Reliability of crackles in fibrotic interstitial lung disease: a prospective, longitudinal study.

BACKGROUND: Although crackles on chest auscultation represent a fundamental component of the diagnostic suspect for fibrotic interstitial lung disease (ILD), their reliability has not been properly studied. We assessed the agreement among respiratory physicians on the presence and changes over time of audible crackles collected in a prospective longitudinal cohort of patients with fibrotic ILD. METHODS: Lung sounds were digitally recorded at baseline and after 12 months at eight anatomical sites. Nine respiratory physicians blindly assessed randomized couples of recordings obtained from the same anatomical site at different timepoints. The physicians indicated the presence of crackles in individual recordings and which recording from each couple eventually had more intense crackles. Fleiss' kappa coefficient was used to measure inter- and intra-rater agreement. RESULTS: Fifty-two patients, mostly with a diagnosis of IPF (n = 40, 76.9%) were prospectively enrolled between October 2019 and May 2021. The final acoustic dataset included 702 single recordings, corresponding to 351 couples of recordings from baseline and 12-months timepoints. Kappa coefficient was 0.57 (95% CI 0.55-0.58) for the presence of crackles and 0.42 (95% CI 0.41-0.43) for acoustic change. Intra-rater agreement, measured for three respiratory physicians on three repeated assessments, ranged from good to excellent for the presence of crackles (κ = 0.87, κ = 0.86, κ = 0.79), and from moderate to good for acoustic change (κ = 0.75, κ = 0.76, κ = 0.57). CONCLUSIONS: Agreement between respiratory physicians for the presence of crackles and acoustic change was acceptable, suggesting that crackles represent a reliable acoustic finding in patients with fibrotic ILD. Their role as a lung-derived indicator of disease progression merits further studies.

Exploring the link between a novel approach for computer aided lung sound analysis and imaging biomarkers: a cross-sectional study.

BACKGROUND: Computer Aided Lung Sound Analysis (CALSA) aims to overcome limitations associated with standard lung auscultation by removing the subjective component and allowing quantification of sound characteristics. In this proof-of-concept study, a novel automated approach was evaluated in real patient data by comparing lung sound characteristics to structural and functional imaging biomarkers. METHODS: Patients with cystic fibrosis (CF) aged > 5y were recruited in a prospective cross-sectional study. CT scans were analyzed by the CF-CT scoring method and Functional Respiratory Imaging (FRI). A digital stethoscope was used to record lung sounds at six chest locations. Following sound characteristics were determined: expiration-to-inspiration (E/I) signal power ratios within different frequency ranges, number of crackles per respiratory phase and wheeze parameters. Linear mixed-effects models were computed to relate CALSA parameters to imaging biomarkers on a lobar level. RESULTS: 222 recordings from 25 CF patients were included. Significant associations were found between E/I ratios and structural abnormalities, of which the ratio between 200 and 400 Hz appeared to be most clinically relevant due to its relation with bronchiectasis, mucus plugging, bronchial wall thickening and air trapping on CT. The number of crackles was also associated with multiple structural abnormalities as well as regional airway resistance determined by FRI. Wheeze parameters were not considered in the statistical analysis, since wheezing was detected in only one recording. CONCLUSIONS: The present study is the first to investigate associations between auscultatory findings and imaging biomarkers, which are considered the gold standard to evaluate the respiratory system. Despite the exploratory nature of this study, the results showed various meaningful associations that highlight the potential value of automated CALSA as a novel non-invasive outcome measure in future research and clinical practice.

Automated Interpretation of Lung Sounds by Deep Learning in Children With Asthma: Scoping Review and Strengths, Weaknesses, Opportunities, and Threats Analysis.

