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Animals : An Open Access Journal From... Jun 2024Heart murmurs in puppies can be innocent or pathologic; the latter is almost always related to a congenital heart disease. Differentiating between these murmurs can be...
BACKGROUND
Heart murmurs in puppies can be innocent or pathologic; the latter is almost always related to a congenital heart disease. Differentiating between these murmurs can be challenging for practicing veterinarians, but this differentiation is essential to ensure the best prognosis for puppies having a congenital heart disease. Our study aimed to reveal how veterinarians manage puppies with a heart murmur.
METHODS
A web-based questionnaire was sent to Dutch and Belgian veterinary practices.
RESULTS
Data from 452 respondents were analyzed. Though 88% of the respondents find detecting a heart murmur easy, only 9% find differentiating innocent murmurs from pathologic murmurs in puppies easy. Of the respondents, only 80% recommend immediate additional examination when detecting a loud heart murmur during the first veterinary health check at 6 weeks of age. Most of the respondents are aware that normal growth and the absence of clinical signs do not exclude severe congenital heart disease. Of the respondents, 31% were uncertain whether early surgical intervention could lead to improved outcomes.
CONCLUSIONS
Veterinarians are aware of the importance of echocardiography for puppies with a loud heart murmur, and recognize their limitations when differentiating an innocent from a pathological heart murmur in a puppy.
PubMed: 38929440
DOI: 10.3390/ani14121821 -
Bioengineering (Basel, Switzerland) Jun 2024Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early...
Respiratory diseases are among the leading causes of death, with many individuals in a population frequently affected by various types of pulmonary disorders. Early diagnosis and patient monitoring (traditionally involving lung auscultation) are essential for the effective management of respiratory diseases. However, the interpretation of lung sounds is a subjective and labor-intensive process that demands considerable medical expertise, and there is a good chance of misclassification. To address this problem, we propose a hybrid deep learning technique that incorporates signal processing techniques. Parallel transformation is applied to adventitious respiratory sounds, transforming lung sound signals into two distinct time-frequency scalograms: the continuous wavelet transform and the mel spectrogram. Furthermore, parallel convolutional autoencoders are employed to extract features from scalograms, and the resulting latent space features are fused into a hybrid feature pool. Finally, leveraging a long short-term memory model, a feature from the latent space is used as input for classifying various types of respiratory diseases. Our work is evaluated using the ICBHI-2017 lung sound dataset. The experimental findings indicate that our proposed method achieves promising predictive performance, with average values for accuracy, sensitivity, specificity, and F1-score of 94.16%, 89.56%, 99.10%, and 89.56%, respectively, for eight-class respiratory diseases; 79.61%, 78.55%, 92.49%, and 78.67%, respectively, for four-class diseases; and 85.61%, 83.44%, 83.44%, and 84.21%, respectively, for binary-class (normal vs. abnormal) lung sounds.
PubMed: 38927822
DOI: 10.3390/bioengineering11060586 -
JMIR Cardio Jun 2024Heart failure (HF) contributes greatly to morbidity, mortality, and health care costs worldwide. Hospital readmission rates are tracked closely and determine federal...
BACKGROUND
Heart failure (HF) contributes greatly to morbidity, mortality, and health care costs worldwide. Hospital readmission rates are tracked closely and determine federal reimbursement dollars. No current modality or technology allows for accurate measurement of relevant HF parameters in ambulatory, rural, or underserved settings. This limits the use of telehealth to diagnose or monitor HF in ambulatory patients.
OBJECTIVE
This study describes a novel HF diagnostic technology using audio recordings from a standard mobile phone.
METHODS
This prospective study of acoustic microphone recordings enrolled convenience samples of patients from 2 different clinical sites in 2 separate areas of the United States. Recordings were obtained at the aortic (second intercostal) site with the patient sitting upright. The team used recordings to create predictive algorithms using physics-based (not neural networks) models. The analysis matched mobile phone acoustic data to ejection fraction (EF) and stroke volume (SV) as evaluated by echocardiograms. Using the physics-based approach to determine features eliminates the need for neural networks and overfitting strategies entirely, potentially offering advantages in data efficiency, model stability, regulatory visibility, and physical insightfulness.
