Group of children identified by the algorithm as having asthmaGroup of children not identified by the algorithm as having asthma
Group of children identified by the algorithm as having asthma: 150 medical files of children identified by the algorithm as having asthma will be randomly selected for expert appraisal.
Group of children not identified by the algorithm as having asthma: 150 medical files of children not identified by the algorithm as having asthma will be randomly selected for expert appraisal.
Study summary
GPs are one of the key players in the early diagnosis of chronic diseases, such as asthma in pre-school children, by detecting symptoms of illness as early as possible. Patient health data is collected on an ongoing basis in GPs' electronic medical records, but remains little exploited despite its potential.
Helping GPs to identify asthma in pre-school children, based on the information in their electronic medical records, could help them to diagnose the condition early and thereby reduce the morbidity and mortality associated with it.
An algorithm developed and evaluated in a primary care data warehouse should help GPs to identify children with a diagnosis of asthma at an early stage.
Eligibility
Sex
ALL
Min age
24 Months
Max age
71 Months
Healthy volunteers
No
Inclusion Criteria:
* Children aged 2 years 0 days to 5 years 11 months and 30 days inclusive
* Consultation in one of the 4 Maisons de Santé Pluriprofessionnelle connected to the PRIMEGE Normandie primary care data warehouse: Neufchâtel-en-Bray, Val-de-Reuil, Le Grand-Quevilly and Rouen Carmes.
* At least two consultations between the ages of 2 and 5, with a general practitioner in the same care setting
* Parents having been informed of the use of data from electronic medical records and having expressed no objection to the use of this data
Exclusion Criteria:
* Children under 2 years of age
* Children aged 6 years 0 days and over
* Recourse by a patient's legal representative to one of the RGPD rights restricting the use of their data in the context of research
Primary outcome measure(s)
Evaluating the sensitivity of an algorithm for the early identification of extracurricular children with asthma — At enrollment visit Evaluate the algorithm's predictions against expert opinion to estimate the Sensitivity of the algorithm with a minimum accuracy of +/- 0.10 at an α risk of 5%, based on the following variables (number of true positives, number of false positives, number of true negatives and number of false negatives)
Assessing the specificity of an algorithm for the early identification of pre-school children with asthma — At enrollment visit Evaluate the algorithm's predictions against expert opinion to estimate the Specificity of the algorithm with a minimum accuracy of +/- 0.10 at an α risk of 5%, based on the following variables (number of true positives, number of false positives, number of true negatives and number of false negatives)
Assessing the positive predictive value of an algorithm for the early identification of pre-school children with asthma — At enrollment visit Evaluate the algorithm's predictions against expert opinion to estimate the positive predictive value of the algorithm with a minimum accuracy of +/- 0.10 at an α risk of 5%, based on the following variables (number of true positives, number of false positives, number of true negatives and number of false negatives)
Assessing the negative predictive value of an algorithm for the early identification of pre-school children with asthma — At enrollment visit Evaluate the algorithm's predictions against expert opinion to estimate the negative predictive value of the algorithm with a minimum accuracy of +/- 0.10 at an α risk of 5%, based on the following variables (number of true positives, number of false positives, number of true negatives and number of false negatives)
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
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