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Journal of Equine Veterinary Science Apr 2024A 25-year-old female mule weighing 336 kg was referred with a history of lethargy, abdominal discomfort, anorexia, and constipation in the previous 24 hours. On...
A 25-year-old female mule weighing 336 kg was referred with a history of lethargy, abdominal discomfort, anorexia, and constipation in the previous 24 hours. On admission, decreased intestinal borborygmi and distended small intestinal loops were detected by auscultation and rectal palpation, respectively. On rectal examination a firm, irregular surface, and pedunculated mass were detected in the middle-caudal region of the abdomen. Transrectal ultrasonography revealed the mass was highly vascularized with heterogeneous tissue density. On exploratory celiotomy two neoplastic masses were observed, one in the jejunoileal junction obstructing the intestinal flow and the second in the dorsal part of the jejunal mesentery, unable to be exposed and resected. An enterectomy was conducted, and the intestinal mass was removed. The mass was pale with hemorrhagic areas and 12 cm in diameter. Histopathology and immunohistochemistry confirmed a diagnosis of enteric associated T cell lymphoma subtype 2. The mule died suddenly 43 days later.
Topics: Female; Animals; Equidae; Lymphoma, T-Cell; Ultrasonography
PubMed: 38527562
DOI: 10.1016/j.jevs.2024.105050 -
American Journal of Hypertension Mar 2024A novel method for estimating central systolic aortic pressure (cSAP) has emerged, relying solely on peripheral mean (MBP) and diastolic (DBP) blood pressures. We aimed...
BACKGROUND
A novel method for estimating central systolic aortic pressure (cSAP) has emerged, relying solely on peripheral mean (MBP) and diastolic (DBP) blood pressures. We aimed to assess the accuracy of this Direct Central Blood Pressure estimation using cuff alone (DCBPcuff=MBP²/DBP) in comparison to the use of generalized transfer function to derive cSAP from radial tonometry (cSAPtono).
METHODS
This retrospective analysis involved International Database of Central Arterial properties for Risk Stratification (IDCARS) data (Aparicio et al., Am J Hypertens 2022). The dataset encompassed 10,930 subjects from 13 longitudinal cohort studies worldwide (54.8%women; median age 46.0 years; office hypertension: 40.1%; treated: 61.0%), documenting cSAPtono via SphygmoCor calibrated against brachial systolic BP (SBP) and DBP. Our analysis focused on aggregate group data from 12/13 studies (89%patients) where full BP dataset was available. A 35% form factor was used to estimate MBP = (DBP+(0.35×(SBP-DBP)), from which DCBPcuff was derived. The predefined acceptable error for cSAPtono estimation was set at ≤5mmHg.
RESULTS
The cSAPtono values ranged 103.8-127.0 mmHg (n=12). The error between DCBPcuff and cSAPtono was 0.2 ± 1.4 mmHg, with no influence of the mean. Errors ranged from -1.8 to 2.9 mmHg across studies. No significant difference in errors was observed between BP measurements obtained via oscillometry (n=9) vs auscultation (n=3) (p=0.50).
CONCLUSIONS
Using published aggregate group data and a 35% form factor, DCBPcuff demonstrated remarkable accuracy in estimating cSAPtono, regardless of the BP measurement technique. However, given that individual BP values were unavailable, further documentation is required to establish DCBPcuff's precision.
PubMed: 38517132
DOI: 10.1093/ajh/hpae039 -
Revista Espanola de Salud Publica Mar 2024Systemic arterial hypertension is the most important modificable risk factor for morbidity and mortality and a Public Health problem. The objective was to estímate... (Observational Study)
Observational Study
OBJECTIVE
Systemic arterial hypertension is the most important modificable risk factor for morbidity and mortality and a Public Health problem. The objective was to estímate ítems of worse quality of life (Qol) in both domains of the MINICHAL questionarie and the associated variables.
METHODS
An observational study of prevalence in men was carried out. Sociodemographic, comorbidity, clinical, examination, control and serum parameters variables were collected. The following questionnaires were applied: MINICHAL, International Physical Activity Questionnaire, International Score of Prostatic Symptomatology and International Index of Erectile Function. Apart from the usual descriptive ones, a bivariate and a multivariate logistic regression were performed, determining Odds Ratio values with a 95% confidence interval.
