scholarly journals Wheezing Characteristics and Predicting Reactivity to Inhaled β2-Agonist in Children for Home Medical Care

2021 ◽  
Vol 9 ◽  
Author(s):  
Chizu Habukawa ◽  
Naoto Ohgami ◽  
Takahiro Arai ◽  
Haruyuki Makata ◽  
Tomoki Nishikido ◽  
...  
Keyword(s):  
Lung Sounds ◽  
Lung Sound ◽  
Tidal Breathing ◽  
Sound Analysis ◽  
Predictive Values ◽  
Before And After ◽  
Number Frequency ◽  
Sensitivity Specificity ◽  
Β2 Agonist ◽  
Β2 Agonists

Background: Given that wheezing is treated with inhaled β2-agonists, their effect should be reviewed before the condition becomes severe; however, few methods can currently predict reactivity to inhaled β2-agonists. We investigated whether preinhalation wheezing characteristics identified by lung sound analysis can predict reactivity to inhaled β2-agonists.Methods: In 202 children aged 10–153 months, wheezing was identified by auscultation. Lung sounds were recorded for 30 s in the chest region on the chest wall during tidal breathing. We analyzed the wheezing before and after β2-agonist inhalation. Wheezing was displayed as horizontal bars of intensity defined as a wheeze power band, and the wheezing characteristics (number, frequency, and maximum intensity frequency) were evaluated by lung sound analysis. The participants were divided into two groups: non-disappears (wheezing did not disappear after inhalation) and disappears (wheezing disappeared after inhalation). Wheezing characteristics before β2-agonist inhalation were compared between the two groups.The characteristics of wheezing were not affected by body size. The number of wheeze power bands of the non-responder group was significantly higher than those of the responder group (P < 0.001). The number of wheeze power bands was a predictor of reactivity to inhaled β2-agonists, with a cutoff of 11.1. The 95% confidence intervals of sensitivity, specificity, and positive and negative predictive values were 88.8, 42, 44, and 81.1% (P < 0.001), respectively.Conclusions: The number of preinhalation wheeze power bands shown by lung sound analysis was a useful indicator before treatment. This indicator could be a beneficial index for managing wheezing in young children.

scholarly journals Computerized lung sound analysis as diagnostic aid for the detection of abnormal lung sounds: A systematic review and meta-analysis

2011 ◽  
Vol 105 (9) ◽  
pp. 1396-1403 ◽  
Author(s):  
Arati Gurung ◽  
Carolyn G. Scrafford ◽  
James M. Tielsch ◽  
Orin S. Levine ◽  
William Checkley
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Lung Sounds ◽  
Lung Sound ◽  
Diagnostic Aid ◽  
Sound Analysis

Validation of the LEOSound Cough Detection Algorithm

2019 ◽  
Author(s):  
Volker Gross ◽  
Patrick Fischer ◽  
Andreas Weissflog ◽  
Olaf Hildebrandt ◽  
Ulrich Koehler ◽  
...  
Keyword(s):  
Respiratory Symptom ◽  
Contingency Table ◽  
Detection Algorithm ◽  
Monitoring Systems ◽  
Lung Sound ◽  
Predictive Values ◽  
Reliable Detection ◽  
Movement Artifacts ◽  
Sensitivity Specificity ◽  
Lung Sound Monitoring

Abstract Background Cough is an important respiratory symptom being of great interest to many researchers. Up to now, most knowledge about cough has been collected through standardized questionnaires. Objective, and reliable detection of cough assessed by automated lung sound monitoring are becoming increasingly important. The aim of this study is to validate the LEOSound lung sound monitor by using previously determined and investigated COPD datasets (1,2). Methods Based on multiple recordings of 48 patients with stable COPD II-IV, we validated the cough detection algorithm of LEOSound by using a contingency table. Sensitivity, specificity, positive and negative predictive values were used as quantitative measures. Results We found the overall accuracy to be 87.3% with sensitivity and specificity of 98.7% and 80.2%, respectively. Major reasons for midsections in descending order were throat cleaning, snoring and movement artifacts. Conclusion In comparison to other full-automated cough monitoring systems, the LEOSound performs the best in sensitivity, but shows slightly poor specificity. Misdetections were mainly caused due to morphological similar noises and can be withdrawn while scanning through the recording manually.

