Establishment of an objective index for the diagnosis of attention deficit/hyperactivity disorder by the continuous performance test "MOGRAZ".
Attention deficit/hyperactivity disorder
Continuous performance test
MOGRAZ
Multiple logistic regression analysis
Prediction model
Journal
Brain & development
ISSN: 1872-7131
Titre abrégé: Brain Dev
Pays: Netherlands
ID NLM: 7909235
Informations de publication
Date de publication:
Nov 2022
Nov 2022
Historique:
received:
02
07
2021
revised:
08
07
2022
accepted:
08
07
2022
pubmed:
26
7
2022
medline:
11
11
2022
entrez:
25
7
2022
Statut:
ppublish
Résumé
The diagnosis of attention deficit/hyperactivity disorder (AD/HD) in Japan is mainly based on information obtained from caregivers. There is therefore a need to establish an objectivity index that can be easily used in clinical practice. The purpose of the study was to create a predictive model for the diagnosis of AD/HD using the MOGRAZ, a visual continuous performance test developed in Japan. We collected data from an AD/HD group and a non-AD/HD group. The AD/HD group included 75 children with predominantly inattentive type AD/HD and 48 with combined type AD/HD who were aged 6 to 12 years and diagnosed at our department. The non-AD/HD group included 153 Japanese children aged 6 to 11 years enrolled in regular classes at a public elementary school. In both groups, multiple logistic regression analysis was performed using the results of MOGRAZ, age, and sex as parameters, and algorithms for a predictive diagnostic model of AD/HD were created. The area under the receiver operating characteristic curve (ROC-AUC) between the predominantly inattentive type AD/HD subgroup and non-AD/HD group was 0.884 (95% confidence interval: 0.837-0.932), and the ROC-AUC between the combined type AD/HD subgroup and non-AD/HD group was 0.914 (95% CI: 0.869-0.959). The prediction model using the MOGRAZ score allowed us to create an objectivity index to determine the diagnosis of AD/HD that can be easily used in clinical practice. We plan additional verification of this prediction model with additional participants.
Identifiants
pubmed: 35879141
pii: S0387-7604(22)00115-2
doi: 10.1016/j.braindev.2022.07.002
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
664-671Informations de copyright
Copyright © 2022 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.