BACKGROUND: The interpretation of lung sounds plays a crucial role in the appropriate diagnosis and management of pediatric asthma. Applying artificial intelligence (AI) to this task has the potential to better standardize assessment and may even improve its predictive potential. OBJECTIVE: This study aims to objectively review the literature on AI-assisted lung auscultation for pediatric asthma and provide a balanced assessment of its strengths, weaknesses, opportunities, and threats. METHODS: A scoping review on AI-assisted lung sound analysis in children with asthma was conducted across 4 major scientific databases (PubMed, MEDLINE Ovid, Embase, and Web of Science), supplemented by a gray literature search on Google Scholar, to identify relevant studies published from January 1, 2000, until May 23, 2023. The search strategy incorporated a combination of keywords related to AI, pulmonary auscultation, children, and asthma. The quality of eligible studies was assessed using the ChAMAI (Checklist for the Assessment of Medical Artificial Intelligence). RESULTS: The search identified 7 relevant studies out of 82 (9%) to be included through an academic literature search, while 11 of 250 (4.4%) studies from the gray literature search were considered but not included in the subsequent review and quality assessment. All had poor to medium ChAMAI scores, mostly due to the absence of external validation. Identified strengths were improved predictive accuracy of AI to allow for prompt and early diagnosis, personalized management strategies, and remote monitoring capabilities. Weaknesses were the heterogeneity between studies and the lack of standardization in data collection and interpretation. Opportunities were the potential of coordinated surveillance, growing data sets, and new ways of collaboratively learning from distributed data. Threats were both generic for the field of medical AI (loss of interpretability) but also specific to the use case, as clinicians might lose the skill of auscultation. CONCLUSIONS: To achieve the opportunities of automated lung auscultation, there is a need to address weaknesses and threats with large-scale coordinated data collection in globally representative populations and leveraging new approaches to collaborative learning.

Breath Measurement Method for Synchronized Reproduction of Biological Tones in an Augmented Reality Auscultation Training System.

An educational augmented reality auscultation system (EARS) is proposed to enhance the reality of auscultation training using a simulated patient. The conventional EARS cannot accurately reproduce breath sounds according to the breathing of a simulated patient because the system instructs the breathing rhythm. In this study, we propose breath measurement methods that can be integrated into the chest piece of a stethoscope. We investigate methods using the thoracic variations and frequency characteristics of breath sounds. An accelerometer, a magnetic sensor, a gyro sensor, a pressure sensor, and a microphone were selected as the sensors. For measurement with the magnetic sensor, we proposed a method by detecting the breathing waveform in terms of changes in the magnetic field accompanying the surface deformation of the stethoscope based on thoracic variations using a magnet. During breath sound measurement, the frequency spectra of the breath sounds acquired by the built-in microphone were calculated. The breathing waveforms were obtained from the difference in characteristics between the breath sounds during exhalation and inhalation. The result showed the average value of the correlation coefficient with the reference value reached 0.45, indicating the effectiveness of this method as a breath measurement method. And the evaluations suggest more accurate breathing waveforms can be obtained by selecting the measurement method according to breathing method and measurement point.

Novel Approach Combining Shallow Learning and Ensemble Learning for the Automated Detection of Swallowing Sounds in a Clinical Database.

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.

SonicGuard Sensor-A Multichannel Acoustic Sensor for Long-Term Monitoring of Abdominal Sounds Examined through a Qualification Study.

Auscultation is a fundamental diagnostic technique that provides valuable diagnostic information about different parts of the body. With the increasing prevalence of digital stethoscopes and telehealth applications, there is a growing trend towards digitizing the capture of bodily sounds, thereby enabling subsequent analysis using machine learning algorithms. This study introduces the SonicGuard sensor, which is a multichannel acoustic sensor designed for long-term recordings of bodily sounds. We conducted a series of qualification tests, with a specific focus on bowel sounds ranging from controlled experimental environments to phantom measurements and real patient recordings. These tests demonstrate the effectiveness of the proposed sensor setup. The results show that the SonicGuard sensor is comparable to commercially available digital stethoscopes, which are considered the gold standard in the field. This development opens up possibilities for collecting and analyzing bodily sound datasets using machine learning techniques in the future.

Cervical Auscultation for Detecting Oropharyngeal Aspiration in Paediatric and Adult Populations: A Systematic Review and Meta-Analysis.

BACKGROUND: Cervical auscultation (CA) involves listening to swallowing and respiratory sounds and/or vibrations to detect oropharyngeal aspiration (OPA). CA has shown promising diagnostic test accuracy when used with the clinical swallowing examination and is gaining popularity in clinical practise. There has not been a review to date analysing the accuracy of CA in paediatric and adult populations with meta-analyses. OBJECTIVES: To determine the accuracy of CA in detecting OPA in paediatric and adult populations, when compared to instrumental assessments. SEARCH METHODS: Databases searched included MEDLINE, PubMed, Embase, CINAHL, AustHealth, Cochrane and Web of Science. The search was restricted between 01 October 2012 and 01 October 2022. SELECTION CRITERIA: Inclusion criteria included (a) all clinical populations of all ages, (b) who have had an instrumental assessment and (c) CA. All study types were included. DATA COLLECTION AND ANALYSIS: Studies were reviewed independently by two authors. The methodological quality of the studies was analysed using the QUADAS-2. MAIN RESULTS: Ten studies met the inclusion criteria for this review and meta-analyses. The pooled diagnostic performance of CA in detecting OPA was 0.91 for sensitivity and 0.79 for specificity. The area under the curve summary receiver operating curve (sROC) was estimated to be 0.86, thereby indicating good discrimination of OPA. Most studies scored high for risk of bias in at least one domain in the QUADAS-2, likely attributed to a lack of high-quality prospectively designed studies. CONCLUSIONS: There are promising diagnostic test accuracies for the use of CA in detection of OPA. Future research could include using CA in specific clinical populations and settings, and identifying standardised criteria for CA.