scholarly journals Clinical Performance of the Spot Vision Photo Screener before and after Induction of Cycloplegia in Children

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Konuralp Yakar
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Clinical Performance ◽  
High Specificity ◽  
Screening Criteria ◽  
Predictive Values ◽  
Before And After ◽  
Sensitivity Specificity ◽  
Vision Screener

Aim. To compare the clinical performance of the Spot Vision Screener used to detect amblyopia risk factors (ARFs) in children before and after induction of cycloplegia; the children were referred because they met the screening criteria of the American Association for Pediatric Ophthalmology and Strabismus (AAPOS). Methods. The Spot Vision Screener and a standard autorefractometer were used to examine 200 eyes of 100 children aged 3–10 years, before and after cycloplegia induction, in terms of ARFs. Sensitivity, specificity, and positive and negative predictive values for the detection of significant refractive errors were measured using the AAPOS referral criteria. It was explored that Spot Screener data were affected by cycloplegia. The extent of agreement between cycloplegic/noncycloplegic photoscreening data and cycloplegic autorefraction measurements was assessed using Wilcoxon and Spearman correlation analyses. Results. The Spot’s sensitivity was improved from 60.9% to 85.3% and specificity from 94.9% to 87.4% with cycloplegia compared to cycloplegic standard autorefractometer results. The positive predictive value of Spot was 75.7%, and the negative predictive value was 90.4% without cycloplegia. With cycloplegia, the positive predictive value of Spot was 63.6% and the negative predictive value was 95.8%. Conclusions. The Spot Screener afforded moderate sensitivity and high specificity prior to cycloplegia. The sensitivity and negative predictive value improved after induction of cycloplegia. Examiners should be aware of the effects of cycloplegia on their findings.

Abstract 154: Acute Stroke Recognition by Paramedics after Regionalization of Stroke Care: Outcomes Based Study

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Prasanthi Govindarajan ◽  
David Ghilarducci ◽  
Steve Shiboski ◽  
Barbara Grimes ◽  
Larry Cook ◽  
...  
Keyword(s):  
Demographic Data ◽  
Patient Discharge ◽  
Stroke Care ◽  
Primary Diagnosis ◽  
Cross Sectional ◽  
Discharge Data ◽  
Predictive Values ◽  
Implementation Phase ◽  
Before And After ◽  
Sensitivity Specificity

Background: Early evidence supports preferential transport of patients with stroke symptoms to primary stroke centers. While validated stroke tools exist for screening of stroke symptoms in the prehospital setting, system wide triage performance of prehospital providers in a regionalized system has not been reported. The objective of this study is to assess the diagnostic ability of prehospital providers, before and after regionalization of care, using outcomes based approach. Methods: This is a cross-sectional study of all patients who were transported to hospitals in two Northern California counties by providers of a single EMS agency during a three year period. One county remained non-regionalized (NR) during the study period and the other initiated and completed regionalization(R) of the system during the study period. Patient demographic data, prehospital provider clinical assessment was obtained from the computerized prehospital transport records and physician diagnosis was obtained from statewide administrative patient discharge data. The data sources were linked using probabilistic linkage methodology. Patients ≥18 years of age with validated ICD- 9 code for stroke were included. We excluded inter-facility transports and direct admissions. Sensitivity, specificity and predictive values for were determined before and after implementation of regionalization. Data analysis was performed using SAS version 9.2. Results: The total number of medical related EMS transports for 3 years was 310,731 and the number of patient discharges with a primary diagnosis of stroke was 10,298. We were able to link 3736 stroke records which indicate EMS use by 36% (3736/10,298) stroke patients. The sensitivity, specificity, PPV and NPV in the pre-regionalization phase was 28%, 80%, 53%, 58% and during the implementation phase of regionalization was 39% 78%,57% and 63% (p <0.05). The performance in the NR County during the entire period was 23%, 76%, 40% and 58%. Conclusions: Diagnostic accuracy remained low although improved prehospital provider performance was observed after regionalization of stroke care.

scholarly journals Lung sounds in bronchial asthma

2021 ◽  
Vol 9 (7) ◽  
Author(s):  
Yukio Nagasaka ◽  
Michiko Tsuchiya
Keyword(s):  
Lung Function ◽  
Bronchial Asthma ◽  
Sound Intensity ◽  
Common Finding ◽  
Lung Sounds ◽  
Lung Sound ◽  
Sound Analysis ◽  
Airway Narrowing ◽  
Breath Sounds ◽  
Historical Article