RESULTS
262 hypertensive patients were analyzed, of which 42% reported worse quality of life in the mental state dimensión compared to 47.3% in the somatic manifestacions dimensión. The multivariate logistic regression analysis showed as outstanding predictor variables: Metabolic Syndrome in the chest pain item without making any effort; the presence of filling symptoms in the item urinate more often; pathological cardiopulmonary auscultation in the item numbness or tingling in some part of the body; the presence of erectile dysfunction in the item difficulty falling asleep.
CONCLUSIONS
All the items of the MINICHAL questionnaire that assess the Somatic Manifestations dimension have a very negative impact on the quality of life of patients, and only the difficulty falling asleep item in the Mental State dimension.
Topics: Male; Humans; Quality of Life; Spain; Hypertension; Comorbidity; Risk Factors; Surveys and Questionnaires
PubMed: 38516938
DOI: No ID Found -
High Altitude Medicine & Biology Jun 2024Lin, Tian, Huaping Jia, Yunming Li, Yongxing Xu, Bei Zhao, Dong Zheng, Hongfeng Yan, Meihui Zhao, Yanlei Li, Liping Xia, Fengxia Zhou, Cuiping Liu, Ke Ma, Ma Mi, and...
Lin, Tian, Huaping Jia, Yunming Li, Yongxing Xu, Bei Zhao, Dong Zheng, Hongfeng Yan, Meihui Zhao, Yanlei Li, Liping Xia, Fengxia Zhou, Cuiping Liu, Ke Ma, Ma Mi, and Jianwen Gu. Epidemiological survey of congenital heart disease among children aged from 2 to 18 in Suo County, Nagqu, Tibet. . 00:000-000, 2024. Studies have reported the prevalence of congenital heart disease (CHD) in parts of Tibet, but relative epidemiological surveys are rare. We aimed to explore the prevalence of CHD in children and its relationship with family history in Suo County, Nagqu, Tibet, an altitude of 3,980 meters. We recruited 4,002 children aged 2-18 years. Subjects underwent a family history investigation, cardiac auscultation, and clinical manifestation examination and then received echocardiographic screening. The prevalence of CHD among children in Suo County was 0.97% (39 cases), much higher than the prevalence at sea level. The most common subtype was atrial septal defect, accounting for 53.9% of CHD, followed by patent ductus arteriosus (33.3%) and ventricular septal defect (12.8%). We also found that children whose mothers had previously borne children with CHD had a higher risk of CHD than those without ( = 0.002); other factors related to CHD during pregnancy, such as smoking, drinking, drug use, and viral infection, showed no statistical differences between children with and without CHD. The prevalence of CHD in children in Suo County is much higher than at low altitude, consisting mostly of simple forms with left-to-right shunt, with rare complex CHD. These results support implementing diagnostic and treatment plans to prevent CHD in Suo County.
Topics: Humans; Tibet; Female; Male; Heart Defects, Congenital; Child; Prevalence; Adolescent; Child, Preschool; Altitude; Risk Factors; Heart Septal Defects, Atrial; Echocardiography
PubMed: 38511279
DOI: 10.1089/ham.2023.0025 -
Clinical and Translational Allergy Mar 2024Guidelines recommend treating asthma exacerbations (AAEs) with bronchodilators combined with inhaled and/or systemic corticosteroids. Indications for antibiotic...
INTRODUCTION
Guidelines recommend treating asthma exacerbations (AAEs) with bronchodilators combined with inhaled and/or systemic corticosteroids. Indications for antibiotic prescriptions for AAEs are usually not incorporated although the literature shows antibiotics are frequently prescribed.
AIM
To investigate the antibiotic prescription rates in AAEs and explore the possible determining factors of those practices.
METHODS
A digital survey was created to determine the antibiotic prescription rates in AAEs and the influencing factors for the prescription practices. The survey was distributed among European academy of allergy and clinical immunology (EAACI) members by mass emailing and through regional/national societies in the Netherlands, Italy, Greece, and Poland. Furthermore, we retrieved local antibiotic prescription rates.
RESULTS
In total, 252 participants completed the survey. Respondents stated that there is a lack of guidelines to prescribe antibiotics in AAEs. The median antibiotic prescription rate in this study was 19% [IQR: 0%-40%] and was significantly different between 4 professions: paediatrics 0% [IQR: 0%-37%], pulmonologists 25% [IQR: 10%-50%], general practitioners 25% [IQR: 0%-50%], and allergologists 17% [IQR: 0%-33%]) (p = 0.046). Additional diagnostic tests were performed in 71.4% of patients before prescription and the most common antibiotic classes prescribed were macrolides (46.0%) and penicillin (42.9%). Important clinical factors for health care providers to prescribe antibiotics were colorised/purulent sputum, abnormal lung sounds during auscultation, fever, and presence of comorbidities.