RESULTS
Recordings were obtained from 113 participants. No recordings were excluded due to background noise or for any other reason. Participants had diverse racial backgrounds and body surface areas. Reliable echocardiogram data were available for EF from 113 patients and for SV from 65 patients. The mean age of the EF cohort was 66.3 (SD 13.3) years, with female patients comprising 38.3% (43/113) of the group. Using an EF cutoff of ≤40% versus >40%, the model (using 4 features) had an area under the receiver operating curve (AUROC) of 0.955, sensitivity of 0.952, specificity of 0.958, and accuracy of 0.956. The mean age of the SV cohort was 65.5 (SD 12.7) years, with female patients comprising 34% (38/65) of the group. Using a clinically relevant SV cutoff of <50 mL versus >50 mL, the model (using 3 features) had an AUROC of 0.922, sensitivity of 1.000, specificity of 0.844, and accuracy of 0.923. Acoustics frequencies associated with SV were observed to be higher than those associated with EF and, therefore, were less likely to pass through the tissue without distortion.
CONCLUSIONS
This work describes the use of mobile phone auscultation recordings obtained with unaltered cellular microphones. The analysis reproduced the estimates of EF and SV with impressive accuracy. This technology will be further developed into a mobile app that could bring screening and monitoring of HF to several clinical settings, such as home or telehealth, rural, remote, and underserved areas across the globe. This would bring high-quality diagnostic methods to patients with HF using equipment they already own and in situations where no other diagnostic and monitoring options exist.
PubMed: 38924781
DOI: 10.2196/57111 -
Journal of Cardiovascular Development... May 2024The congenital Gerbode defect is defined as an abnormal communication between the left ventricle and the right atrium. This review aimed to summarize existing evidence,... (Review)
Review
The congenital Gerbode defect is defined as an abnormal communication between the left ventricle and the right atrium. This review aimed to summarize existing evidence, shed light on the clinical implications, and identify knowledge gaps. The systematic literature search was conducted in the PubMed and Google Scholar medical databases using specifically selected keywords. The inclusion of each publication was assessed according to predefined eligibility criteria based on the PICOM (Population, Phenomenon of Interest, Context, Methodology) schema. Titles and abstracts were screened independently by two authors. Available full-text versions of included publications were reviewed and relevant information was extracted. A total of 78 reports were included. The compilation of all congenital Gerbode defect cases described in the literature revealed a variety of clinical presentations comprising dyspnea, palpitations, growth retardation, and asymptomatology. A suitable multimodal diagnostic approach for newborns consists of auscultation, TTE, and optionally TEE and MRI. Because of its rarity, diversity of findings, unknown pathophysiology, and similarity to more common cardiac diseases, the diagnostic challenge remains significant. To prevent untreated long-term sequelae, early individualized treatment is recommended. Surgical defect closure is preferred to device closure for evidence reasons, although major developments are currently taking place. In conclusion, the congenital Gerbode defect provides a diagnostic challenge for pediatricians to allow early diagnosis and intervention in order to improve patients' quality of life.
PubMed: 38921666
DOI: 10.3390/jcdd11060166 -
Resuscitation Plus Sep 2024To examine speed and accuracy of newborn heart rate measurement by various assessment methods employed at birth. (Review)
Review
AIM
To examine speed and accuracy of newborn heart rate measurement by various assessment methods employed at birth.
METHODS
A search of Medline, SCOPUS, CINAHL and Cochrane was conducted between January 1, 1946, to until August 16, 2023. (CRD 42021283364) Study selection was based on predetermined criteria. Reviewers independently extracted data, appraised risk of bias and assessed certainty of evidence.
