Evaluation of the diagnostic implications of Das-Naglieri cognitive assessment system in children with attention deficit hyperactivity disorder

Alterations of brain gray matter volume in children with obstructive sleep apnea

Objective

Obstructive sleep apnea (OSA) seriously affects the children's cognitive functions, but the neuroimaging mechanism of cognitive impairment is still unclear. The purpose of our study was to explore the difference in brain local gray matter volume (GMV) between children with OSA and non-OSA, and the correlation between the difference regions of brain gray matter volume and cognitive, the severity of OSA.

Method

Eighty-three children aged 8-13 years were recruited in our study, 52 children were diagnosed as OSA by polysomnography, and 31 as the non-OSA. All the subjects were underwent high-resolution 3-dimensional T1-weighted magnetic resonance images. The voxel-based morphometry (VBM) was be used to analyse the local GMV. The Das-Naglieri cognitive assessment system (DN: CAS) was used to assess the subjects' cognitive. The difference of local GMV between the two groups was analyzed by two-sample T-test. The PSG variables and the scores of DN: CAS between the OSA group and non-OSA group were compared by independent samples t-tests. Pearson correlation was used to calculate the association between the difference areas of gray matter volumes in brain and DN: CAS scores, obstructive apnea/hypopnea index (OAHI, an index of the severity of OSA).

Results

The gray matter volume of the right Middle Frontal Gyrus (MFG_R) in OSA children were larger than the non-OSA children, and the OSA children had lower scores of the Word Series in DN: CAS. There was negative correlation between the scores of Expressive Attention in DN: CAS and the gray matter volume of the right middle frontal gyrus, and it was no significantly correlation between OAHI and the gray matter volume of the right middle frontal gyrus.

Conclusion

Our results suggest that the development of gray matter volume in frontal cortex, which associated with attention, were sensitive to the effects of OSA, provides neuroimaging evidence for cognitive impairment in children with OSA.

Comparison of the Cognitive Processing Structures of Students Diagnosed With Attention Deficit Hyperactivity Disorder, and Specific Learning Disorder According to Cognitive Assessment System Scores

OBJECTIVE

The aim of this study is to compare the cognitive processing structures of students diagnosed with attention deficit hyperactivity disorder (ADHD) and specific learning disorder (SLD). AD and HD in this study are grouped separately. There are no students diagnosed as having two subgroups together.

METHODS

A total of 105 students, 35 AD, 35 SLD, and 35 HD, who were applied to the Cognitive Assessment System (CAS) and diagnosed by an expert, were selected as the sample. The students were evaluated according to their CAS full scale scores and the results of planning, attention, and simultaneous and successive cognitive processing areas.

RESULTS

It was examined whether the cognitive processing areas of the students differed among the diagnosis groups by one-way analysis of variance. Although no significant difference was found in the cognitive processing full scale score among the diagnosis groups, significant differences were found between the cognitive processing areas among the diagnosis groups. The planning scale scores of the students in the HD diagnosis group were lower than the other groups, the attention scale scores of the students in the AD diagnosis group were lower than the HD and SLD diagnostic groups, and simultaneous and successive cognitive processing scores of the students in the SLD diagnosis group were lower than the scores of the students in the HD and AD diagnosis groups. In our study, it was determined that students in different diagnosis groups have different cognitive structures. For this reason, it is necessary to prepare and apply different cognitive intervention programs suitable for each diagnostic group.

CONCLUSION

Determining the cognitive processing areas of students in different diagnosis groups will guide the creation of the content of cognitive intervention programs.