CONCLUSION
In 19% of patients with AAEs, antibiotics were prescribed in various classes with a broad range among different subspecialities. This study stresses the urgency to compose evidence-based guidelines to aim for more rational antibiotic prescriptions for AAE.
PubMed: 38497844
DOI: 10.1002/clt2.12345 -
International Journal of Cardiology.... Apr 2024Insufficient clinicians' auscultation ability delays the diagnosis and treatment of valvular heart disease (VHD); artificial intelligence provides a solution to...
BACKGROUND
Insufficient clinicians' auscultation ability delays the diagnosis and treatment of valvular heart disease (VHD); artificial intelligence provides a solution to compensate for the insufficiency in auscultation ability by distinguishing between heart murmurs and normal heart sounds. However, whether artificial intelligence can automatically diagnose VHD remains unknown. Our objective was to use deep learning to process and compare raw heart sound data to identify patients with VHD requiring intervention.
METHODS
Heart sounds from patients with VHD and healthy controls were collected using an electronic stethoscope. Echocardiographic findings were used as the gold standard for this study. According to the chronological order of enrollment, the early-enrolled samples were used to train the deep learning model, and the late-enrollment samples were used to validate the results.
RESULTS
The final study population comprised 499 patients (354 in the algorithm training group and 145 in the result validation group). The sensitivity, specificity, and accuracy of the deep-learning model for identifying various VHDs ranged from 71.4 to 100.0%, 83.5-100.0%, and 84.1-100.0%, respectively; the best diagnostic performance was observed for mitral stenosis, with a sensitivity of 100.0% (31.0-100.0%), a specificity of 100% (96.7-100.0%), and an accuracy of 100% (97.5-100.0%).
CONCLUSIONS
Based on raw heart sound data, the deep learning model effectively identifies patients with various types of VHD who require intervention and assists in the screening, diagnosis, and follow-up of VHD.
PubMed: 38482387
DOI: 10.1016/j.ijcha.2024.101368 -
Sensors (Basel, Switzerland) Mar 2024An educational augmented reality auscultation system (EARS) is proposed to enhance the reality of auscultation training using a simulated patient. The conventional EARS...
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.
Topics: Humans; Augmented Reality; Auscultation; Stethoscopes; Respiration; Exhalation; Respiratory Sounds
PubMed: 38475162
DOI: 10.3390/s24051626 -
Sensors (Basel, Switzerland) Feb 2024Cardiac auscultation is an essential part of physical examination and plays a key role in the early diagnosis of many cardiovascular diseases. The analysis of...
Cardiac auscultation is an essential part of physical examination and plays a key role in the early diagnosis of many cardiovascular diseases. The analysis of phonocardiography (PCG) recordings is generally based on the recognition of the main heart sounds, i.e., S1 and S2, which is not a trivial task. This study proposes a method for an accurate recognition and localization of heart sounds in Forcecardiography (FCG) recordings. FCG is a novel technique able to measure subsonic vibrations and sounds via small force sensors placed onto a subject's thorax, allowing continuous cardio-respiratory monitoring. In this study, a template-matching technique based on normalized cross-correlation was used to automatically recognize heart sounds in FCG signals recorded from six healthy subjects at rest. Distinct templates were manually selected from each FCG recording and used to separately localize S1 and S2 sounds, as well as S1-S2 pairs. A simultaneously recorded electrocardiography (ECG) trace was used for performance evaluation. The results show that the template matching approach proved capable of separately classifying S1 and S2 sounds in more than 96% of all heartbeats. Linear regression, correlation, and Bland-Altman analyses showed that inter-beat intervals were estimated with high accuracy. Indeed, the estimation error was confined within 10 ms, with negligible impact on heart rate estimation. Heart rate variability (HRV) indices were also computed and turned out to be almost comparable with those obtained from ECG. The preliminary yet encouraging results of this study suggest that the template matching approach based on normalized cross-correlation allows very accurate heart sounds localization and inter-beat intervals estimation.
Topics: Humans; Heart Sounds; Phonocardiography; Heart; Heart Auscultation; Electrocardiography; Heart Rate
PubMed: 38475062
DOI: 10.3390/s24051525 -
Health Information Science and Systems Dec 2024The utilization of lung sounds to diagnose lung diseases using respiratory sound features has significantly increased in the past few years. The Digital Stethoscope data...