RESULTS
Pulse oximetry is slower and less precise than ECG for heart rate assessment. Both auscultation and palpation are imprecise for heart rate assessment. Other devices such as digital stethoscope, Doppler ultrasound, an ECG device using dry electrodes incorporated in a belt, photoplethysmography and electromyography are studied in small numbers of newborns and data are not available for extremely preterm or bradycardic newborns receiving resuscitation. Digital stethoscope is fast and accurate. Doppler ultrasound and dry electrode ECG in a belt are fast, accurate and precise when compared to conventional ECG with gel adhesive electrodes.
LIMITATIONS
Certainty of evidence was low or very low for most comparisons.
CONCLUSION
If resources permit, ECG should be used for fast and accurate heart rate assessment at birth. Pulse oximetry and auscultation may be reasonable alternatives but have limitations. Digital stethoscope, doppler ultrasound and dry electrode ECG show promise but need further study.
PubMed: 38912532
DOI: 10.1016/j.resplu.2024.100668 -
Medicina 2024Takotsubo syndrome, was described in Japan in 1990, it is a stress cardiomyopathy, predominantly in women, usually postmenopausal. Cardiac hypokinesia occurs, with...
Takotsubo syndrome, was described in Japan in 1990, it is a stress cardiomyopathy, predominantly in women, usually postmenopausal. Cardiac hypokinesia occurs, with involvement of multiple coronary territories. In intensive care unit (ICU), it is considered underdiagnosed. Manifestations of severe dengue fever include cardiovascular involvement, mainly arrhythmias and systolic dysfunction. A case of a 72-year-old man is presented, who was hospitalized in ICU for dengue fever, with plateletopenia (15000 cells/mm3) and dehydration. After fluid management the patient reported respiratory discomfort, auscultating crackling rales. A pulmonary ultrasound was made where bilateral B lines were found with B7 pattern compatible with interstitial syndrome and pulmonary edema. Basal hyperkinesia, medial and apical hypokinesia with an image consistent with apical ballooning were observed in the transthoracic echocardiogram. The electrocardiogram showed complete right bundle branch block. Chagas serology was negative and quantitative troponin I was increased. In the context of severe dengue, a Takotsubo syndrome was diagnosed. The patient evolved favorably. After discharge, a normalization of the cardiac function was stated in ultrasound images. The case is of clinical importance due to the low association of these two diseases and the need to screen for cardiac involvement in severe dengue.
Topics: Humans; Takotsubo Cardiomyopathy; Aged; Male; Dengue; Electrocardiography; Severe Dengue; Echocardiography
PubMed: 38907979
DOI: No ID Found -
IEEE Open Journal of Engineering in... 2024Auscultation for neonates is a simple and non-invasive method of diagnosing cardiovascular and respiratory disease. However, obtaining high-quality chest sounds...
Auscultation for neonates is a simple and non-invasive method of diagnosing cardiovascular and respiratory disease. However, obtaining high-quality chest sounds containing only heart or lung sounds is non-trivial. Hence, this study introduces a new deep-learning model named NeoSSNet and evaluates its performance in neonatal chest sound separation with previous methods. We propose a masked-based architecture similar to Conv-TasNet. The encoder and decoder consist of 1D convolution and 1D transposed convolution, while the mask generator consists of a convolution and transformer architecture. The input chest sounds were first encoded as a sequence of tokens using 1D convolution. The tokens were then passed to the mask generator to generate two masks, one for heart sounds and one for lung sounds. Each mask is then applied to the input token sequence. Lastly, the tokens are converted back to waveforms using 1D transposed convolution. Our proposed model showed superior results compared to the previous methods based on objective distortion measures, ranging from a 2.01 dB improvement to a 5.06 dB improvement. The proposed model is also significantly faster than the previous methods, with at least a 17-time improvement. The proposed model could be a suitable preprocessing step for any health monitoring system where only the heart sound or lung sound is desired.
