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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 -
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 -
European Journal of Case Reports in... 2024Small cell lung cancer is an aggressive tumor with a poor prognosis that requires prompt treatment. While radiotherapy may enhance survival when superior vena cava...
BACKGROUND
Small cell lung cancer is an aggressive tumor with a poor prognosis that requires prompt treatment. While radiotherapy may enhance survival when superior vena cava syndrome is present, radiation therapy-induced pericardial disease can be a potential complication.
CASE REPORT
A 55-year-old man, who recently underwent radiotherapy for stage IV small-cell lung cancer complicated by superior vena cava syndrome, presented with chest pain and dyspnea. In the emergency room, he was dyspneic, hypotensive, and tachycardic. Pulmonary auscultation revealed the absence of lung sounds on the right. The initial electrocardiogram showed ST-segment elevation in lateral leads and in lead DII, with reciprocal changes in lead DIII. A bedside transthoracic echocardiogram revealed cardiac tamponade and emergent pericardiocentesis was performed, removing 500 ml of purulent fluid, resulting in an immediate clinical improvement. Thoracentesis was also performed, showing no empyema. Large spectrum empirical antibiotic therapy was started. Cultures from the pericardial fluid and peripheral blood grew multi-sensitive . Cytological analysis of the pericardial fluid was consistent with infection. The patient improved after 2 weeks of targeted antibiotic therapy and underwent the first cycle of chemotherapy. He was discharged with an early scheduled pulmonology appointment.
CONCLUSIONS
Although the most common causes of pericardial effusion in lung cancer are malignant, non-malignant etiologies should also be considered. This patient had an infectious pericardial effusion most probably due to a pericardial-mediastinal mass fistula caused by radiotherapy. This was a diagnostic challenge, both in the emergency room as well in the inpatient setting.
LEARNING POINTS
Small cell lung cancer is a fast-growing cancer that exhibits aggressive behavior.In patients with lung cancer, malignant pericardial effusions are more common than non-malignant ones.Purulent pericardial effusions, especially those due to lung cancer, are rare in developed countries with very few reports in the literature.
PubMed: 38846671
DOI: 10.12890/2024_004477 -
Pneumonia (Nathan Qld.) Jun 2024The Covid-19 pandemic has caused immense pressure on Intensive Care Units (ICU). In patients with severe ARDS due to Covid-19, respiratory mechanics are important for...
BACKGROUND
The Covid-19 pandemic has caused immense pressure on Intensive Care Units (ICU). In patients with severe ARDS due to Covid-19, respiratory mechanics are important for determining the severity of lung damage. Lung auscultation could not be used during the pandemic despite its merit. The main objective of this study was to investigate associations between lung auscultatory sound features and lung mechanical properties, length of stay (LOS) and survival, in adults with severe Covid-19 ARDS.
METHODS
Consecutive patients admitted to a large ICU between 2020 and 2021 (n = 173) were included. Digital stethoscopes obtained auscultatory sounds and stored them in an on-line database for replay and further processing using advanced AI techniques. Correlation and regression analysis explored relationships between digital auscultation findings and lung mechanics or the ICU outcome. The resulting annotated lung sounds database is also publicly available as supplementary material.
RESULTS
The presence of squawks was associated with the ICU LOS, outcome and 90-day mortality. Other features (age, SOFA score & oxygenation index upon admission, minimum crackle entropy) had significant impact on outcome. Additional features affecting the 90-d survival were age and mean crackle entropy. Multivariate logistic regression showed that survival was affected by age, baseline SOFA, baseline oxygenation index and minimum crackle entropy.
CONCLUSIONS
Respiratory mechanics were associated with various adventitious sounds, whereas the lung sound analytics and the presence of certain adventitious sounds correlated with the ICU outcome and the 90-d survival. Spectral features of crackles sounds can serve as prognostic factors for survival, highlighting the importance of digital auscultation.
PubMed: 38835101
DOI: 10.1186/s41479-024-00131-1 -
BMJ Open May 2024This study aimed to describe the clinical characteristics of adults with suspected acute community-acquired pneumonia (CAP) on hospitalisation, evaluate their prediction...
Community-acquired pneumonia: use of clinical characteristics of acutely admitted patients for the development of a diagnostic model - a cross-sectional multicentre study.
OBJECTIVES
This study aimed to describe the clinical characteristics of adults with suspected acute community-acquired pneumonia (CAP) on hospitalisation, evaluate their prediction performance for CAP and compare the performance of the model to the initial assessment of the physician.
DESIGN
Cross-sectional, multicentre study.
SETTING
The data originated from the INfectious DisEases in Emergency Departments study and were collected prospectively from patient interviews and medical records. The study included four Danish medical emergency departments (EDs) and was conducted between 1 March 2021 and 28 February 2022.
PARTICIPANTS
A total of 954 patients admitted with suspected infection were included in the study.