Artificial intelligence-based framework to identify the abnormalities in the COVID-19 disease and other common respiratory diseases from digital stethoscope data using deep CNN.
The utilization of lung sounds to diagnose lung diseases using respiratory sound features has significantly increased in the past few years. The Digital Stethoscope data has been examined extensively by medical researchers and technical scientists to diagnose the symptoms of respiratory diseases. Artificial intelligence-based approaches are applied in the real universe to distinguish respiratory disease signs from human pulmonary auscultation sounds. The Deep CNN model is implemented with combined multi-feature channels (Modified MFCC, Log Mel, and Soft Mel) to obtain the sound parameters from lung-based Digital Stethoscope data. The model analysis is observed with max-pooling and without max-pool operations using multi-feature channels on respiratory digital stethoscope data. In addition, COVID-19 sound data and enriched data, which are recently acquired data to enhance model performance using a combination of L2 regularization to overcome the risk of overfitting because of less respiratory sound data, are included in the work. The suggested DCNN with Max-Pooling on the improved dataset demonstrates cutting-edge performance employing a multi-feature channels spectrogram. The model has been developed with different convolutional filter sizes (, , , , and ) that helped to test the proposed neural network. According to the experimental findings, the suggested DCNN architecture with a max-pooling function performs better to identify respiratory disease symptoms than DCNN without max-pooling. In order to demonstrate the model's effectiveness in categorization, it is trained and tested with the DCNN model that extract several modalities of respiratory sound data.
PubMed: 38469455
DOI: 10.1007/s13755-024-00283-w -
Blood Pressure Monitoring Aug 2024Understanding of how oscillometric waveforms (OMW) vary between pregnant and nonpregnant individuals remains low. An exploratory analysis was completed to assess for... (Comparative Study)
Comparative Study Clinical Trial
OBJECTIVE
Understanding of how oscillometric waveforms (OMW) vary between pregnant and nonpregnant individuals remains low. An exploratory analysis was completed to assess for quantitative and qualitative changes in OMW and oscillometric envelope features in pregnancy.
DESIGN AND METHODS
Eighteen pregnant individuals (over 20 weeks gestational age) and healthy, nonpregnant (HNP) women were recruited. Six HNP were matched to six healthy pregnant (HP) women, and six pregnant women with a hypertensive disorder of pregnancy (HDP) by age, arm circumference, and cuff size. Blood pressure measurements were completed per the International Organization for Standardization (ISO) protocol using a custom-built oscillometric device as the test device and two-observer mercury auscultation as the reference measurement. Auscultatory blood pressure and blood pressure derived from slope-based and fixed ratio algorithms were determined. OMW and envelope features were compared among groups.
RESULTS
In HNP, HP, and HDP groups respectively: mean auscultatory blood pressure (systolic mean ± SD/diastolic mean ± SD) was 103.4 ± 12.2/67.1 ± 7.9; 109.5 ± 3.1/58.1 ± 6.4; 135.6 ± 18.9/85.1 ± 14.2 mmHg. HDP had significantly higher auscultatory systolic and diastolic blood pressure than the HP group ( P = 0.001). The pregnant groups had a lower average pulse width (mean ± SD: HNP = 0.8 ± 0 s, HP = 0.6 ± 0.1 s, HDP = 0.6 ± 0.1 s; HP vs. HNP mean difference [adjusted P value]: 0.2 [ P = 0.004], HDP vs. HNP 0.1 [ P = 0.018]) compared with the HNP group. The HDP group had a larger area under the OMW envelope than the HNP group (mean ± SD: HNP = 22.6 ± 3.4; HDP = 28.5 ± 4.2; HDP vs. HNP mean difference [adjusted P value]: 5.9 P = 0.05).
CONCLUSION
In this exploratory work, differences in the OMW morphology and parameters were found in pregnancy and in hypertensive disorders of pregnancy compared with healthy controls. Even small differences may have important implications in algorithm development; further work comparing OMW envelopes in pregnancy is needed to optimize the algorithms used to determine blood pressure in pregnancy.
Topics: Humans; Female; Pregnancy; Adult; Hypertension, Pregnancy-Induced; Oscillometry; Blood Pressure; Blood Pressure Determination
PubMed: 38465772
DOI: 10.1097/MBP.0000000000000700