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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT02897960
Other study ID # ID RCB : 2015-A01499-40
Secondary ID
Status Completed
Phase
First received
Last updated
Start date October 2016
Est. completion date June 2017

Study information

Verified date August 2016
Source Assistance Publique - Hôpitaux de Paris
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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.


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).


Recruitment information / eligibility

Status Completed
Enrollment 600
Est. completion date June 2017
Est. primary completion date April 2017
Accepts healthy volunteers No
Gender All
Age group 1 Month to 24 Months
Eligibility Inclusion Criteria: - infant 1 to 24 months old - respiratory complaint in the emergency room Exclusion Criteria:

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
France Hôpital Robert Debré; service de Physiologie Paris

Sponsors (1)

Lead Sponsor Collaborator
Assistance Publique - Hôpitaux de Paris

Country where clinical trial is conducted

France, 

References & Publications (1)

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. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary positive and negative predictive values of the algorithm for wheezing diagnosis 8 months
Secondary 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
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