resulting in unnecessary healthcare costs.

Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling

Recognizing specific heart sound patterns is important for the diagnosis of structural heart diseases. However, the correct recognition of heart murmur depends largely on clinical experience. Accurately identifying abnormal heart sound patterns is challenging for young and inexperienced clinicians. This study is aimed at the development of a novel algorithm that can automatically recognize systolic murmurs in patients with ventricular septal defects (VSDs). Heart sounds from 51 subjects with VSDs and 25 subjects without a significant heart malformation were obtained in this study. Subsequently, the soundtracks were divided into different training and testing sets to establish the recognition system and evaluate the performance. The automatic murmur recognition system was based on a novel temporal attentive pooling-convolutional recurrent neural network (TAP-CRNN) model. On analyzing the performance using the test data that comprised 178 VSD heart sounds and 60 normal heart sounds, a sensitivity rate of 96.0% was obtained along with a specificity of 96.7%. When analyzing the heart sounds recorded in the second aortic and tricuspid areas, both the sensitivity and specificity were 100%. We demonstrated that the proposed TAP-CRNN system can accurately recognize the systolic murmurs of VSD patients, showing promising potential for the development of software for classifying the heart murmurs of several other structural heart diseases.

Synthesis of Normal Heart Sounds Using Generative Adversarial Networks and Empirical Wavelet Transform

Currently, there are many works in the literature focused on the analysis of heart sounds, specifically on the development of intelligent systems for the classification of normal and abnormal heart sounds. However, the available heart sound databases are not yet large enough to train generalized machine learning models. Therefore, there is interest in the development of algorithms capable of generating heart sounds that could augment current databases. In this article, we propose a model based on generative adversary networks (GANs) to generate normal synthetic heart sounds. Additionally, a denoising algorithm is implemented using the empirical wavelet transform (EWT), allowing a decrease in the number of epochs and the computational cost that the GAN model requires. A distortion metric (mel–cepstral distortion) was used to objectively assess the quality of synthetic heart sounds. The proposed method was favorably compared with a mathematical model that is based on the morphology of the phonocardiography (PCG) signal published as the state of the art. Additionally, different heart sound classification models proposed as state-of-the-art were also used to test the performance of such models when the GAN-generated synthetic signals were used as test dataset. In this experiment, good accuracy results were obtained with most of the implemented models, suggesting that the GAN-generated sounds correctly capture the characteristics of natural heart sounds.

Automatic Segmentation and Classification of Heart Sounds Using Modified Empirical Wavelet Transform and Power Features

A system for the automatic classification of cardiac sounds can be of great help for doctors in the diagnosis of cardiac diseases. Generally speaking, the main stages of such systems are (i) the pre-processing of the heart sound signal, (ii) the segmentation of the cardiac cycles, (iii) feature extraction and (iv) classification. In this paper, we propose methods for each of these stages. The modified empirical wavelet transform (EWT) and the normalized Shannon average energy are used in pre-processing and automatic segmentation to identify the systolic and diastolic intervals in a heart sound recording; then, six power characteristics are extracted (three for the systole and three for the diastole)—the motivation behind using power features is to achieve a low computational cost to facilitate eventual real-time implementations. Finally, different models of machine learning (support vector machine (SVM), k-nearest neighbor (KNN), random forest and multilayer perceptron) are used to determine the classifier with the best performance. The automatic segmentation method was tested with the heart sounds from the Pascal Challenge database. The results indicated an error (computed as the sum of the differences between manual segmentation labels from the database and the segmentation labels obtained by the proposed algorithm) of 843,440.8 for dataset A and 17,074.1 for dataset B, which are better values than those reported with the state-of-the-art methods. For automatic classification, 805 sample recordings from different databases were used. The best accuracy result was 99.26% using the KNN classifier, with a specificity of 100% and a sensitivity of 98.57%. These results compare favorably with similar works using the state-of-the-art methods.

Evaluation and diagnostic approach for heart murmurs in children

Heart murmurs are common in children. Most of them are innocent murmurs with normal heart anatomy and function, and only a few are pathologic murmurs with congenital heart anomaly or abnormal heart function. However, a heart murmur may be the sole symptom of serious heart disease. Therefore, careful evaluation of heart murmurs for distinguishing pathologic murmurs from innocent murmurs is important. Heart murmurs are described by their intensity, timing in the cardiac cycle, location, transmission, and quality. Murmurs, such as a holosystolic or diastolic murmur, of grade 3 or higher intensity, harsh quality, an abnormal S2, a systolic click, or increased intensity when the patient stands are more likely to be pathologic murmurs. Innocent murmurs are more likely to be systolic murmurs, with soft sounds, short duration, low pitch, and varying intensity with phases of respiration and posture (disappears with standing). Not only auscultation but also physical examination findings are important to evaluate heart murmurs. The gold standard test for the evaluation of any potentially pathologic murmur is echocardiography. For the appropriate use of echocardiography, close physical examination, including auscultation, is essential and requires considerable practice.