Since the historical article by Forgacs in 1978, many studies have clarified the changes of lung sounds due to airway narrowing as well as the mechanism of genesis of these sounds. Studies using bronchoprovocation have shown that an increase of the frequency and/or intensity of lung sounds was a common finding of airway narrowing and correlated well with lung function in bronchial asthma. Bronchoprovocation studies also showed that wheezing may not be as sensitive as changes in basic lung sounds in acute airway narrowing in adult asthmatics. In lung sound analysis, narrow airways cause an increase in the frequency of breath sounds and lung sound intensity, implying when the patient has higher than normal breath sounds, i.e., bronchial sounds, he or she may have airway narrowing. Recent studies reported that this increase of breath sounds suggested worsening of airway inflammation in rather stable patients with bronchial asthma. As it is difficult to detect subtle changes in lung sounds by auscultation alone, automated sound analysis will be expected.

Limitations in the use of median frequency for lung sound analysis

2000 ◽  
Vol 214 (3) ◽  
pp. 265-275 ◽  
Author(s):  
A R Whittaker ◽  
M Lucas ◽  
R Carter ◽  
K Anderson
Keyword(s):  
Air Flow ◽  
Measurement Techniques ◽  
High Sensitivity ◽  
Forced Expiratory Volume ◽  
Median Frequency ◽  
Lung Sounds ◽  
Lung Sound ◽  
Flow Measurements ◽  
Sound Analysis ◽  
Lung Condition

The aim of this paper is to investigate methods of standardizing lung sound analysis, with a view to supplementing traditional spirometric air flow measurements to help in the diagnosis of asthma and to provide a measure of the effectiveness of treatment. Lung sounds were measured in nine patients with asthma and five control subjects, alongside air flow measurements of forced expiratory volume (FEV1) and forced vital capacity (FVC). The patients were administered the broncho-dilator, salbutamol, to assess how effective these measurement techniques were for quantifying its effect. The results agree with previous studies, that analysis of lung sounds is a potentially useful tool for indicating air flow changes. The results, however, also demonstrate that the emerging standard of ‘F50’ or ‘median frequency’ should be treated with great caution because of its high sensitivity to the measurement frequency range. F50 is very unlikely to provide a reliable single indicator of lung condition.

Discriminating Malignancy in Thyroid Nodules: The Nomogram Versus the Kwak and ACR TI-RADS

2020 ◽  
Vol 163 (6) ◽  
pp. 1156-1165
Author(s):  
Juan Xiao ◽  
Qiang Xiao ◽  
Wei Cong ◽  
Ting Li ◽  
Shouluan Ding ◽  
...  
Keyword(s):  
Thyroid Nodules ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Diagnostic Study ◽  
Diagnostic Efficiency ◽  
Training Set ◽  
Multivariable Logistic Regression Model ◽  
Predictive Values ◽  
Validation Set ◽  
Sensitivity Specificity

Objective To develop an easy-to-use nomogram for discrimination of malignant thyroid nodules and to compare diagnostic efficiency with the Kwak and American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS). Study Design Retrospective diagnostic study. Setting The Second Hospital of Shandong University. Subjects and Methods From March 2017 to April 2019, 792 patients with 1940 thyroid nodules were included into the training set; from May 2019 to December 2019, 174 patients with 389 nodules were included into the validation set. Multivariable logistic regression model was used to develop a nomogram for discriminating malignant nodules. To compare the diagnostic performance of the nomogram with the Kwak and ACR TI-RADS, the area under the receiver operating characteristic curve, sensitivity, specificity, and positive and negative predictive values were calculated. Results The nomogram consisted of 7 factors: composition, orientation, echogenicity, border, margin, extrathyroidal extension, and calcification. In the training set, for all nodules, the area under the curve (AUC) for the nomogram was 0.844, which was higher than the Kwak TI-RADS (0.826, P = .008) and the ACR TI-RADS (0.810, P < .001). For the 822 nodules >1 cm, the AUC of the nomogram was 0.891, which was higher than the Kwak TI-RADS (0.852, P < .001) and the ACR TI-RADS (0.853, P < .001). In the validation set, the AUC of the nomogram was also higher than the Kwak and ACR TI-RADS ( P < .05), each in the whole series and separately for nodules >1 or ≤1 cm. Conclusions When compared with the Kwak and ACR TI-RADS, the nomogram had a better performance in discriminating malignant thyroid nodules.

