The vibratory innocent heart murmur in schoolchildren: difference in auscultatory findings between school medical officers and a pediatric cardiologist

Deep Learning in Heart Sound Analysis: From Techniques to Clinical Applications

Importance: Heart sound auscultation is a routinely used physical examination in clinical practice to identify potential cardiac abnormalities. However, accurate interpretation of heart sounds requires specialized training and experience, which limits its generalizability. Deep learning, a subset of machine learning, involves training artificial neural networks to learn from large datasets and perform complex tasks with intricate patterns. Over the past decade, deep learning has been successfully applied to heart sound analysis, achieving remarkable results and accumulating substantial heart sound data for model training. Although several reviews have summarized deep learning algorithms for heart sound analysis, there is a lack of comprehensive summaries regarding the available heart sound data and the clinical applications. Highlights: This review will compile the commonly used heart sound datasets, introduce the fundamentals and state-of-the-art techniques in heart sound analysis and deep learning, and summarize the current applications of deep learning for heart sound analysis, along with their limitations and areas for future improvement. Conclusions: The integration of deep learning into heart sound analysis represents a significant advancement in clinical practice. The growing availability of heart sound datasets and the continuous development of deep learning techniques contribute to the improvement and broader clinical adoption of these models. However, ongoing research is needed to address existing challenges and refine these technologies for broader clinical use.

A Noise-Robust Heart Sound Segmentation Algorithm Based on Shannon Energy

Heart sound segmentation has been shown to improve the performance of artificial intelligence (AI)-based auscultation decision support systems increasingly viewed as a solution to compensate for eroding auscultatory skills and the associated subjectivity. Various segmentation approaches with demonstrated performance can be utilized for this task, but their robustness can suffer in the presence of noise. A noise-robust heart sound segmentation algorithm was developed and its accuracy was tested using two datasets: the CirCor DigiScope Phonocardiogram dataset and an in-house dataset - a heart murmur library collected at the Children's National Hospital (CNH). On the CirCor dataset, our segmentation algorithm marked the boundaries of the primary heart sounds S1 and S2 with an accuracy of 0.28 ms and 0.29 ms, respectively, and correctly identified the actual positive segments with a sensitivity of 97.44%. The algorithm also executed four times faster than a logistic regression hidden semi-Markov model. On the CNH dataset, the algorithm succeeded in 87.4% cases, achieving a 6% increase in segmentation success rate demonstrated by our original Shannon energy-based algorithm. Accurate heart sound segmentation is critical to supporting and accelerating AI research in cardiovascular diseases. The proposed algorithm increases the robustness of heart sound segmentation to noise and viability for clinical use.

StethAid: A Digital Auscultation Platform for Pediatrics

(1) Background: Mastery of auscultation can be challenging for many healthcare providers. Artificial intelligence (AI)-powered digital support is emerging as an aid to assist with the interpretation of auscultated sounds. A few AI-augmented digital stethoscopes exist but none are dedicated to pediatrics. Our goal was to develop a digital auscultation platform for pediatric medicine. (2) Methods: We developed StethAid-a digital platform for artificial intelligence-assisted auscultation and telehealth in pediatrics-that consists of a wireless digital stethoscope, mobile applications, customized patient-provider portals, and deep learning algorithms. To validate the StethAid platform, we characterized our stethoscope and used the platform in two clinical applications: (1) Still's murmur identification and (2) wheeze detection. The platform has been deployed in four children's medical centers to build the first and largest pediatric cardiopulmonary datasets, to our knowledge. We have trained and tested deep-learning models using these datasets. (3) Results: The frequency response of the StethAid stethoscope was comparable to those of the commercially available Eko Core, Thinklabs One, and Littman 3200 stethoscopes. The labels provided by our expert physician offline were in concordance with the labels of providers at the bedside using their acoustic stethoscopes for 79.3% of lungs cases and 98.3% of heart cases. Our deep learning algorithms achieved high sensitivity and specificity for both Still's murmur identification (sensitivity of 91.9% and specificity of 92.6%) and wheeze detection (sensitivity of 83.7% and specificity of 84.4%). (4) Conclusions: Our team has created a technically and clinically validated pediatric digital AI-enabled auscultation platform. Use of our platform could improve efficacy and efficiency of clinical care for pediatric patients, reduce parental anxiety, and result in cost savings.

