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The diagnosis of respiratory disease in children using a phone-based cough and symptom analysis algorithm: The smartphone recordings of cough sounds 2 (SMARTCOUGH-C 2) trial design.基于电话的咳嗽和症状分析算法诊断儿童呼吸疾病：智能手机记录咳嗽声音 2（SMARTCOUGH-C 2）试验设计。
Contemp Clin Trials. 2021 Feb;101:106278. doi: 10.1016/j.cct.2021.106278. Epub 2021 Jan 12.
2
Development and technical validation of a smartphone-based pediatric cough detection algorithm.基于智能手机的小儿咳嗽检测算法的开发和技术验证。
Pediatr Pulmonol. 2022 Mar;57(3):761-767. doi: 10.1002/ppul.25801. Epub 2022 Jan 11.
3
A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centred analytic system for the identification of common respiratory disorders in children.一项前瞻性多中心研究，旨在测试一种以咳嗽声为中心的自动分析系统在识别儿童常见呼吸道疾病方面的诊断准确性。
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Can Acute Cough Characteristics From Sound Recordings Differentiate Common Respiratory Illnesses in Children?: A Comparative Prospective Study.从录音中能否分辨出儿童常见呼吸道疾病的急性咳嗽特征？一项比较性前瞻性研究。
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Diagnosing community-acquired pneumonia via a smartphone-based algorithm: a prospective cohort study in primary and acute-care consultations.通过基于智能手机的算法诊断社区获得性肺炎：在初级和急性护理会诊中的一项前瞻性队列研究
Br J Gen Pract. 2021 Mar 26;71(705):e258-e265. doi: 10.3399/BJGP.2020.0750. Print 2021 Apr.
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Detecting acute respiratory diseases in the pediatric population using cough sound features and machine learning: A systematic review.利用咳嗽声特征和机器学习技术检测儿科急性呼吸道疾病：系统综述。
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A smartphone-based algorithm comprising cough analysis and patient-reported symptoms identifies acute exacerbations of asthma: a prospective, double blind, diagnostic accuracy study.基于智能手机的算法，包含咳嗽分析和患者报告症状，可识别哮喘急性加重：一项前瞻性、双盲、诊断准确性研究。
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Cough sound analysis can rapidly diagnose childhood pneumonia.咳嗽声分析可快速诊断儿童肺炎。
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A signal processing approach for the diagnosis of asthma from cough sounds.一种基于咳嗽声音诊断哮喘的信号处理方法。
J Med Eng Technol. 2013 Apr;37(3):165-71. doi: 10.3109/03091902.2012.758322.

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Identifying unique spectral fingerprints in cough sounds for diagnosing respiratory ailments.识别咳嗽声中的独特光谱特征，用于诊断呼吸疾病。
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Drug resistant tuberculosis: Implications for transmission, diagnosis, and disease management.耐药结核病：传播、诊断和疾病管理的影响。
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Making cough count in tuberculosis care.重视咳嗽在结核病治疗中的作用。
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A deep-learning based multimodal system for Covid-19 diagnosis using breathing sounds and chest X-ray images.一种基于深度学习的多模态系统，用于利用呼吸声和胸部X光图像诊断新冠肺炎。
Appl Soft Comput. 2021 Sep;109:107522. doi: 10.1016/j.asoc.2021.107522. Epub 2021 May 26.
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End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework.基于端到端人工智能的即时护理诊断系统，用于呼吸道疾病分类和COVID-19早期检测：一个理论框架
Front Med (Lausanne). 2021 Mar 31;8:585578. doi: 10.3389/fmed.2021.585578. eCollection 2021.

