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A wheeze recognition algorithm for practical implementation in children.

ABSTRACT: BACKGROUND:The detection of wheezes as an exacerbation sign is important in certain respiratory diseases. However, few highly accurate clinical methods are available for automatic detection of wheezes in children. This study aimed to develop a wheeze detection algorithm for practical implementation in children. METHODS:A wheeze recognition algorithm was developed based on wheezes features following the Computerized Respiratory Sound Analysis guidelines. Wheezes can be detected by auscultation with a stethoscope and using an automatic computerized lung sound analysis. Lung sounds were recorded for 30 s in 214 children aged 2 months to 12 years and 11 months in a pediatric consultation room. Files containing recorded lung sounds were assessed by two specialist physicians and divided into two groups: 65 were designated as "wheeze" files, and 149 were designated as "no-wheeze" files. All lung sound judgments were agreed between two specialist physicians. We compared wheeze recognition between the specialist physicians and using the wheeze recognition algorithm and calculated the sensitivity, specificity, positive predictive value, and negative predictive value for all recorded sound files to evaluate the influence of age on the wheeze detection sensitivity. RESULTS:The detection of wheezes was not influenced by age. In all files, wheezes were differentiated from noise using the wheeze recognition algorithm. The sensitivity, specificity, positive predictive value, and negative predictive value of the wheeze recognition algorithm were 100%, 95.7%, 90.3%, and 100%, respectively. CONCLUSIONS:The wheeze recognition algorithm could identify wheezes in sound files and therefore may be useful in the practical implementation of respiratory illness management at home using properly developed devices.

SUBMITTER: Habukawa C

PROVIDER: S-EPMC7544038 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A wheeze recognition algorithm for practical implementation in children.

Habukawa Chizu C Ohgami Naoto N Matsumoto Naoki N Hashino Kenji K Asai Kei K Sato Tetsuya T Murakami Katsumi K

PloS one 20201008 10

<h4>Background</h4>The detection of wheezes as an exacerbation sign is important in certain respiratory diseases. However, few highly accurate clinical methods are available for automatic detection of wheezes in children. This study aimed to develop a wheeze detection algorithm for practical implementation in children.<h4>Methods</h4>A wheeze recognition algorithm was developed based on wheezes features following the Computerized Respiratory Sound Analysis guidelines. Wheezes can be detected by ...[more]

PMID: 33031408

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Project description:Asthma is an inflammatory disease of the airways characterised by episodic airway obstruction resulting in cough, episodic shortness of breath. It is, and is clinically and physiologically heterogeneous. It is estimated that around 300 million people worldwide have the diseaseare diagnosed with asthma, including up to 20% of children (Asher et al, 2006), with 5–10% of these children believed to have severe or difficult-to-treat asthma. Asthma has often been classified in terms of severity and based on clinical diagnostic criteria, but it is now apparent that the heterogeneity that exists at the physiological level is also a feature of the underlying pathological mechanisms (Lotvall et al, 2011). The aim of this study was to identify blood transcriptomics profiles for children diagnosed with asthma or wheeze, and establish whether these profiles suggested endotypes or mechanisms that could underlie disease, or be related to disease severity, in these children. Importantly, given that children are currently treated with the same medicines as adults, we also aimed to compare profiles of children to those of adults with asthma to help determine whether efforts should be directed to the development of medicines targeting pathways and mechanisms that may be unique to children. To this end, we used gene transcriptome data generated from blood samples from adults and children from the U-BIOPRED consortium to ask how similar or different the differential gene expression profiles were between groups of adults and pre-school or school-aged children with severe or mild-moderate asthma (or wheeze for the pre-school aged children) using current definitions. The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project was set up as a public-private partnership within the framework of the Innovative Medicines Initiative (IMI), engaging academia, the pharmaceutical industry and patient groups. The goal of this investigation was to identify transcript fingerprints in whole blood that characterize patients with severe asthma and to determine whether subgroups of severe asthmatics can be identified.

Project description:BackgroundBronchiolitis is a common acute respiratory condition with high prevalence worldwide. This clinically diagnosed syndrome is manifested by tachypnoea (rapid breathing), with crackles or wheeze in young children. In the acute phase of bronchiolitis (≤ 14 days), antibiotics are not routinely prescribed unless the illness is severe or a secondary bacterial infection is suspected. Although bronchiolitis is usually self-limiting, some young children continue to have protracted symptoms (e.g. cough and wheezing) beyond the acute phase and often re-present to secondary care.ObjectivesTo compare the effectiveness of antibiotics versus controls (placebo or no treatment) for reducing or treating persistent respiratory symptoms following acute bronchiolitis within six months of acute illness.Search methodsWe searched the following databases: the Cochrane Airways Group Register of Trials, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid), Embase (Ovid), the World Health Organization (WHO) trial portal, the Australian and New Zealand Clinical Trials Registry, and ClinicalTrials.gov, up to 26 August 2016.Selection criteriaWe included randomised controlled trials (RCTs) comparing antibiotics versus controls (placebo or no treatment) given in the post-acute phase of bronchiolitis (> 14 days) for children younger than two years with a diagnosis of bronchiolitis.Data collection and analysisTwo review authors independently assessed studies against predefined criteria, and selected, extracted, and assessed data for inclusion. We contacted trial authors for further information.Main resultsIn this review update, we added one study with 219 children. A total of two RCTs with 249 children (n = 240 completed) were eligible for inclusion in this review. Both studies contributed to our primary and secondary outcomes, but we assessed the quality of evidence for our three primary outcomes as low, owing to the small numbers of studies and participants; and high attrition in one of the studies. Data show no significant differences between treatment groups for our primary outcomes: proportion of children (n = 249) who had persistent symptoms at follow-up (odds ratio (OR) 0.69, 95% confidence interval (CI) 0.37 to 1.28; fixed-effect model); and number of children (n = 240) rehospitalised with respiratory illness within six months (OR 0.54, 95% CI 0.05 to 6.21; random-effects model). We were unable to analyse exacerbation rate because studies used different methods to report this information. Data showed no significant differences between treatment groups for our secondary outcome: proportion of children (n = 240) with wheeze at six months (OR 0.47, 95% CI 0.06 to 3.95; random-effects model). One study reported bacterial resistance, but only at 48 hours (thus with limited applicability for this review). Another study reported adverse events from which all children recovered and remained in the study.Authors' conclusionsCurrent evidence is insufficient to inform whether antibiotics should be used to treat or prevent persistent respiratory symptoms in the post-acute bronchiolitis phase. Future RCTs are needed to evaluate the efficacy of antibiotics for reducing persistent respiratory symptoms. This is particularly important in populations with high acute and post-acute bronchiolitis morbidity (e.g. indigenous populations in Australia, New Zealand, and the USA).

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A wheeze recognition algorithm for practical implementation in children.

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A wheeze recognition algorithm for practical implementation in children.

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