Automated identification of innocent Still's murmur using a convolutional neural network

Background

Still's murmur is the most prevalent innocent heart murmur of childhood. Auscultation is the primary clinical tool to identify this murmur as innocent. Whereas pediatric cardiologists routinely perform this task, primary care providers are less successful in distinguishing Still's murmur from the murmurs of true heart disease. This results in a large number of children with a Still's murmur being referred to pediatric cardiologists.

Objectives

To develop a computer algorithm that can aid primary care providers to identify the innocent Still's murmur at the point of care, to substantially decrease over-referral.

Methods

The study included Still's murmurs, pathological murmurs, other innocent murmurs, and normal (i.e., non-murmur) heart sounds of 1,473 pediatric patients recorded using a commercial electronic stethoscope. The recordings with accompanying clinical diagnoses provided by a pediatric cardiologist were used to train and test the convolutional neural network-based algorithm.

Results

A comparative analysis showed that the algorithm using only the murmur sounds recorded at the lower left sternal border achieved the highest accuracy. The developed algorithm identified Still's murmur with 90.0% sensitivity and 98.3% specificity for the default decision threshold. The area under the receiver operating characteristic curve was 0.943.

Conclusions

Still's murmur can be identified with high accuracy with the algorithm we developed. Using this approach, the algorithm could help to reduce the rate of unnecessary pediatric cardiologist referrals and use of echocardiography for a common benign finding.

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.

Detecting and recording cardiac murmurs in clinically healthy puppies in first opinion veterinary practice at the first health check

Background

The frequency that cardiac murmurs are identified and recorded in first opinion veterinary practices at the first health check in puppies is unknown. The aims of the study were to assess the agreement between first opinion veterinary practitioners, a veterinary student and a veterinary cardiology specialist on detecting murmurs, and to establish whether abnormal auscultation findings had been recorded in the health certificates of clinically healthy puppies. The study included prospective and retrospective investigations, where the prospectively collected auscultation findings from a veterinary cardiology specialist and a trained veterinary student were compared to auscultation findings recorded by first opinion veterinary practitioners.

Results

Cardiac auscultation was performed on 331 client-owned, clinically healthy dogs at two time points: at age 34–69 days by a first opinion veterinary practitioner and at age 45–76 days, on average 9 days later, by a veterinary cardiology specialist and a trained veterinary student. Agreement among the three was compared for the presence of a murmur. The degree of inter-observer agreement was evaluated using Cohen’s kappa. Auscultation findings, as noted in the pets’ passports, from 331 puppies and 43 different first opinion veterinary practices, were retrospectively reviewed and prospectively compared with auscultation findings from a veterinary cardiology specialist. Agreement between the veterinary cardiology specialist and the first opinion veterinary practitioners was poor (ϰ = 0.01) and significantly different (P < 0.001). First opinion veterinary practitioners had recorded a cardiac murmur in only 1 of the 97 puppies in which the veterinary cardiology specialist detected a murmur. Two-hundred-and-fifty-two puppies were auscultated by both the veterinary cardiology specialist and the student. Their agreement was fair (ϰ = 0.40) and significantly different (P = 0.024). The agreement between the student and a first opinion veterinary practitioner on these 252 puppies was poor (ϰ = 0.03) and significantly different (P < 0.001).

Conclusions

This study shows that soft cardiac murmurs are rarely documented during the first veterinary health check in puppies by first opinion veterinary practitioners. Although soft murmurs may not be clinically relevant, finding and recording them is evidence of a carefully performed auscultation. Missing a non-pathological murmur is not of clinical importance; however, missing a pathological murmur could prove detrimental for the individual puppy.

A study of time-frequency features for CNN-based automatic heart sound classification for pathology detection

This study concerns the task of automatic structural heart abnormality risk detection from digital phonocardiogram (PCG) signals aiming at pediatric heart disease screening applications. Recently, various systems based on convolutional neural networks trained on time-frequency representations of segmental PCG frames have been presented that outperform systems using hand-crafted features. This study focuses on the segmentation and time-frequency representation components of the CNN-based designs. We consider the most commonly used features (MFCC and Mel-Spectrogram) used in state-of-the-art systems and a time-frequency representation influenced by domain-knowledge, namely sub-band envelopes as an alternative feature. Via tests carried on two high quality databases with a large set of possible settings, we show that sub-band envelopes are preferable to the most commonly used features and period synchronous windowing is preferable over asynchronous windowing.