PRIMARY AND SECONDARY OUTCOME
The primary outcome was CAP diagnosis assessed by an expert panel.
RESULTS
According to expert evaluation, CAP had a 28% prevalence. 13 diagnostic predictors were identified using least absolute shrinkage and selection operator regression to build the prediction model: dyspnoea, expectoration, cough, common cold, malaise, chest pain, respiratory rate (>20 breaths/min), oxygen saturation (<96%), abnormal chest auscultation, leucocytes (<3.5×10/L or >8.8×10/L) and neutrophils (>7.5×10/L). C reactive protein (<20 mg/L) and having no previous event of CAP contributed negatively to the final model. The predictors yielded good prediction performance for CAP with an area under the receiver-operator characteristic curve (AUC) of 0.85 (CI 0.77 to 0.92). However, the initial diagnosis made by the ED physician performed better, with an AUC of 0.86 (CI 84% to 89%).
CONCLUSION
Typical respiratory symptoms combined with abnormal vital signs and elevated infection biomarkers were predictors for CAP on admission to an ED. The clinical value of the prediction model is questionable in our setting as it does not outperform the clinician's assessment. Further studies that add novel diagnostic tools and use imaging or serological markers are needed to improve a model that would help diagnose CAP in an ED setting more accurately.
TRIAL REGISTRATION NUMBER
NCT04681963.
Topics: Humans; Community-Acquired Infections; Cross-Sectional Studies; Male; Female; Middle Aged; Aged; Pneumonia; Emergency Service, Hospital; Hospitalization; Denmark; Adult; ROC Curve; Prospective Studies; C-Reactive Protein
PubMed: 38816044
DOI: 10.1136/bmjopen-2023-079123 -
PeerJ 2024During the COVID-19 pandemic, universal mask-wearing became one of the main public health interventions. Because of this, most physical examinations, including lung...
OBJECTIVE
During the COVID-19 pandemic, universal mask-wearing became one of the main public health interventions. Because of this, most physical examinations, including lung auscultation, were done while patients were wearing surgical face masks. The aim of this study was to investigate whether mask wearing has an impact on pulmonologist assessment during auscultation of the lungs.
METHODS
This was a repeated measures crossover design study. Three pulmonologists were instructed to auscultate patients with previously verified prolonged expiration, wheezing, or crackles while patients were wearing or not wearing masks (physician and patients were separated by an opaque barrier). As a measure of pulmonologists' agreement in the assessment of lung sounds, we used Fleiss kappa (K).
RESULTS
There was no significant difference in agreement on physician assessment of lung sounds in all three categories (normal lung sound, duration of expiration, and adventitious lung sound) whether the patient was wearing a mask or not, but there were significant differences among pulmonologists when it came to agreement of lung sound assessment.
CONCLUSION
Clinicians and health professionals are safer from respiratory infections when they are wearing masks, and patients should be encouraged to wear masks because our research proved no significant difference in agreement on pulmonologists' assessment of auscultated lung sounds whether or not patients wore masks.
Topics: Humans; Masks; COVID-19; Cross-Over Studies; Auscultation; Male; Respiratory Sounds; Female; SARS-CoV-2; Middle Aged; Adult; Pandemics; Pulmonologists; Aged
PubMed: 38803582
DOI: 10.7717/peerj.17368 -
Sensors (Basel, Switzerland) May 2024Cervical auscultation is a simple, noninvasive method for diagnosing dysphagia, although the reliability of the method largely depends on the subjectivity and experience...
Cervical auscultation is a simple, noninvasive method for diagnosing dysphagia, although the reliability of the method largely depends on the subjectivity and experience of the evaluator. Recently developed methods for the automatic detection of swallowing sounds facilitate a rough automatic diagnosis of dysphagia, although a reliable method of detection specialized in the peculiar feature patterns of swallowing sounds in actual clinical conditions has not been established. We investigated a novel approach for automatically detecting swallowing sounds by a method wherein basic statistics and dynamic features were extracted based on acoustic features: Mel Frequency Cepstral Coefficients and Mel Frequency Magnitude Coefficients, and an ensemble learning model combining Support Vector Machine and Multi-Layer Perceptron were applied. The evaluation of the effectiveness of the proposed method, based on a swallowing-sounds database synchronized to a video fluorographic swallowing study compiled from 74 advanced-age patients with dysphagia, demonstrated an outstanding performance. It achieved an F1-micro average of approximately 0.92 and an accuracy of 95.20%. The method, proven effective in the current clinical recording database, suggests a significant advancement in the objectivity of cervical auscultation. However, validating its efficacy in other databases is crucial for confirming its broad applicability and potential impact.
Topics: Humans; Deglutition; Deglutition Disorders; Auscultation; Databases, Factual; Support Vector Machine; Male; Female; Aged; Machine Learning; Algorithms; Sound
PubMed: 38793908
DOI: 10.3390/s24103057