本文引用的文献

1
Diagnosing Chronic Obstructive Airway Disease on a Smartphone Using Patient-Reported Symptoms and Cough Analysis: Diagnostic Accuracy Study.使用患者报告症状和咳嗽分析通过智能手机诊断慢性阻塞性气道疾病：诊断准确性研究
JMIR Form Res. 2020 Nov 10;4(11):e24587. doi: 10.2196/24587.
2
An analysis of clinical predictive values for radiographic pneumonia in children.儿童放射学肺炎的临床预测值分析。
BMJ Glob Health. 2020 Aug;5(8). doi: 10.1136/bmjgh-2020-002708.
3
Time to Say Goodbye to Bronchiolitis, Viral Wheeze, Reactive Airways Disease, Wheeze Bronchitis and All That.是时候告别细支气管炎、病毒性喘息、反应性气道疾病、喘息性支气管炎等等了。
Front Pediatr. 2020 May 5;8:218. doi: 10.3389/fped.2020.00218. eCollection 2020.
4
Effects of high altitude on respiratory rate and oxygen saturation reference values in healthy infants and children younger than 2 years in four countries: a cross-sectional study.高海拔地区对四个国家 2 岁以下健康婴儿和儿童呼吸频率及血氧饱和度参考值的影响：一项横断面研究。
Lancet Glob Health. 2020 Mar;8(3):e362-e373. doi: 10.1016/S2214-109X(19)30543-1.
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The radiological diagnosis of pneumonia in children.儿童肺炎的放射学诊断
Pneumonia (Nathan). 2014 Dec 1;5(Suppl 1):38-51. doi: 10.15172/pneu.2014.5/482. eCollection 2014.
6
Stratifying asthma severity in children using cough sound analytic technology.利用咳嗽声分析技术对儿童哮喘严重程度进行分层。
J Asthma. 2021 Feb;58(2):160-169. doi: 10.1080/02770903.2019.1684516. Epub 2019 Nov 25.
7
A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centred analytic system for the identification of common respiratory disorders in children.一项前瞻性多中心研究，旨在测试一种以咳嗽声为中心的自动分析系统在识别儿童常见呼吸道疾病方面的诊断准确性。
Respir Res. 2019 Jun 6;20(1):81. doi: 10.1186/s12931-019-1046-6.
8
Antibiotic Prescribing During Pediatric Direct-to-Consumer Telemedicine Visits.儿科直接面向消费者的远程医疗就诊期间的抗生素处方。
Pediatrics. 2019 May;143(5). doi: 10.1542/peds.2018-2491. Epub 2019 Apr 8.
9
Global, regional, and national estimates of pneumonia morbidity and mortality in children younger than 5 years between 2000 and 2015: a systematic analysis.全球、区域和国家层面 2000 至 2015 年 5 岁以下儿童肺炎发病率和死亡率的系统分析。
Lancet Glob Health. 2019 Jan;7(1):e47-e57. doi: 10.1016/S2214-109X(18)30408-X. Epub 2018 Nov 26.
10
Predicting spirometry readings using cough sound features and regression.使用咳嗽声音特征和回归预测肺活量读数。
Physiol Meas. 2018 Sep 5;39(9):095001. doi: 10.1088/1361-6579/aad948.

基于电话的咳嗽和症状分析算法诊断儿童呼吸疾病：智能手机记录咳嗽声音 2（SMARTCOUGH-C 2）试验设计。

The diagnosis of respiratory disease in children using a phone-based cough and symptom analysis algorithm: The smartphone recordings of cough sounds 2 (SMARTCOUGH-C 2) trial design.

机构信息

Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.

Texas Children's Hospital and Baylor College of Medicine, Houston, TX, USA.

出版信息

Contemp Clin Trials. 2021 Feb;101:106278. doi: 10.1016/j.cct.2021.106278. Epub 2021 Jan 12.

DOI:10.1016/j.cct.2021.106278
PMID:33444779
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7990113/
Abstract

The diagnosis of acute respiratory diseases in children can be challenging, and no single objective diagnostic test exists for common pediatric respiratory diseases. Previous research has demonstrated that ResAppDx, a cough sound and symptom-based analysis algorithm, can identify common respiratory diseases at the point of care. We present the study protocol for SMARTCOUGH-C 2, a prospective diagnostic accuracy trial of a cough and symptom-based algorithm in a cohort of children presenting with acute respiratory diseases. The objective of the study is to assess the performance characteristics of the ResAppDx algorithm in the diagnosis of common pediatric acute respiratory diseases.

摘要

儿童急性呼吸道疾病的诊断具有一定挑战性，目前还没有针对常见儿科呼吸道疾病的单一客观诊断测试。既往研究表明，ResAppDx 是一种基于咳嗽声音和症状的分析算法，可在护理点识别常见的呼吸道疾病。我们介绍了 SMARTCOUGH-C2 的研究方案，这是一项针对基于咳嗽和症状的算法在急性呼吸道疾病患儿中的前瞻性诊断准确性试验。该研究的目的是评估 ResAppDx 算法在诊断常见儿科急性呼吸道疾病方面的性能特征。