PubMed: 38899018
DOI: 10.1109/OJEMB.2024.3401571 -
IEEE Open Journal of Engineering in... 2024In light of the COVID-19 pandemic, the early diagnosis of respiratory diseases has become increasingly crucial. Traditional diagnostic methods such as computed...
In light of the COVID-19 pandemic, the early diagnosis of respiratory diseases has become increasingly crucial. Traditional diagnostic methods such as computed tomography (CT) and magnetic resonance imaging (MRI), while accurate, often face accessibility challenges. Lung auscultation, a simpler alternative, is subjective and highly dependent on the clinician's expertise. The pandemic has further exacerbated these challenges by restricting face-to-face consultations. This study aims to overcome these limitations by developing an automated respiratory sound classification system using deep learning, facilitating remote and accurate diagnoses. We developed a deep convolutional neural network (CNN) model that utilizes spectrographic representations of respiratory sounds within an image classification framework. Our model is enhanced with attention feature fusion of low-to-high-level information based on a knowledge propagation mechanism to increase classification effectiveness. This novel approach was evaluated using the ICBHI benchmark dataset and a larger, self-collected Pediatric dataset comprising outpatient children aged 1 to 6 years. The proposed CNN model with knowledge propagation demonstrated superior performance compared to existing state-of-the-art models. Specifically, our model showed higher sensitivity in detecting abnormalities in the Pediatric dataset, indicating its potential for improving the accuracy of respiratory disease diagnosis. The integration of a knowledge propagation mechanism into a CNN model marks a significant advancement in the field of automated diagnosis of respiratory disease. This study paves the way for more accessible and precise healthcare solutions, which is especially crucial in pandemic scenarios.
PubMed: 38899013
DOI: 10.1109/OJEMB.2024.3402139 -
Indian Pediatrics Jun 2024Conventional stethoscope is a useful clinical examination tool to aid evaluation of the underlying clinical condition, especially respiratory and cardiac illnesses, even...
Conventional stethoscope is a useful clinical examination tool to aid evaluation of the underlying clinical condition, especially respiratory and cardiac illnesses, even before definitive imaging studies are performed. Auscultation with a stethoscope becomes highly challenging when wearing personal protective equipment (PPE) because the hood of the PPE covers both the ears. Herein, we describe an innovation that involves refashioning of the head cover device of the PPE suit to facilitate conventional auscultation using a stethoscope. In resource-limited settings where advanced gadgets such as wireless stethoscopes may be lacking, redesigning the head cover of the PPE suit can allow the use of manual stethoscopes without increasing the risk of exposure to the pathogen of concern.
Topics: Humans; Personal Protective Equipment; Stethoscopes; Auscultation; Equipment Design
PubMed: 38872294
DOI: No ID Found -
Chest Jun 2024A 57-year-old man was admitted to our hospital via the ED presenting in reduced general condition because of an infection of unknown origin, generalized edema, and...
A 57-year-old man was admitted to our hospital via the ED presenting in reduced general condition because of an infection of unknown origin, generalized edema, and dyspnea at rest (peripheral capillary oxygen saturation, 89%) that required 2 L/min intranasal oxygen. Anamnesis was complicated by an infection-triggered delirium, but his wife reported an increasing physical decay that had led to bed confinement. The BP was reduced at 88/55 mm Hg with a normal heart rate of 86 beats/min. Lung auscultation showed mild bipulmonal rales. Previous comorbidities were a BMI of 42 kg/m, an insulin-dependent type 2 diabetes mellitus with a severe diabetes-related chronic kidney disease stage G4A3, and systemic arterial hypertension.
Topics: Humans; Male; Middle Aged; Pulmonary Artery; Vascular Calcification; Tomography, X-Ray Computed; Diagnosis, Differential
PubMed: 38852977
DOI: 10.1016/j.chest.2024.02.022