Impact of echocardiography on parental anxiety in children with innocent murmurs

AIM

Heart murmurs are not uncommon in childhood. Once noted, they may induce appreciable parental anxiety even if the likely diagnosis is that of an innocent murmur. This study aimed to clarify if a confirmatory echocardiogram may increase parental understanding and reduce their anxiety even though the murmur had been diagnosed as being innocent by an experienced paediatric cardiologist.

METHODS

Parents of children referred to a paediatric cardiologist for evaluation of a murmur were asked to complete a State Trait Anxiety Inventory after the cardiologist's clinical diagnosis of an innocent murmur. The questionnaire was repeated after cross-sectional echocardiography to assess if there was a change in the parental understanding regarding their child's murmur and to review their level of anxiety.

RESULTS

Over the time available for the study, 62 parents were recruited consecutively wherever possible. Forty-eight (77%) completed both questionnaires. There was a reduction in the state anxiety level following the echocardiogram in parents who exhibited a high (n = 23) or even a low-level trait anxiety (n = 25) (P < 0.05). Enhanced parental understanding of the diagnosis was also demonstrated.

CONCLUSIONS

Reduced parental anxiety and an increase in their understanding after echocardiography suggested that the procedure may have an important role in the management of innocent murmurs even after the initial reassurance by a paediatric cardiologist.

The quality, understandability, readability, and popularity of online educational materials for heart murmur

OBJECTIVE

Murmurs are abnormal audible heart sounds produced by turbulent blood flow. Therefore, murmurs in a child may be a source of anxiety for family members. Families often use online materials to explore possible reasons for these murmurs, given the accessibility of information on the Internet. In this study, we evaluated the quality, understandability, readability, and popularity of online materials about heart murmur.

METHODS

An Internet search was performed for "heart murmur" using the Google search engine. The global quality score (on a scale of 1 to 5, corresponding to poor to excellent quality) and Health on the Net code were used to measure the quality of information presented. The understandability of the web pages identified was measured using the Patient Education Materials Assessment Tool (score range from 0 to 100%, scores below 70% reflect poor performance). The readability of each web pages was assessed using four validated indices: the Flesch Reading Ease Score, the Flesch-Kincaid Grade Level, the Gunning Frequency of Gobbledygook, and the Simple Measure of Gobbledygook. The ALEXA traffic tool was used to reference domains' popularity and visibility.

RESULTS

We identified 230 English-language patient educational materials that discussed heart murmur. After exclusion, a total of 86 web pages were evaluated for this study. The average global quality score was 4.34 (SD = 0.71; range from 3 to 5) indicating that the quality of information of most websites was good. Only 14 (16.3%) websites had Health on the Net certification. The mean understandability score for all Internet-based patient educational materials was 74.6% (SD = 12.8%; range from 31.2 to 93.7%). A score suggesting these Internet-based patient educational materials were "easy to understand". The mean readability levels of all patient educational materials were higher than the recommended sixth-grade reading level, according to all indices applied. This means that the level of readability is difficult. The average grade level for all web pages was 10.4 ± 1.65 (range from 7.53 to 14.13). The Flesch-Kincaid Grade level was 10 ± 1.81, the Gunning Frequency of Gobbledygook level was 12.1 ± 1.85, and the Simple Measure of Gobbledygook level was 9.1 ± 1.38. The average Flesch Reading Ease Score was 55 ± 9.1 (range from 32.4 to 72.9).

CONCLUSION

We demonstrated that web pages describing heart murmurs were understandable and high quality. However, the readability level of the websites was above the recommended sixth-grade reading level. Readability of written materials from online sources need to be improved. However, care must be taken to ensure that the information of web pages is of a high quality and understandable.

Does Echocardiography Have a Role in the Cardiologist's Diagnosis of Innocent Murmurs in Childhood?

BACKGROUND

Innocent murmurs are common in childhood. Echocardiography may diagnose almost all congenital cardiac abnormalities. Earlier studies have suggested that it may be unnecessary when a clinical diagnosis of an innocent murmur is made by an experienced cardiologist. Yet, echocardiography is commonly performed despite such a diagnosis. Is that justifiable?

METHODS

Patients referred to a paediatric cardiologist for evaluation of a murmur were assessed. If an innocent murmur was clinically diagnosed, an echocardiogram and an electrocardiogram were ordered when requested. The cardiologist completed a questionnaire documenting the reasons for the investigations and his degree of confidence in the clinical diagnosis. The parents and patients were informed of the diagnosis and the results of the investigations.

RESULTS

In almost all 62 cases whose murmurs were clinically considered to be innocent, the referring doctor expected an echocardiogram to be performed. Following echocardiography, one patient was found to have a small muscular ventricular septal defect. On review, the murmur was consistent with that diagnosis. Three (3) others had abnormal echocardiograms namely congenitally corrected transposition of great arteries, partial anomalous right upper lobe pulmonary vein, and left ventricular non-compaction. All on review were still considered clinically to have innocent murmurs.

CONCLUSIONS

Despite the competency of the cardiologist, echocardiography diagnosed important but relatively uncommon cardiac abnormalities with prognostic implications that would have been missed if only the clinical examination was performed. Over and above the referring doctor's expectations for an echocardiogram to be performed is the need for the cardiologist to provide a complete and definitive diagnosis.