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Current Problems in Cardiology Feb 2023A heart murmur in adults is a common reason for referral for echocardiography at most general cardiology clinics in Europe. A murmur may indicate either a mild... (Review)
Review
A heart murmur in adults is a common reason for referral for echocardiography at most general cardiology clinics in Europe. A murmur may indicate either a mild age-related valvular calcification or regurgitation, or represent a significant heart valve disease requiring valvular intervention. Generally, the correlation between murmurs by auscultation and severity of heart valve disease by echocardiography is poor. Particularly, the severity and characterization of diastolic murmurs by auscultation may poorly correlate with echocardiographic findings. This narrative review aims to summarize the differential diagnoses of physiological and pathological murmurs, describes the current referral practice of murmur patients for echocardiography, and presents a single-center experience on the correlation of auscultation and echocardiographic findings with a particular focus on aortic and mitral valve diseases. A careful auscultation of the heart prior to the echocardiogram is mandatory and may help to predict the echocardiographic findings and their interpretation in view of the clinical information. The correlation between clinical examination, point of care ultrasound and standard echocardiography is a matter of continued exploration.
Topics: Adult; Humans; Heart Auscultation; Cardiologists; Heart Murmurs; Echocardiography; Heart Valve Diseases
PubMed: 36336114
DOI: 10.1016/j.cpcardiol.2022.101479 -
Sensors (Basel, Switzerland) Jun 2023(1) Background: Mastery of auscultation can be challenging for many healthcare providers. Artificial intelligence (AI)-powered digital support is emerging as an aid to...
(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.
Topics: Humans; Child; Artificial Intelligence; Auscultation; Stethoscopes; Heart Murmurs; Algorithms; Respiratory Sounds
PubMed: 37420914
DOI: 10.3390/s23125750 -
Revista Espanola de Cardiologia... Jul 2019
Topics: Aged; Arteriovenous Fistula; Computed Tomography Angiography; Diagnosis, Differential; Heart Auscultation; Heart Murmurs; Humans; Iliac Artery; Iliac Vein; Male
PubMed: 30037540
DOI: 10.1016/j.rec.2018.06.021 -
Pediatrics International : Official... Jan 2022Auscultation is an easy way to evaluate and diagnose patients with lung conditions but has the shortcoming of being subjective. Using the spectrogram, it is possible to...
BACKGROUND
Auscultation is an easy way to evaluate and diagnose patients with lung conditions but has the shortcoming of being subjective. Using the spectrogram, it is possible to visualize wheezing. We therefore conducted a study to compare the efficacy of diagnosing wheezing by auscultation versus diagnosing wheezing by spectrogram.
METHODS
This was an investigation of interrater reliability and agreement in which the subject population consisted of children, and the rater population consisted of pediatric pulmonologists. We recorded 55 respiratory sound files from June to November 2019. Three pediatric pulmonologists listened to the respiratory sound files and assessed whether wheezing was present. All respiratory sound files were also converted into spectrograms; the same pulmonologists viewed these and assessed whether wheezing was present. We tested for interrater reliability and agreement between the auscultation results and spectrographic results and investigated the diagnostic reliability of auscultation versus spectrogram.
RESULTS
Agreement among the three raters of our auscultation respiratory recordings was 88% and reliability was good (κ = 0.76, P < 0.001). Agreement among the three raters of our spectrograms was 83% and reliability was good (κ =0.66, P < 0.001). The level of agreement between each rater's spectrographic findings and diagnosed wheezing was 91%, 75%, and 93%, respectively. Reliability was accordingly very good, moderate, and very good (κ = 0.82, 0.49, 0.85, P < 0.001), respectively.
CONCLUSIONS
A spectrogram may be a valuable tool for evaluating wheezing in children. It may also be used to improve a young clinician's ability to accurately diagnose wheezing in the future.
Topics: Humans; Child; Respiratory Sounds; Reproducibility of Results; Auscultation
PubMed: 34582093
DOI: 10.1111/ped.15003 -
Dysphagia Feb 2023This study investigated the reliability and validity (sensitivity and specificity) of cervical auscultation (CA) using both swallow and pre-post swallow-respiratory...
