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.
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。
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