Wheezing Diagnosis Using a Smartphone (WheezSmart)

Wheezing Diagnosis Using a Smartphone in Infants Referred for Bronchiolitis

Abnormal respiratory sounds (wheezing and/or crackles) are diagnosis criteria of acute bronchiolitis. One third of these infants will develop recurrent episodes, leading to the diagnosis of infant asthma. Nowadays, no available treatment shortens the course of bronchiolitis or hastens the resolution of symptoms, thus, therapy is supportive. Our hypothesis is that the diagnosis of wheezing during bronchiolitis (~60% of infants) will help to select infants who will benefit from anti-asthma therapy. In this setting the diagnosis of wheezing is crucial, and an objective tool for recognition of wheezing is of clinical value. The investigators developed a wheezing recognition algorithm from recorded respiratory sounds with a Smartphone placed near the mouth (Bokov P, Comput Biol Med, 2016). The objectives of the present cross sectional, observational study are 1/ to further validate our approach in a larger sample of infants (1 to 24 months) admitted to hospital for a respiratory complaint during the period of viral bronchiolitis, and 2/ to use gold standard diagnosis of wheezing by respiratory sound recording (Littmann) and subsequent analysis by two experienced pediatricians.

Study Overview

• Status: Completed
• Conditions: Bronchiolitis

Detailed Description

Infants (1 to 24 months old) are recruited in two emergency departments (Robert Debré; Antoine Béclère hospitals of Assistance publique - Hôpitaux de Paris) based on a respiratory complaint. Six characteristics are recorded (age, sex, SpO2, presence or absence of wheezing, other respiratory sound, initial diagnosis). Two recordings of respiratory sounds are obtained almost simultaneously: one with a Smartphone at the mouth (5 cm) and one with an electronic stetoscope (Littmann). Two expert pediatricians listen the recordings giving thee groups: with wheezing (agreement), without wheezing (agreement) and non agreement diagnosis. The recordings made with the Smartphone are subjected to the wheezing recognition algorithm as previously described. The sensitivity, specificity, PPV, NPP are then evaluated. The algorithm will further be improved if necessary using the true negative and true positive recordings (those with expert agreement).

• Study Type: Observational
• Enrollment (Actual): 600

Contacts and Locations

Study Locations

• France
  • Paris, France, 75019
    • Hôpital Robert Debré; service de Physiologie

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 1 month to 2 years (CHILD)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Infant selected in the emergency department: respiratory complaint

Description

Inclusion Criteria:

• infant 1 to 24 months old
• respiratory complaint in the emergency room

Exclusion Criteria:

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
positive and negative predictive values of the algorithm for wheezing diagnosis	8 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
sensibility and specificity of the algorithm in subgroups	The sensibility and specificity of the algorithm will be assessed for recordings with other respiratory sounds (crackles for instance) The agreement (kappa value) between the emergency room sound diagnosis and both the expert and algorithm diagnosis (diagnostic ability of the physician in the emergency room)	8 months

Collaborators and Investigators

• Sponsor: Assistance Publique - Hôpitaux de Paris

Publications and helpful links

General Publications

• Bokov P, Mahut B, Flaud P, Delclaux C. Wheezing recognition algorithm using recordings of respiratory sounds at the mouth in a pediatric population. Comput Biol Med. 2016 Mar 1;70:40-50. doi: 10.1016/j.compbiomed.2016.01.002. Epub 2016 Jan 8.

Study record dates

Study Major Dates

• Study Start (ACTUAL): October 1, 2016
• Primary Completion (ACTUAL): April 1, 2017
• Study Completion (ACTUAL): June 1, 2017

Study Registration Dates

• First Submitted: September 1, 2016
• First Submitted That Met QC Criteria: September 7, 2016
• First Posted (ESTIMATE): September 13, 2016

Study Record Updates

• Last Update Posted (ACTUAL): February 6, 2023
• Last Update Submitted That Met QC Criteria: February 3, 2023
• Last Verified: August 1, 2016

More Information

Terms related to this study

• Keywords: wheezing; bronchiolitis; respiratory sound algorithm
• Additional Relevant MeSH Terms: Infections; Respiratory Tract Infections; Respiratory Tract Diseases; Lung Diseases; Bronchial Diseases; Signs and Symptoms, Respiratory; Lung Diseases, Obstructive; Bronchitis; Bronchiolitis; Respiratory Sounds
• Other Study ID Numbers: ID RCB : 2015-A01499-40

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO