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Subtypes of autism by cluster analysis based on structural MRI data
Hrdlicka M., Dudova I., Beranova I., Lisy J., Belsan T., Neuwirth J., Komarek V., Faladova L., Havlovicova M., Sedlacek Z., Blatny M., Urbanek T.
Jazyk angličtina Země Německo
E-zdroje NLK Online
ProQuest Central od 1997-03-01 do Před 1 rokemCINAHL Plus with Full Text (EBSCOhost) od 1998-01-01 do Před 1 rokem
Medline Complete (EBSCOhost) od 1998-01-01 do Před 1 rokem
Nursing & Allied Health Database (ProQuest) od 1997-03-01 do Před 1 rokem
Health & Medicine (ProQuest) od 1997-03-01 do Před 1 rokem
Family Health Database (ProQuest) od 1997-03-01 do Před 1 rokem
Psychology Database (ProQuest) od 1997-03-01 do Před 1 rokem
- MeSH
- autistická porucha diagnóza MeSH
- dítě MeSH
- financování vládou MeSH
- lidé MeSH
- magnetická rezonanční tomografie MeSH
- mozek abnormality MeSH
- shluková analýza MeSH
- Check Tag
- dítě MeSH
- lidé MeSH
The aim of our study was to subcategorize Autistic Spectrum Disorders (ASD) using a multidisciplinary approach. Sixty four autistic patients (mean age 9.4+/-5.6 years) were entered into a cluster analysis. The clustering analysis was based on MRI data. The clusters obtained did not differ significantly in the overall severity of autistic symptomatology as measured by the total score on the Childhood Autism Rating Scale (CARS). The clusters could be characterized as showing significant differences: Cluster 1: showed the largest sizes of the genu and splenium of the corpus callosum (CC), the lowest pregnancy order and the lowest frequency of facial dysmorphic features. Cluster 2: showed the largest sizes of the amygdala and hippocampus (HPC), the least abnormal visual response on the CARS, the lowest frequency of epilepsy and the least frequent abnormal psychomotor development during the first year of life. Cluster 3: showed the largest sizes of the caput of the nucleus caudatus (NC), the smallest sizes of the HPC and facial dysmorphic features were always present. Cluster 4: showed the smallest sizes of the genu and splenium of the CC, as well as the amygdala, and caput of the NC, the most abnormal visual response on the CARS, the highest frequency of epilepsy, the highest pregnancy order, abnormal psychomotor development during the first year of life was always present and facial dysmorphic features were always present. This multidisciplinary approach seems to be a promising method for subtyping autism.
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- $a The aim of our study was to subcategorize Autistic Spectrum Disorders (ASD) using a multidisciplinary approach. Sixty four autistic patients (mean age 9.4+/-5.6 years) were entered into a cluster analysis. The clustering analysis was based on MRI data. The clusters obtained did not differ significantly in the overall severity of autistic symptomatology as measured by the total score on the Childhood Autism Rating Scale (CARS). The clusters could be characterized as showing significant differences: Cluster 1: showed the largest sizes of the genu and splenium of the corpus callosum (CC), the lowest pregnancy order and the lowest frequency of facial dysmorphic features. Cluster 2: showed the largest sizes of the amygdala and hippocampus (HPC), the least abnormal visual response on the CARS, the lowest frequency of epilepsy and the least frequent abnormal psychomotor development during the first year of life. Cluster 3: showed the largest sizes of the caput of the nucleus caudatus (NC), the smallest sizes of the HPC and facial dysmorphic features were always present. Cluster 4: showed the smallest sizes of the genu and splenium of the CC, as well as the amygdala, and caput of the NC, the most abnormal visual response on the CARS, the highest frequency of epilepsy, the highest pregnancy order, abnormal psychomotor development during the first year of life was always present and facial dysmorphic features were always present. This multidisciplinary approach seems to be a promising method for subtyping autism.
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