This study investigated the reliability and validity (sensitivity and specificity) of cervical auscultation (CA) using both swallow and pre-post swallow-respiratory sounds, as compared with Flexible Endoscopic Evaluation of Swallowing (FEES). With 103 swallow-respiratory sequences from 23 heterogenic patients, these swallows sounds were rated by eight CA-trained Speech-Language Pathologists (SLPs) to investigate: (1) if the swallow was safe (primary outcome); (2) patient dysphagia status; (3) the influence of liquid viscosity on CA accuracy (secondary outcomes). Primary outcome data showed high CA sensitivity (85.4%), and specificity (80.3%) with all consistencies for the safe measurement, with CA predictive values of [Formula: see text] 90% to accurately detect unsafe swallows. Intra-rater reliability was good (Kappa [Formula: see text] 0.65), inter rater reliability moderate (Kappa [Formula: see text] 0.58). Secondary outcome measures showed high sensitivity (80.1%) to identify if a patient was dysphagic, low specificity (22.9%), and moderate correlation (r [Formula: see text] 0.62) with FEES. A difference across bolus viscosities identified that CA sensitivities (90.1%) and specificities ([Formula: see text] 84.7%) for thin liquids were greater than for thick liquids (71.0-77.4% sensitivities, 74.0-81.3% specificities). Results demonstrate high validity and moderate-good reliability of CA-trained SLPs to determine swallow safety when compared with FEES. Data support the use of CA as an adjunct to the clinical swallow examination. CA should include pre-post respiratory sounds and requires specific training. Clinical implications: The authors advocate for holistic dysphagia management including instrumental assessment and ongoing CSE/review [Formula: see text] CA. Adding CA to the CSE/review does not replace instrumental assessment, nor should CA be used as a stand-alone tool.
Topics: Humans; Deglutition Disorders; Deglutition; Reproducibility of Results; Respiratory Sounds; Auscultation
PubMed: 35838785
DOI: 10.1007/s00455-022-10468-8 -
Scandinavian Journal of Primary Health... Dec 2022To investigate interrater and intrarater agreement between physicians and medical students on heart sound classification from audio recordings, and factors predicting...
OBJECTIVE
To investigate interrater and intrarater agreement between physicians and medical students on heart sound classification from audio recordings, and factors predicting agreement with a reference classification.
DESIGN
Intra- and interrater agreement study.
SUBJECTS
Seventeen GPs and eight cardiologists from Norway and the Netherlands, eight medical students from Norway.
MAIN OUTCOME MEASURES
Proportion of agreement and kappa coefficients for intrarater agreement and agreement with a reference classification.
RESULTS
The proportion of intrarater agreement on the presence of any murmur was 83% on average, with a median kappa of 0.64 (range = 0.09-0.86) for all raters, and 0.65, 0.69, and 0.61 for GPs, cardiologist, and medical students, respectively.The proportion of agreement with the reference on any murmur was 81% on average, with a median kappa of 0.67 (range 0.29-0.90) for all raters, and 0.65, 0.69, and 0.51 for GPs, cardiologists, and medical students, respectively.Distinct murmur, more than five years of clinical practice, and cardiology specialty were most strongly associated with the agreement, with ORs of 2.41 (95% CI 1.63-3.58), 2.19 (1.58-3.04), and 2.53 (1.46-4.41), respectively.
CONCLUSION
We observed fair but variable agreement with a reference on heart murmurs, and physician experience and specialty, as well as murmur intensity, were the factors most strongly associated with agreement.Key points:Heart auscultation is the main physical examination of the heart, but we lack knowledge of inter- and intrarater agreement on heart sounds.• Physicians identified heart murmurs from heart sound recordings fairly reliably compared with a reference classification, and with fair intrarater agreement.• Both intrarater agreement and agreement with the reference showed considerable variation between doctors• Murmur intensity, more than five years in clinical practice, and cardiology specialty were most strongly linked to agreement with the reference.
Topics: Humans; Heart Murmurs; Heart Auscultation; Heart Sounds; Students, Medical; Cardiology; Reproducibility of Results
PubMed: 36598178
DOI: 10.1080/02813432.2022.2159204 -
Nursing For Women's Health Apr 2024Intermittent 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...
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.