Accidental Heart Murmurs

INTRODUCTION

Accidental murmurs occur in anatomically and physiologically normal heart. Accidental (innocent) murmurs have their own clearly defined clinical characteristics (asymptomatic, they require minimal follow-up care).

AIM

To point out the significance of auscultation of the heart in the differentiation of heart murmurs and show clinical characteristics of accidental heart murmurs.

MATERIAL AND METHODS

Article presents review of literature which deals with the issue of accidental heart murmurs in the pediatric cardiology.

RESULTS

In the group of accidental murmurs we include classic vibratory parasternal-precordial Stills murmur, pulmonary ejection murmur, the systolic murmur of pulmonary flow in neonates, venous hum, carotid bruit, Potaine murmur, benign cephalic murmur and mammary souffle.

CONCLUSION

Accidental heart murmurs are revealed by auscultation in over 50% of children and youth, with a peak occurrence between 3-6 years or 8-12 years of life. Reducing the frequency of murmurs in the later period can be related to poor conduction of the murmur, although the disappearance of murmur in principle is not expected. It is the most common reason of cardiac treatment of the child, and is a common cause of unreasonable concern of parents.

Automated Identification of Innocent Still's Murmur in Children

OBJECTIVE

Still's murmur is the most common innocent heart murmur in children. It is also the most commonly misdiagnosed murmur, resulting in a high number of unnecessary referrals to pediatric cardiologist. The purpose of this study was to develop a computer algorithm for automated identification of Still's murmur that may help reduce unnecessary referrals.

METHODS

We first developed an accurate segmentation algorithm to locate the first and the second heart sounds. Once these sounds were identified, we extracted signal features specific to Still's murmur. Subsequently, machine learning-based classifiers, artificial neural network and support vector machine, were used to identify Still's murmur.

RESULTS

We evaluated our classifiers using the jackknife method using 87 Still's murmurs and 170 non-Still's murmurs. Our algorithm identified Still's murmur accurately with 84-93% sensitivity and 91-99% specificity.

CONCLUSION

We have achieved accurate automated identification of Still's murmur while minimizing false positives. The performance of our algorithm is comparable to the rate of murmur identification by auscultation by pediatric cardiologists.

SIGNIFICANCE

To our knowledge, our solution is the first murmur classifier that focuses singularly on Still's murmur. Following further refinement and testing, the presented algorithm could reduce the number of children with Still's murmur referred unnecessarily to pediatric cardiologists.

Evaluation of Diagnostic Methods in the Differentiation of Heart Murmurs in Children

Introduction:

The most common clinical sign in pediatric cardiology is a heart murmur (organic and inorganic). Organic are sign of heart disease, while inorganic (basically divided into accidental and functional) murmurs occur on anatomically healthy heart.

Aim:

To determine the justification of the application of the methods of cardiac treatment.

Patients and methods:

Study included 116 children aged from 1 to 15 years, who were referred due to cardiac treatment to Pediatric Clinic, of Sarajevo University Clinical Center.

Results:

The first group consisted of children with innocent heart murmur, 97 (53 males). The second group consisted of patients with organic murmur, 19 (13 males). The average age of the first group was 7.69 (1.01–15.01) years old, and of the second group 3.15 (1.01- 8.06) years old, and there is a significant difference between these two groups (p <0.001). Medical history questions about potentially harmful habits of mother in pregnancy, found significant differences in the frequency of the existence of habits between the first and second groups of subjects (14.44% vs. 85.1%, p = 0.013). The values of the pulse of patients showed statistically significant difference (p = 0.012). The most common place of the murmurs’ appearance is the second left intercostal space. In the first group, the most common were vibratory (32.3%) and ejection (31.9%) and in the second the most common were holosystolic (73.7%) murmur. Analyzing the R/S ratio of V1, a significant difference among the two groups was found (mean 0.78 vs. the values for 1.45, p = 0.003). There is a significance in terms of developed hypertrophy of the heart cavities (BVH) between the two groups. The most common accidental murmur was classic vibratory Still’s murmurs (55.43%) and the most common congenital heart defects was ASD (36.8%).