[Research Progress of Breath Sound Analysis for Common Respiratory Diseases in Children].

Breath sounds can reflect the physiological and pathological conditions of the lungs and airways.Due to the differences in acoustic characteristics of breath sounds between healthy children and those with different respiratory diseases,analyzing breath sounds may provide important information for the diagnosis and treatment of respiratory diseases in children.With the development of digital auscultation,children's breath sounds have gradully become a research focus.This article summarizes the recent research progress in breath sound analysis for the diagnosis and treatment of common respiratory diseases in children,offering reference for the research in related fields.

[Improving adaptive noise reduction performance of body sound auscultation through linear preprocessing].

Adaptive filtering methods based on least-mean-square (LMS) error criterion have been commonly used in auscultation to reduce ambient noise. For non-Gaussian signals containing pulse components, such methods are prone to weights misalignment. Unlike the commonly used variable step-size methods, this paper introduced linear preprocessing to address this issue. The role of linear preprocessing in improving the denoising performance of the normalized least-mean-square (NLMS) adaptive filtering algorithm was analyzed. It was shown that, the steady-state mean square weight deviation of the NLMS adaptive filter was proportional to the variance of the body sounds and inversely proportional to the variance of the ambient noise signals in the secondary channel. Preprocessing with properly set parameters could suppress the spikes of body sounds, and decrease the variance and the power spectral density of the body sounds, without significantly reducing or even with increasing the variance and the power spectral density of the ambient noise signals in the secondary channel. As a result, the preprocessing could reduce weights misalignment, and correspondingly, significantly improve the performance of ambient-noise reduction. Finally, a case of heart-sound auscultation was given to demonstrate how to design the preprocessing and how the preprocessing improved the ambient-noise reduction performance. The results can guide the design of adaptive denoising algorithms for body sound auscultation.

[Bowel Sounds Detection Method Based on ResNet-BiLSTM and Attention Mechanism].

Bowel sounds can reflect the movement and health status of the gastrointestinal tract. However, the traditional manual auscultation method has subjective deviation and is time-consuming and labor-intensive. In order to better assist doctors in diagnosing bowel sounds and improve the reliability and efficiency of bowel sound detection, this study proposed a deep neural network model that combines a residual neural network (ResNet), a bidirectional long short-term memory network (BiLSTM), and an attention mechanism. Firstly, a large number of labeled clinical data was collected using the self-developed multi-channel bowel sound acquisition system, and the multi-scale wavelet decomposition and reconstruction method was used to preprocess the bowel sounds. Then, log Mel spectrogram features were extracted and sent to the network for training. Finally, the performance and effectiveness of the model were evaluated and verified by 10-fold cross-validation and an ablation experiment. The experimental results showed that the precision, recall, and F 1 score of the model reached 83%, 76%, and 79%, respectively, and it could effectively detect bowel sound segments and locate their start and end times, performing better than previous algorithms. This algorithm can not only provide auxiliary information for doctors in clinical practice but also offer technical support for further analysis and research of bowel sounds.

Laennecs' mediate auscultation: Child's play.

Before Laennec, respiratory diseases that we recognize today were often confused, because the heart and lung are locked inside the rib cage. Impressed by the autopsies performed by Xavier Bichat (1771-1802), Laennec maintained the importance of the anatomoclinical method. But he indicated in his early 1820s lectures at the Collège de France that the discovery of auscultation was fortuitous and empirical. Duffin demonstrates that medical discoveries hardly obey an implacable logic, they arise outside of pre-established projects. In this paper, we retrace the chronology and antecedents at the origin of the important medical invention that is the stethoscope.

Reference blood pressure values obtained using the auscultation method for 2-year-old Japanese children: from the Japan Environment and Children's Study.

