Personalized Digital Health and Artificial Intelligence in Childhood Asthma

NCT04528342 | Unknown DMC

• 1 other identifier: 2019-01238
• Study Type: observational
• Target: 290
• Locations: 1 country
• Sites: 2

Brief Summary

Asthma is a chronic inflammatory disease of the airways that causes recurrent episodes of wheezing, breathing difficulties and coughing. The prevalence of asthma is 8% in school-aged children and 30% in preschoolers, making asthma the first chronic disease in children. Symptoms are due to diffuse but variable airway obstruction, reversible spontaneously or after inhalation of beta2 agonists (β-2a) such as salbutamol. Exacerbations of asthma are frequent and difficult to assess by parents and the patient himself. It is estimated that approximately 2.5% of children with asthma are hospitalized annually. The global burden caused by asthma can thus be reduced by improving early detection of bronchial obstruction, prescribing immediate treatment with the appropriate background therapy, and reliably and objectively assess response to treatment. The natural history of asthma symptoms in children shows a great intra and inter-individual variability. The difficulty of assessing the severity of an attack by the parents or the child himself, when he is old enough to control his chronic disease, is a key element in the management of asthma and allows the treatment to be adapted quickly, sometimes avoiding hospitalization. Healthcare professionals can assess the severity of the episode using the Pediatric Respiratory Assesment Measure (PRAM) score, which has the advantage of being adaptable at any age. The Global Alliance against Chronic Respiratory Diseases (GARD) integrates in its diagnostic strategy for chronic respiratory diseases, the lung function test, which allows the quantification of respiratory function in the context of diagnosis and long-term follow-up. Although spirometry are non-invasive tests, they still require a high level of patient cooperation, which remains problematic before the age of 7 years. The digital stethsocope integrates a capacity for recording auscultations and data transmission to high-performance software. This has made it possible to extend auscultation beyond what was audible to the human ear alone (over 20-20,000 Hertz).Auscultatory sounds analysis, particularly those most often associated with obstructive syndrome could be simple, reproducible and a reliable method of assessing the severity and response to treatment in children's asthma. Major advances in signal processing and unsupervised learning in artificial intelligence research provide the potential for high-performance analysis of physiological measures.

Conditions

Asthma in Children

Keywords

Digital stethoscope;; digital health; machine learning; Asthma

Outcome Measures

Primary Outcomes (2)

• Diagnostic performance of an algorithm compared to the physician in asthma attack

  To evaluate the diagnostic performance of an algorithm in the asthma crisis in children aged between 2 and 16 years old, presenting to the Reception Service, and to Pediatric Emergencies compared to the physician.

  Assessment before inhalation of bronchodilators

• Diagnostic performance of an algorithm compared to the physician in asthma attack

  To evaluate the diagnostic performance of an algorithm in the asthma crisis in children aged between 2 and 16 years old, presenting to the Reception Service, and to Pediatric Emergencies compared to the physician.

  Assessment 20 minutes after inhalation of bronchodilators

Secondary Outcomes (12)

• Artificial intelligence algorithm evaluation in treatment response

  Assessment before inhalation of bronchodilators

• Artificial intelligence algorithm evaluation in treatment response

  Assessment 20 minutes after inhalation of bronchodilators

• Asthma attack severity

  Assessment before inhalation of bronchodilators

• Asthma attack severity

  Assessment 20 minutes after inhalation of bronchodilators

• Analysis of different parameters in asthma attack

  Assessment before inhalation of bronchodilators

Eligibility Criteria

• Age: 2 Years - 16 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17)
• Sampling Method: Probability Sample

Study Population

290 patients presenting with an acute asthma exacerbation within 70 severe asthma (clinical PRAM score \> 7) within the PED. For the hospitalized patients, we estimate 70 patients needed during two years. At least 150 patients up to 7 years of age, within DS measurements and spirometer measures evaluation 6 to 8 weeks after acute episode by the pulmonlogist.

You may qualify if:

• Patients with clinical diagnosis of acute asthma exacerbations
• age \> 2 years and \< 16 years
• information and written consent of a legal representative

You may not qualify if:

• Chronic lung diseases other than asthma (cystic fibrosis, bronchopulmonary Dysplasia),
• Congenital heart disease
• Refusal of consent.

Sponsors & Collaborators

• Isabelle Ruchonnet-Métrailler: lead

Study Sites (2)

Geneva University Hospital

Geneva, 1205, Switzerland

RECRUITING

Geneva University Hospital

Geneva, 1205, Switzerland

RECRUITING

MeSH Terms

Conditions

Asthma

Condition Hierarchy (Ancestors)

Bronchial Diseases; Respiratory Tract Diseases; Lung Diseases, Obstructive; Lung Diseases; Respiratory Hypersensitivity; Hypersensitivity, Immediate; Hypersensitivity; Immune System Diseases

Study Officials

• Alain Gervaix, M.D

  University of Geneva

  STUDY DIRECTOR

• Constance Barazzone Argiroffo, M.D

  University of Geneva

  STUDY CHAIR

• Isabelle Ruchonnet-Metrailler, M.D., PhD

  University of Geneva

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Isabelle Ruchonnet-Metrailler, M.D., PhD

CONTACT

+41.79.553.41.69; Isabelle.Ruchonnet-Metrailler@hcuge.ch

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Hôpitaux Universitaires de Genève

Study Record Dates

• First Submitted: May 12, 2020
• First Posted: August 27, 2020
• Study Start: March 1, 2020
• Primary Completion: November 30, 2021
• Study Completion: April 1, 2022
• Last Updated: February 4, 2021

Record last verified: 2021-02

Data Sharing

• IPD Sharing: Will not share

Locations

CH (2)