Conclusions:

A heart murmur itself, should not be the purpose of auscultation. One of the tasks of pediatricians, pediatric cardiologists in particular would be to improve auscultation, as a sovereign method of heart murmurs assessment. Heart murmur assessment should be adapted to recognize whether heart murmur is innocent, or there is suspected or probable congenital heart defect.

[Diagnosis of a systolic murmur among young asymptomatic patient: An assessment of professional practices for the expertise in military medicine]

The finding of a systolic heart murmur is common in medical military practice. Albeit often benign among young healthy adults, it can reveal a valvular or a cardiac disease, which could worsen during workout or expose to risk of a sudden death. This study aims to evaluate the diagnostic efficiency of the military general practitioner when discovering a systolic murmur among young asymptomatic patients.

MATERIALS AND METHODS

During one year, this study involved all the general practitioners of the medical military centres of Brittany and the cardiologists of the military hospital in Brest. It prospectively enrolled a cohort of all military asymptomatic patients under 40, without any underlying known heart condition. Military general practitioners listed, thanks to an anonymous form, the main features of the systolic murmur and of the ECG and proposed an auscultatory diagnosis: innocent or organic murmur. Then cardiologists did the same and finally performed a transthoracic echocardiography giving the diagnosis.

RESULTS

Fifty-eight patients were referred, 5 not meeting the inclusion criteria. Of the 53 patients included, military general practitioners found 46 innocent murmurs and 7 organic ones. Cardiologists found 51 innocent murmurs and 2 organic. Transthoracic echocardiography just took on one organic murmur (linked with a bicuspid aortic valve), spotted by the specialist, though judged innocent by the general practitioner.

DISCUSSION

Most of innocent murmurs diagnosed by general practitioners (45/46) were confirmed. Regarding the seven organic murmurs, the main selected criteria (intensity over 3, orthostatic persistence, diffuse irradiation) are mostly in accordance with the literature, proving right medical instincts. Authors propose a practical management of systolic murmurs among asymptomatic young patients.

CONCLUSION

Military general practitioners seem to master symptoms of organic murmur. This assessment argues for a promotion of a holistic clinical examination, which will help not only to rationalize the use of transthoracic echocardiography in economic terms but also to value the medical expertise.

[Echographic diagnosis of systolic murmur among 280 young French militaries. Implications for the expertise in military medicine]

Clinically discovering a systolic murmur is frequent among the young military population. When this murmur does not sound benign, a transthoracic echocardiography (TTE) is made to detect any cardiopathy, which could cause sudden cardiac death. The aim of this study was to evaluate the interest of systematic TTE in the assessment of any cardiac systolic murmur (CSM) among militaries.

METHODS

We ran a retrospective monocentric study in the "Clermont-Tonnerre" military hospital in Brest. We included all patients sent for TEE, aged 15 to 30 years old, from the 1st January 2010 until the 31st July 2013.

RESULTS

Two hundred and eighty TTES assessing CSM were performed. We found 28/280 (10%) echocardiographic abnormalities: 13 were bicuspid aortic valves (4.6%), 6 were ventricular septal defects (2.15%), 3 were atrial septal defects (1.07%), 4 were mild mitral regurgitations (1.43%), one mild pulmonary stenosis (0.35%) and one aortic stenosis (0.35%). No hypertrophic cardiomyopathy was found. Concerning military expertise, 11 (3.92%) patients among these 28 with abnormal TEE were considered unfit for work or "fit for work with limitations".

CONCLUSION

Assessing a cardiac systolic murmur with TEE lead to the diagnosis of a cardiomyopathy in 10% of the case. This study enhances the importance of systematic TEE when a CSM is detected in the young military, in order to determine if those soldiers can still fulfill their military duty.

Skills of primary healthcare physicians in paediatric cardiac auscultation

AIM

To evaluate the performance of primary healthcare physicians in paediatric cardiac auscultation and the impact of a multimedia-based teaching intervention.

METHODS

A total of 106 primary healthcare physicians (77 paediatricians, 14 general practitioners and 15 medical graduates) attended four paediatric cardiac auscultation teaching courses based on virtual patients' presentation (digital phonocardiography). Their auscultatory performance was documented at the beginning of each course and at the end of two of the courses.