BACKGROUND: Reference blood pressure (BP) values for Japanese children based on a large number of measurements by auscultation have not yet been established. METHODS: This was a cross-sectional analysis of data from a birth-cohort study. The data from the sub-cohort study conducted for children at the age of 2 years in the Japan Environment and Children's Study from April 2015 to January 2017 were analyzed. BP was measured via auscultation using an aneroid sphygmomanometer. Each participant was measured in triplicate, and the average value of two consecutive measurements with a difference of less than 5 mmHg was recorded. The reference BP values were estimated using the lambda-mu-sigma (LMS) method and compared with those obtained via the polynomial regression model. RESULTS: Data from 3361 participants were analyzed. Although the difference between the estimated BP values by the LMS and the polynomial regression model was small, the LMS model was more valid based on the results of the fit curve of the observed values and regression models for each model. For 2-year-old children with heights in the 50th percentile, the 50th, 90th, 95th, and 99th percentile reference values of systolic BP (mmHg) for boys were 91, 102, 106, and 112, and that for girls were 90, 101, 103, and 109, respectively, and those of diastolic BP for boys were 52, 62, 65, and 71, and that for girls were 52, 62, 65, and 71, respectively. CONCLUSION: The reference BP values for 2-year-old Japanese children were determined based on auscultation and were made available.

Clinical tests for confirming tracheal intubation or excluding oesophageal intubation: a diagnostic test accuracy systematic review and meta-analysis.

Unrecognised oesophageal intubation causes preventable serious harm to patients undergoing tracheal intubation. When capnography is unavailable or doubted, clinicians still use clinical findings to confirm tracheal intubation, or exclude oesophageal intubation, and false reassurance from clinical examination is a recurring theme in fatal cases of unrecognised oesophageal intubation. We conducted a systematic review and meta-analysis of the diagnostic accuracy of five clinical examination tests and the oesophageal detector device when used to confirm tracheal intubation. We searched four databases for studies reporting index clinical tests against a reference standard, from inception to 28 February 2023. We included 49 studies involving 10,654 participants. Methodological quality was overall moderate to high. We looked at misting (three studies, 115 participants); lung auscultation (three studies, 217 participants); combined lung and epigastric auscultation (four studies, 506 participants); the oesophageal detector device (25 studies, 3024 participants); 'hang-up' (two non-human studies); and chest rise (one non-human study). The reference standards used were capnography (22 studies); direct vision (10 studies); and bronchoscopy (three studies). When used to confirm tracheal intubation, misting has a false positive rate (95%CI) of 0.69 (0.43-0.87); lung auscultation 0.14 (0.08-0.23); five-point auscultation 0.18 (0.08-0.36); and the oesophageal detector device 0.05 (0.02-0.09). Tests to exclude events that invariably lead to severe damage or death must have a negligible false positive rate. Misting or auscultation have too high a false positive rate to reliably exclude oesophageal intubation and there is insufficient evidence to support the use of 'hang-up' or chest rise. The oesophageal detector device may be considered where other more reliable means are not available, though waveform capnography remains the reference standard for confirmation of tracheal intubation.

Agreement of Oscillometric and Auscultatory blood pressure measurement methods: An ambulance noise simulation study.

OBJECTIVE: Although noise is known to negatively affect blood pressure (BP) measurements, its impact on different BP measurement methods remains unclear. The aim of this study is to compare the agreement of oscillometric and auscultatory BP measurement methods under in-ambulance noise levels. METHODS: This method-comparison study was conducted on 50 healthy volunteers in a tertiary emergency department (ED). Participants were divided into two groups of 25, and BP was measured using auscultatory and oscillometric methods in noisy and ambient environments by 2 emergency medicine technicians (EMT). The primary object of the study was to compare the agreement of auscultatory mercury sphygmomanometers and automated auscillometric BP measurements in ambient and noisy environments. RESULTS: We examined the agreement between auscultative and oscillometric measurements of BP conducted in an ambient environment (46.75 [IQR (41.2--55.18)] dB) and found that both systolic and diastolic BP were within the level of agreement (LoA) established before the study (systolic BP [-13.96 to 8.48 mmHG], diastolic BP [-7.44 to 8.08 mmHg]); whereas, in noisy environment (92.35 [IQR 88-96.55] dB) both systolic and diastolic BP were outside the range of LoA (systolic BP [-37.77 to 9.94 mmHg], diastolic BP [-21.73 to 16.37 mmHg]). Additionally, we found that in ambient environments, concordance correlation coefficients were higher than in noisy environments (0.943 [0.906-0.966], 0.957 [0.93-0.974]; 0.574 [0.419-0.697], 0.544 [0.326-0.707]; systolic and diastolic BP, respectively). CONCLUSION: The results of this study demonstrate that noise significantly affects the agreement between oscillometric and auscultatory blood pressure measurement methods.