scholarly journals The Impact of Narrow-band Imaging on the Pre- and Intra- operative Assessments of Neoplastic and Preneoplastic Laryngeal Lesions. A Systematic Review

2020 ◽  
Author(s):  
Carmelo Saraniti ◽  
Enzo Chianetta ◽  
Giuseppe Greco ◽  
Norhafiza Mat Lazim ◽  
Barbara Verro
Keyword(s):  
White Light ◽  
Diagnostic Tool ◽  
Narrow Band ◽  
Narrow Band Imaging ◽  
Resection Margins ◽  
Predictive Values ◽  
White Light Endoscopy ◽  
Laryngeal Lesions ◽  
Sensitivity Specificity ◽  
The Impact

Introduction Narrow-band imaging is an endoscopic diagnostic tool that, focusing on superficial vascular changes, is useful to detect suspicious laryngeal lesions, enabling their complete excision with safe and tailored resection margins. Objectives To analyze the applications and benefits of narrow-band imaging in detecting premalignant and malignant laryngeal lesions through a comparison with white-light endoscopy. Data Synthesis A literature search was performed in the PubMed, Scopus and Web of Science databases using strict keywords. Then, two authors independently analyzed the articles, read the titles and abstracts, and read completely only the relevant studies according to certain eligibility criteria. In total, 14 articles have been included in the present review; the sensitivity, specificity, positive and negative predictive values, and accuracy of pre- and/or intraoperative narrow-band imaging were analyzed. The analysis showed that narrow-band imaging is better than white-light endoscopy in terms of sensitivity, specificity, positive and negative predictive values, and accuracy regarding the ability to identify cancer and/or precancerous laryngeal lesions. Moreover, the intraoperative performance of narrow-band imaging resulted more effective than the in-office performance. Conclusion Narrow-band imaging is an effective diagnostic tool to detect premalignant and malignant laryngeal lesions and to define proper resection margins. Moreover, narrow-band imaging is useful in cases of leukoplakia that may cover a possible malignant lesion and that cannot be easily assessed with white-light endoscopy. Finally, a shared, simple and practical classification of laryngeal lesions, such as that of the European Laryngological Society, is required to identify a shared lesion management strategy. Key Points

scholarly journals Predicting youth diabetes risk using NHANES data and machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nita Vangeepuram ◽  
Bian Liu ◽  
Po-hsiang Chiu ◽  
Linhua Wang ◽  
Gaurav Pandey
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Clinical Guideline ◽  
Diabetes Risk ◽  
Screening Tools ◽  
Clinical Screening ◽  
Predictive Values ◽  
Screening Guideline ◽  
Demographic Subgroups ◽  
Sensitivity Specificity

AbstractPrediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step in developing such a tool, we used a large-scale dataset from the National Health and Nutritional Examination Survey (NHANES) to examine the performance of a published pediatric clinical screening guideline in identifying youth with preDM/DM based on American Diabetes Association diagnostic biomarkers. We assessed the agreement between the clinical guideline and biomarker criteria using established evaluation measures (sensitivity, specificity, positive/negative predictive value, F-measure for the positive/negative preDM/DM classes, and Kappa). We also compared the performance of the guideline to those of machine learning (ML) based preDM/DM classifiers derived from the NHANES dataset. Approximately 29% of the 2858 youth in our study population had preDM/DM based on biomarker criteria. The clinical guideline had a sensitivity of 43.1% and specificity of 67.6%, positive/negative predictive values of 35.2%/74.5%, positive/negative F-measures of 38.8%/70.9%, and Kappa of 0.1 (95%CI: 0.06–0.14). The performance of the guideline varied across demographic subgroups. Some ML-based classifiers performed comparably to or better than the screening guideline, especially in identifying preDM/DM youth (p = 5.23 × 10−5).We demonstrated that a recommended pediatric clinical screening guideline did not perform well in identifying preDM/DM status among youth. Additional work is needed to develop a simple yet accurate screener for youth diabetes risk, potentially by using advanced ML methods and a wider range of clinical and behavioral health data.

Sign in / Sign up

Export Citation Format

Share Document