RESULTS

Participants initially detected 73% of abnormal murmurs and 17% of additional sounds, while 22% of innocent murmurs were interpreted as abnormal. Overall cardiac auscultation performance, assessed by a combined auscultation score, was low and independent of training level (graduates: 39.5/trainees: 42.8/board certified: 42.6, p = 0.89) or specialty (paediatricians: 42.7/general practitioners: 43.1, p = 0.89). Multimedia-based teaching was associated with a significant improvement in abnormal murmur (92.5%) and additional sound (40%) detection (p < 0.001), while 25% of innocent murmurs were still interpreted as abnormal (p = 0.127).

CONCLUSION

Clinical skills of primary healthcare physicians in paediatric cardiac auscultation, independent of training level or specialty, still leave potential for improvement. Multimedia-based teaching interventions represent an effective means of improving paediatric cardiac auscultatory skills.

Cardiac auscultatory skills of academic family physicians: strength of association with an academic pediatric cardiologist

Aim. Heart murmur is common in children, and it is one of the main reasons for referral among children in primary care. The aim of this study is to evaluate agreement and consistency of normal, innocent, and pathologic murmur decision between academic family physicians and academic pediatric cardiologist. Methods. Seven hundred fifteen primary school children were examined by family physicians and paediatric cardiologist. Auscultatory examination was performed. Intensity, frequency, duration, quality, location, and radiation of the murmur were described if present. Agreement of normal, innocent, and pathologic murmur classification decision between family physician and paediatric cardiologist was analyzed by using kappa statistic. Results. Normal, innocent and pathologic murmurs were reported for 419, 228, and 54 children in family physicians' reports, respectively. Paediatric cardiologist agreed on 383 (91.4%) children as normal, 191 (83.7%) children having innocent murmur, and 19 (35.2%) children having pathologic murmur among family physician's reports. There was good consistency between family physicians and paediatric cardiologist (κ value = 0.679, 95% CI 0.630-0.727, P < .001). They agreed on the majority of normal and innocent murmur decisions. However family physicians reported pathologic murmur more frequently. Conclusion. Cardiac auscultatory skills of academic family physicians may be concordant with paediatric cardiologist.

Utility of store-and-forward pediatric telecardiology evaluation in distinguishing normal from pathologic pediatric heart sounds

Because pediatric cardiologists can accurately diagnose innocent murmurs by physical exam alone, the authors developed a system for remote cardiac auscultation. They hypothesized that their system could accurately classify auscultatory findings as normal/innocent or pathologic. Patients undergoing evaluation underwent examination, echocardiography, and heart sound recording. Pediatric cardiologists evaluated the heart sounds and classified the case as either normal/innocent or pathologic. They reviewed103 heart sound data sets; 85% of the cases were accurately classified as either normal/innocent or pathologic, with a sensitivity of 82% and specificity of 86%. However, when accounting for clinical diagnosis, reviewer uncertainty, and ECG abnormalities, the sensitivity and specificity improved to 91% and 88% (accuracy 89%), respectively. Degree of certainty with the telecardiology diagnosis correlated with correct interpretation (P < .005). Digital heart sound recordings evaluated via telemedicine can distinguish normal/innocent murmurs from pathologic ones. Such a system could improve the use of pediatric cardiology services.

Detection of cardiac pathology: time intervals and spectral analysis

AIM

To develop an objective diagnostic method that facilitates detection of noncyanotic congenital heart diseases.

METHODS

Heart sounds and murmurs were recorded from 60 healthy children and 173 children with noncyanotic congenital heart disease. Time intervals were measured and spectrum of the systolic murmurs analyzed. Stepwise logistic regression analysis was used to distinguish physiological from pathological signals. The receiver operating characteristic (ROC) curve was plotted to show the classification performance of the model and the area under the curve (AUC) was calculated. The probability cut-off points for calculation of sensitivities and specificities were estimated.

RESULTS

The distinguishing variables were the interval from the end of the first heart sound (S(1)) and the beginning of the systolic murmur, respiratory variation of the splitting of the second heart sound, intensity of the systolic murmur, and standard deviation of the interval from the end of the S(1) to the maximum intensity of the murmur. The AUC was 0.95, indicating an excellent classification performance of the model. The sensitivity of 95% and specificity of 72% was achieved at a probability cut-off point of 0.45. Significant cardiac defects were correctly classified.

CONCLUSION

Interval measurements and spectral analysis can be used to confirm significant noncyanotic congenital heart diseases. Further development of the method is necessary to detect also insignificant heart defects.