Clinical and imaging factors that can predict contagiousness of pulmonary tuberculosis.

BACKGROUND: Knowledge on predicting pulmonary tuberculosis (PTB) contagiosity in the hospital admission setting is limited. The objective was to assess clinical and radiological criteria to predict PTB contagiosity. METHODS: Retrospective analysis of 7 clinical, 4 chest X-ray (CXR) and 5 computed tomography (CT) signs in 299 PTB patients admitted to an urban tertiary hospital from 2008 to 2016. If the acid fact bacilli stain was positive (AFB+) on admission, the case was considered high contagiosity. RESULTS: Best predictors for high PTB contagiosity (AFB+) were haemoptysis (OR 4.33), cough (3.00), weight loss (2.96), cavitation in CT (2.75), cavitation in CXR (2.55), tree-in-bud-sign in CT (2.12), German residency of the patient (1.89), and abnormal auscultation findings (1.83). A previous TB infection reduced the risk of contagiosity statistically (0.40). Radiographic infiltrates, miliary picture, and pleural effusion were not helpful in predicting high or low contagiosity. 34% of all patients were clinically asymptomatic (20% of the highly contagious group, 50% of the low contagious group). CONCLUSION: Haemoptysis, cough and weight loss as well as cavitation and tree-in-bud sign in CXR/CT can be helpful to predict PTB contagiosity and to improve PTB management.

Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study.

BACKGROUND: Interstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prompt and accurate diagnosis is important to enable patients to receive appropriate care at the earliest possible stage to delay disease progression and prolong survival. Artificial intelligence-assisted lung auscultation and ultrasound (LUS) could constitute an alternative to conventional, subjective, operator-related methods for the accurate and earlier diagnosis of these diseases. This protocol describes the standardised collection of digitally-acquired lung sounds and LUS images of adult outpatients with IPF, NSIP or COPD and a deep learning diagnostic and severity-stratification approach. METHODS: A total of 120 consecutive patients (≥ 18 years) meeting international criteria for IPF, NSIP or COPD and 40 age-matched controls will be recruited in a Swiss pulmonology outpatient clinic, starting from August 2022. At inclusion, demographic and clinical data will be collected. Lung auscultation will be recorded with a digital stethoscope at 10 thoracic sites in each patient and LUS images using a standard point-of-care device will be acquired at the same sites. A deep learning algorithm (DeepBreath) using convolutional neural networks, long short-term memory models, and transformer architectures will be trained on these audio recordings and LUS images to derive an automated diagnostic tool. The primary outcome is the diagnosis of ILD versus control subjects or COPD. Secondary outcomes are the clinical, functional and radiological characteristics of IPF, NSIP and COPD diagnosis. Quality of life will be measured with dedicated questionnaires. Based on previous work to distinguish normal and pathological lung sounds, we estimate to achieve convergence with an area under the receiver operating characteristic curve of > 80% using 40 patients in each category, yielding a sample size calculation of 80 ILD (40 IPF, 40 NSIP), 40 COPD, and 40 controls. DISCUSSION: This approach has a broad potential to better guide care management by exploring the synergistic value of several point-of-care-tests for the automated detection and differential diagnosis of ILD and COPD and to estimate severity. Trial registration Registration: August 8, 2022. CLINICALTRIALS: gov Identifier: NCT05318599.

Performance of the Aktiia optical blood pressure measurement device in the elderly: a comparison with double blinded auscultation in different body positions.

