Clinical trial NCT02897960: Wheezing Diagnosis Using a Smartphone
Official title: Wheezing Diagnosis Using a Smartphone in Infants Referred for Bronchiolitis
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Bronchiolitis
Keywords: wheezing
bronchiolitis
respiratory sound algorithm
Lead sponsor: Assistance Publique - Hôpitaux de Paris
Sponsor class: OTHER
First posted: 2016-09-13
Enrollment: 600
Sex: ALL
Minimum age (years): 1
Maximum age (years): 24
Standard ages: CHILD
Accepts healthy volunteers: no
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Infant selected in the emergency department: respiratory complaint

Brief summary: 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.

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).

Eligibility criteria: Inclusion Criteria:

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

Exclusion Criteria:

Primary outcomes:
measure: positive and negative predictive values of the algorithm for wheezing diagnosis
timeFrame: 8 months
Secondary outcomes:
measure: sensibility and specificity of the algorithm in subgroups
timeFrame: 8 months
Other outcomes:
Locations:
city: Paris
country: France
facility: Hôpital Robert Debré; service de Physiologie
Study officials:
References:
citation: 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.