Phono-spectrographic analysis of heart murmur in children

BACKGROUND

More than 90% of heart murmurs in children are innocent. Frequently the skills of the first examiner are not adequate to differentiate between innocent and pathological murmurs. Our goal was to evaluate the value of a simple and low-cost phonocardiographic recording and analysis system in determining the characteristic features of heart murmurs in children and in distinguishing innocent systolic murmurs from pathological.

METHODS

The system consisting of an electronic stethoscope and a multimedia laptop computer was used for the recording, monitoring and analysis of auscultation findings. The recorded sounds were examined graphically and numerically using combined phono-spectrograms. The data consisted of heart sound recordings from 807 pediatric patients, including 88 normal cases without any murmur, 447 innocent murmurs and 272 pathological murmurs. The phono-spectrographic features of heart murmurs were examined visually and numerically. From this database, 50 innocent vibratory murmurs, 25 innocent ejection murmurs and 50 easily confusable, mildly pathological systolic murmurs were selected to test whether quantitative phono-spectrographic analysis could be used as an accurate screening tool for systolic heart murmurs in children.

RESULTS

The phono-spectrograms of the most common innocent and pathological murmurs were presented as examples of the whole data set. Typically, innocent murmurs had lower frequencies (below 200 Hz) and a frequency spectrum with a more harmonic structure than pathological cases. Quantitative analysis revealed no significant differences in the duration of S1 and S2 or loudness of systolic murmurs between the pathological and physiological systolic murmurs. However, the pathological murmurs included both lower and higher frequencies than the physiological ones (p < 0.001 for both low and high frequency limits). If the systolic murmur contained intensive frequency components of over 200 Hz, or its length accounted for over 80 % of the whole systolic duration, it was considered pathological. Using these criteria, 90 % specificity and 91 % sensitivity in screening were achieved.

CONCLUSION

Phono-spectrographic analysis improves the accuracy of primary heart murmur evaluation and educates inexperienced listener. Using simple quantitative criterias a level of pediatric cardiologist is easily achieved in screening heart murmurs in children.

Comparison of two educational interventions on pediatric resident auscultation skills

OBJECTIVE

Multiple cross-sectional physician surveys have documented poor cardiac auscultation skills. We evaluated the impact of 2 different educational interventions on pediatric resident auscultation skills.

METHODS

The auscultation skills of all first-year (PGY1; n = 20) and second-year pediatric residents (PGY2; n = 20) were evaluated at the beginning and end of the academic year. Five patient recordings were presented: atrial septal defect, ventricular septal defect, pulmonary valve stenosis, bicuspid aortic valve with insufficiency, and innocent murmur. Residents were asked to classify the second heart sound, identify a systolic ejection click, describe the murmur, and provide a diagnosis. All PGY1 and most PGY2 (14 of 20) participated on the inpatient cardiology service for 1 month. PGY2 on the cardiology service also attended outpatient clinic. PGY1 did not attend outpatient clinic but were allotted 2 hours/week to use a self-directed cardiac auscultation computer teaching program.

RESULTS

Resident auscultation skills on initial evaluation were dependent on training level (PGY1: 42 +/- 15% correct; PGY2: 53 +/- 13% correct), primarily as a result of better classification of second heart sound (PGY1: 45%; PGY2: 63%) and diagnosis of an innocent murmur (PGY1: 35%; PGY2: 65%). There was no difference in the ability to identify correctly a systolic ejection click (20% vs 23%) or to arrive at the correct diagnosis (35% vs 40%). At the end of the academic year, the PGY1 scores improved by 21%, primarily as a result of improved diagnostic accuracy of the innocent murmur (35% to 65%). PGY2 scores remained unchanged (53% vs 51%), regardless of participation in a cardiology rotation (cardiology rotation: 50%; no cardiology rotation: 51%). Combined, diagnostic accuracy was best for ventricular septal defect (55%) and innocent murmur (60%) and worst for atrial septal defect (18%) and pulmonary valve stenosis (15%). However, 40% identified the innocent murmur as pathologic and 21% of pathologic murmurs were diagnosed as innocent.

CONCLUSIONS

Pediatric resident auscultation skills were poor and did not improve after an outpatient cardiology rotation. Auscultation skills did improve after the use of a self-directed cardiac auscultation teaching program. These data have relevance given the American College of Graduate Medical Education's emphasis on measuring educational outcomes and documenting clinical competencies during residency training.