Topics: Pregnancy; Infant, Newborn; Female; Humans; Fetal Monitoring; Heart Rate, Fetal; Labor, Obstetric; Auscultation; Cardiotocography
PubMed: 38363259
DOI: 10.1016/j.nwh.2023.11.001 -
Biomedical Signal Processing and Control Aug 2023Stethoscopes are used ubiquitously in clinical settings to 'listen' to lung sounds. The use of these systems in a variety of healthcare environments (hospitals, urgent...
Stethoscopes are used ubiquitously in clinical settings to 'listen' to lung sounds. The use of these systems in a variety of healthcare environments (hospitals, urgent care rooms, private offices, community sites, mobile clinics, etc.) presents a range of challenges in terms of ambient noise and distortions that mask lung signals from being heard clearly or processed accurately using auscultation devices. With advances in technology, computerized techniques have been developed to automate analysis or access a digital rendering of lung sounds. However, most approaches are developed and tested in controlled environments and do not reflect real-world conditions where auscultation signals are typically acquired. Without a priori access to a recording of the ambient noise (for signal-to-noise estimation) or a reference signal that reflects the true undistorted lung sound, it is difficult to evaluate the quality of the lung signal and its potential clinical interpretability. The current study proposes an objective reference-free Auscultation Quality Metric (AQM) which incorporates low-level signal attributes with high-level representational embeddings mapped to a nonlinear quality space to provide an independent evaluation of the auscultation quality. This metric is carefully designed to solely judge the signal based on its integrity relative to external distortions and masking effects and not confuse an adventitious breathing pattern as low-quality auscultation. The current study explores the robustness of the proposed AQM method across multiple clinical categorizations and different distortion types. It also evaluates the temporal sensitivity of this approach and its translational impact for deployment in digital auscultation devices.
PubMed: 38274002
DOI: 10.1016/j.bspc.2023.104852 -
Annual International Conference of the... Nov 2021Cardiovascular (CV) diseases are the leading cause of death in the world, and auscultation is typically an essential part of a cardiovascular examination. The ability to...
Cardiovascular (CV) diseases are the leading cause of death in the world, and auscultation is typically an essential part of a cardiovascular examination. The ability to diagnose a patient based on their heart sounds is a rather difficult skill to master. Thus, many approaches for automated heart auscultation have been explored. However, most of the previously proposed methods involve a segmentation step, the performance of which drops significantly for high pulse rates or noisy signals. In this work, we propose a novel segmentation-free heart sound classification method. Specifically, we apply discrete wavelet transform to denoise the signal, followed by feature extraction and feature reduction. Then, Support Vector Machines and Deep Neural Networks are utilised for classification. On the PASCAL heart sound dataset our approach showed superior performance compared to others, achieving 81% and 96% precision on normal and murmur classes, respectively. In addition, for the first time, the data were further explored under a user-independent setting, where the proposed method achieved 92% and 86% precision on normal and murmur, demonstrating the potential of enabling automatic murmur detection for practical use.
Topics: Deep Learning; Heart Auscultation; Heart Sounds; Humans; Neural Networks, Computer; Wavelet Analysis
PubMed: 34891381
DOI: 10.1109/EMBC46164.2021.9630203 -
Internal Medicine (Tokyo, Japan) Sep 2019A 79-year-old man with dilated cardiomyopathy and severe functional mitral regurgitation presented with general fatigue and dyspnea. Auscultation revealed a systolic...
A 79-year-old man with dilated cardiomyopathy and severe functional mitral regurgitation presented with general fatigue and dyspnea. Auscultation revealed a systolic regurgitant murmur with a minimized second heart sound due to a low output. On the other hand, the third heart sound was ultimately enhanced, being visible and palpable as a pulsatile knock of the precordium. Phonocardiography and echocardiography successfully confirmed early-diastolic rapid distension of the left ventricle along with rapid ventricular filling and abrupt deceleration of the atrioventricular blood flow to be the precise etiology of the ultimate third heart sound, indicating critically deteriorated hemodynamics due to massive mitral regurgitation combined with a low output.
Topics: Aged; Cardiac Output, Low; Cardiomyopathy, Dilated; Dyspnea; Echocardiography; Fatigue; Heart Auscultation; Heart Sounds; Hemodynamics; Humans; Male; Mitral Valve Insufficiency; Phonocardiography; Ventricular Dysfunction, Left
PubMed: 31118397
DOI: 10.2169/internalmedicine.2731-19