BACKGROUND: Accurate blood pressure (BP) measurement is essential for the correct diagnosis and management of hypertension (HTN) especially in the elderly population. As with of all BP devices, the accuracy of cuffless devices must be verified. This study (NCT04027777) aimed to evaluate the performance of a wrist cuffless optical BP device in an elderly population cohort in different body positions with auscultation as the reference measurement. DESIGN AND METHODS: Patients aged 65-85 years with different BP categories but without diabetes were recruited. After an initial calibration based on auscultatory measurements, BP estimation from the Aktiia Bracelet (Aktiia SA, Switzerland) were compared to reference double-blinded auscultatory measurements in sitting, standing and lying positions on four separate visits distributed over one month. In the absence of a universal standard for cuffless BP device at the time of the study, modified ISO81060-2 criteria were used for performance analysis. RESULTS: Thirty-five participants were included in the analysis fulfilling the inclusion requirements of ISO 81060-2. A total of 469 paired measurements were obtained with overall 83% acceptance rate. Differences (mean ± SD)   between Aktiia Bracelet and auscultation for systolic BP were -0.26 ± 9.96 mmHg for all body positions aggregated (sitting 1.23 ± 7.88 mmHg, standing -1.81 ± 11.11 mmHg, lying -1.8 ± 9.96 mmHg). Similarly, differences for diastolic BP were -0.75 ± 7.0 mmHg (0.2 ± 5.55 mmHg, -5.35 ± 7.75 mmHg and -0.94 ± 7.47 mmHg, respectively). Standard deviation of the averaged differences per subject for systolic/diastolic BP was 3.8/2.5 mmHg in sitting and 4.4/3.7 mmHg for all body positions aggregated. CONCLUSIONS: Overall, this study demonstrates a similar performance of the Aktiia Bracelet compared to auscultation in an elderly population in body positions representative of daily activities. The use of more comfortable, non-invasive, and non-occlusive BP monitors during long periods may facilitate e-health and may contribute to better management of HTN, including diagnosis and treatment of HTN, in the elderly.

Accuracy of blood pressure measurements is essential in the diagnosis and the follow-up of patients with high blood pressure. As with any blood pressure measuring device, a validation is necessary. In this study including a elderly population, we compared values obtained by the cuffless Aktiia Bracelet (Aktiia SA, Switzerland) after an initial calibration with the reference auscultatory method during four separate study days distributed over one month. We show that the accuracy of the Aktiia Bracelet is similar to auscultation. The accuracy varies depending on the position in which the measurement is performed. Overall, the accuracy is not modified by a higher age category. The use of a cuffless device in the elderly population characterized by high prevalence of hypertension may facilitate the follow-up of blood pressure with more comfort and minimal constraints.

Dysphagia Management and Cervical Auscultation: Reliability and Validity Against FEES.

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 (rs [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.

Masking of Korotkoff sounds used in blood pressure measurement through auscultation.

Measurement of blood pressure (BP) through manual auscultation and the observation of Korotkoff sounds (KSs) remains the gold standard in BP methodology. Critical to determining BP levels via auscultation is the determination of KS audibility. While absolute sound level audibility is well researched, the problem has not been approached from the point of view of psychoacoustic masking of the sounds. Here, during manual auscultation of BP, a direct comparison is made between what an observer perceives as audible and the electronic analysis of audibility level determined from masking of sound signal levels. KSs are collected during auscultation with an electronic stethoscope, which allows simultaneously observing sound audibility and recording the sound electronically. By time-segmenting the recorded sound around Korotkoff peaks into a test segment and a masking segment, performing Fourier transforms on the segments, and comparing frequency-band sound energy levels, signal-to-noise ratios of a sound to its masking counterpart can be defined. Comparing these ratios to difference limen in the psychoacoustic masking literature, an approximate threshold for sound audibility is obtained. It is anticipated that this approach could have profound effects on future development of automated auscultation BP measurements.

Cardiac screening in school children: Combining auscultation and electrocardiography with a crowdsourcing model.

BACKGROUND/PURPOSE: School-based cardiac screening is useful for identifying children and adolescents with a high risk of sudden cardiac death. However, because of challenges associated with cost, distance, and human resources, cardiac screening is not widely implemented, especially in rural areas with limited medical resources. This study aims to establish a cloud-based system suitable for mass cardiac screening of schoolchildren in rural areas with limited medical resources. METHODS: Students from three schools were included. They or their guardians completed a simple questionnaire, administered in paper or electronic form. Heart sounds were recorded using an electronic stethoscope. Twelve-lead electrocardiograms (ECGs) were recorded and digitalized. The signals were transmitted through Bluetooth to a tablet computer and then uploaded to a cloud server over Wi-Fi. Crowdsourced pediatric cardiologists reviewed those data from a web-based platform and provided remote consultation. In cases in which abnormal heart sounds or ECGs were noted, the students were referred to the hospital for further evaluation. RESULTS: A total of 1004 students were enrolled in this study. Of the 138 students referred, 62 were diagnosed as having an abnormal heart condition and most had previously been undiagnosed. The interrater agreeability was high. CONCLUSION: An innovative strategy combining a cloud-based cardiac screening system with remote consultation by crowdsourced experts was established. This system allows pediatric cardiologists to provide consultation and make reliable diagnoses. Combined with crowdsourcing, the system constitutes a viable approach for mass cardiac screening in children and adolescents living in rural areas with insufficient medical resources.