Heart murmurs recorded by a sensor based electronic stethoscope and e-mailed for remote assessment

BACKGROUND

Heart murmurs are common in children, and they are often referred to a specialist for examination. A clinically innocent murmur does not need further investigation. The referral area of the University Hospital is large and sparsely populated. A new service for remote auscultation (telemedicine) of heart murmurs in children was established where heart sounds and short texts were sent as an attachment to e-mails.

AIM

To assess the clinical quality of this method.

METHODS

Heart sounds from 47 patients with no murmur (n = 7), with innocent murmurs (n = 20), or with pathological murmurs (n = 20) were recorded using a sensor based stethoscope and e-mailed to a remote computer. The sounds were repeated, giving 100 cases that were randomly distributed on a compact disc. Four cardiologists assessed and categorised the cases as having "no murmur", "innocent murmur", or "pathological murmur", recorded the assessment time per case, their degree of certainty, and whether they recommended referral.

RESULTS

On average, 2.1 minutes were spent on each case. The mean sensitivity and specificity were 89.7% and 98.2% respectively, and the inter-observer and intra-observer variabilities were low (kappa 0.81 and 0.87), respectively. A total of 93.4% of cases with a pathological murmur and 12.6% of cases with an innocent murmur were recommended for referral.

CONCLUSION

Telemedical referral of patients with heart murmurs for remote assessment by a cardiologist is safe and saves time. Skilled auscultation is adequate to detect patients with innocent murmurs.

Parental anxiety associated with referral of a child to a pediatric cardiologist for evaluation of a Still's murmur

OBJECTIVE

We assessed factors contributing to parental anxiety when children are referred to a cardiology clinic for evaluation of a Still's murmur.

METHODS

Parents of 95 children completed questionnaires designed to assess family and patient characteristics, parents' ratings of their anxiety and the reassurance they received from their pediatrician, and current (state) and general anxiety levels.

RESULTS

Parents reported anxiety about multiple issues including the need for medication (49%), sports restrictions (41%), cardiac surgery (29%), cardiac risk for siblings (20%), and premature death (13%). Of reporting mothers, 19% felt the murmur resulted from something they did wrong during pregnancy. Although 54% of parents were extremely reassured by their pediatrician, only 17% had no anxiety associated with the specialty visit. After reassurance from the cardiologist, 7% of parents had persistent anxiety. In multivariable analysis, 2 features, both related to the referring pediatrician, were significantly related to parental anxiety level. High parental anxiety was associated with lower pediatrician reassurance ratings and greater pediatrician practice years.

CONCLUSIONS

Parental anxiety is common among parents of children referred for specialty evaluation. Educational strategies to improve pediatrician communication skills with parents may improve quality of care.

Pediatric tele-echocardiography: evaluation of transmission modalities

Pediatric cardiology consultation has been effectively delivered outside the tertiary care setting through the use of tele-echocardiography. This study examined the effectiveness of several tele-echocardiography connections and the satisfaction of the referring physicians using these services. Studies were transmitted via either a shared fiber-optic (DS3) connection (two sites), a dedicated fast-copper (ISDN-PRI) link, or by courier from a nearby (25-mile) or distant (170-mile) site. Time intervals between when echocardiograms were performed locally until they were received, interpreted, and reported were prospectively recorded. Referring physician satisfaction was assessed through a survey. The critical time between when a remote echocardiogram was performed and when its result was reported to the referring physician was primarily determined by the mode of transmission. The time interval between performing an echocardiogram and receiving the study was significantly longer for echocardiograms sent from the 170-mile courier site (2474 +/- 295 min) than either the 25-mile courier site (474 +/- 151 min), DS3 (374 +/- 121 min), or ISDN-PRI (129 +/- 16 min). Regardless of the method of transmission, all referring physicians felt that the service improved their ability to manage children, and they would recommend the service to their colleagues. Those using the courier service from the 25-mile away site were more concerned about the availability of a pediatric cardiologist and image quality, presumably due to the delay in response times. The time interval data provided in this study and the assessment of physician satisfaction provide important data as echocardiography laboratories implement tele-echocardiography services.

Artificial neural network-based method of screening heart murmurs in children

BACKGROUND

Early recognition of heart disease is an important goal in pediatrics. Efforts in developing an inexpensive screening device that can assist in the differentiation between innocent and pathological heart murmurs have met with limited success. Artificial neural networks (ANNs) are valuable tools used in complex pattern recognition and classification tasks. The aim of the present study was to train an ANN to distinguish between innocent and pathological murmurs effectively.

METHODS AND RESULTS

Using an electronic stethoscope, heart sounds were recorded from 69 patients (37 pathological and 32 innocent murmurs). Sound samples were processed using digital signal analysis and fed into a custom ANN. With optimal settings, sensitivities and specificities of 100% were obtained on the data collected with the ANN classification system developed. For future unknowns, our results suggest the generalization would improve with better representation of all classes in the training data.

CONCLUSION

We demonstrated that ANNs show significant potential in their use as an accurate diagnostic tool for the classification of heart sound data into innocent and pathological classes. This technology offers great promise for the development of a device for high-volume screening of children for heart disease.

Clinical and basic laboratory assessment of children for possible congenital heart disease

Accurate and cost-effective detection of congenital heart disease is a priority for the primary care physician, but there are many diagnostic modalities and strategies available. Within the past year, investigators have reported factors that contribute to the failure to diagnose congenital heart disease before autopsy. Recent research also highlights the strengths and weaknesses of the clinical evaluation by the primary care physician. An examination by a pediatric cardiologist is a more specific discriminator between heart disease and innocent murmur and can, in many instances, eliminate the expense of relying on echocardiography for diagnosis. Current reports document substantial limitations of diagnostic utility of electrocardiography and chest roentgenography. Suspicions that echocardiography can be misleading when performed in laboratories without expertise in congenital heart disease are confirmed in recent organized comparisons of accuracy. High-quality, well-designed tele-echocardiography programs are shown to be effective solutions when maldistribution of pediatric cardiology services hampers diagnostic efficiency.

[Diagnostic value of physical examination and electrocardiogram in the initial evaluation of heart murmurs in children]

OBJECTIVE

To investigate the diagnostic value of the physical examination and electrocardiogram in the evaluation of heart murmur in new patients referred to the pediatric cardiologist.

METHOD

From 1 April to 30 September 1998, all consecutive patients referred to the pediatric cardiology clinic for evaluation of heart murmur were included. They were prospectively categorized with no heart disease, possible heart disease or definite heart disease based on history and physical examination. They then underwent electrocardiogram with which the diagnosis was reevaluated by the pediatric cardiologist. Lastly, a doppler-echocardiography was systematically performed.

RESULTS

In 120 children aged four days to 14 years (median: ten months), 72 (60%) showed abnormalities on doppler-echocardiography and 48 (40%) no heart disease. After physical examination, 52 patients were categorized with no heart disease: 45 patients had a normal doppler-echocardiography; in three of them, the diagnosis was incorrectly modified to possible heart disease on the basis of the electrocardiogram. In the other seven children, the electrocardiogram was normal and the doppler-echocardiography revealed minor (n = 5) or moderate (n = 2) heart defects. Nineteen patients were suspected of having possible heart disease, no diagnosis was modified after analysis of the electrocardiogram and six had normal doppler-echocardiography; 49 patients were correctly diagnosed as having definite heart disease. The sensibility of the physical examination was 90.3%, the specificity was 93.8%, the positive predictive value 95.6% and the negative predictive value 86.5%.

CONCLUSION

The electrocardiogram is of no help in the discrimination between heart disease and no heart disease in children referred to the pediatric cardiologist for a cardiac murmur. The physical examination is able to differentiate children with or without heart disease in most of the cases.

What makes a heart murmur innocent?

The physician determines that a murmur is innocent by evaluating it on its own merits. The information should be assessed in a logical and orderly fashion, and the possibilities are considered based on the information that is obtained. All of this information is processed through the physician's knowledge and experience base, and then a decision is made. One cannot increase one's skill as a cardiac auscultator by reading articles such as this-one can only learn what is abnormal by being completely comfortable with what is normal. There is no substitution for listening to many hearts, but the physician must listen to normal hearts thoughtfully and analytically. What makes a heart murmur innocent? The answer to this question includes the characteristics of the murmur in the context of the patient's total cardiovascular examination. How are these characteristics determined? They are determined the same way as any other technical skill is accomplished-with practice.