RESUMO
Attention is an essential cognitive function which was use to perceive the external world, and it is the basis of all cognitive activities.Other cognitive functions such as working memory, executive function, information processing speed and so on, are also adversely affected in hypoprosexia or hyperfocusing state.Patients with schizophrenia have severe attention disorder, which makes patients unable to successfully complete the task of work or study, thus reduce the quality of life.Attention disorder exists throughout the whole course of this disease, and there is no specific drug for it.In recent years, antipsychotic medications have widespread application, but it has not shown up significantly improvement of attention disorder, worse still, its side effects will exacerbate the disease, which results in the impairment of the patients' ability to learn and explore the novelties.Neuroimaging markers of attention disorder in schizophrenia are the focus of current researches.White matter fibers are important pathways that connect attention networks and maintain the three-dimensional structure of the brain.Previous studies have suggested that attention disorder may be related to abnormalities of white matter fibers connecting various encephalic regions.In particular, abnormalities in the integrity of white matter, such as corpus callosum, cingulum bundle, superior longitudinal fasciculus, inferior fronto-occipital fasciculus, have been reported to be significantly associated with attention disorder in patients with schizophrenia.In this study, the relationship between attention disorder and white matter structure in patients with schizophrenia is reviewed through diffusion tensor imaging (DTI) technique.
RESUMO
Resumen Introducción: el análisis de conglomerados de clases latentes (ACCL) es un procedimiento estadístico para agrupamientos, dependiendo de la respuesta a cada ítem. Se ha usado con el trastorno de atención hiperactividad (TDAH), para derivar tipos sutiles de casos en estudios genéticos. Objetivo: analizar los CCL de 408 miembros de 120 familias con un caso índice de TDAH, en relación con los síntomas registrados en la entrevista psiquiátrica. Pacientes y métodos: a partir de un caso índice (niño escolarizado de Barranquilla con diagnóstico estándar de oro de TDAH) se construyeron familias nucleares, las cuales de evaluaron para el diagnóstico de TDAH y comorbilidades. La muestra fue de 408 miembros de 120 familias, edad 26,6 ± 15,4 años. Con el programa para computador Latent-Gold 4,0 se hizo el ACCL con la respuesta nominal para cada síntoma de TDAH, y la presencia o no de comorbilidades con TOD y TDC. Se usó el sexo y la edad como covariables categóricas. Se hizo un análisis cruzado de cada conglomerado con el diagnóstico estándar de oro. Resultados: el mejor modelo (índices de verosimilitud) fue de 6 CCL (p Bootstrap = 0,08). El conglomerado 1 (32,5 %) son adultos, predominio de sexo femenino, probabilidad < 20 % de síntomas y comorbilidades. El segundo (17,4 %) son adultos y niños de sexo masculino con 40 a 80 % de síntomas de TDAH combinado. El grupo tres (15,7 %) son niños con ~100 % síntomas de TDAH combinado, TOD y TDC. El cuarto conglomerado (14,3 %) son adultos de ambos sexos con 20 a 50 % probabilidades de hiperactividad-impulsividad, TOD (70 %) y TDC (40 %). El grupo 5 (10,6 %) en un 80 % adultos con 30 a 90 % probabilidades de inatención sin comorbilidades. El conglomerado 6 (9,5 %) con altas probabilidades de síntomas de inatención. Conclusiones: se derivaron 6 CCL. Cuatro conglomerados son de afectados, 1 de no afectados y 1 con similar proporción de afectados y no afectados, los cuales podrían ser usados en análisis con marcadores genéticos de susceptibilidad para TDAH.
Summary Introduction: Latent class cluster analysis (LCCA) is a statistical procedure to sort a sample, according to item response of each member of a sample. It has been used with ADHD in order to derive mild cases for genetic studies. Objective: To analyze LCC from 408 members of 120 nuclear families with a ADHD proband, related to registered symptoms obtained with a structured psychiatric interview. Patient and methods: From a proband (school -gold standard- ADHD affected child from Barranquilla) nuclear families were recruited, which were assess for ADHD and comorbidities diagnoses. Sample was 408 members of 120 nuclear families, mean age 26,6 ± 15,4 years old. Using Latent Gold 4,0 software, an ACCL with each ADHD categorical symptoms, and comorbidities with ODD and CD was run. Gender and age were used as categorical active covariables. A cross tabulation analysis between LCC and ADHD gold standard diagnosis was done. Results: The best model (maximum likelihood index) was a 6 LCC (p Bootstrap = 0,08). Cluster 1 (32,5%) were predominantly female adults with low (< 20%) probability of ADHD symptoms. Cluster 2 (17,4%) were adults and children with 40 to 80% probabilities of combined ADHD symptoms. Cluster 3 (15,7%) were children with ~100% of ADHD combined symptoms with ODD and CD comorbidities. Cluster 4 (14,3%) were adults of both genders with 20 to 50% probabilities of hyperactivity - impulsivity and ODD (70%) and CD (40%). Cluster 5 (10,6%) were 80% adults with 30 to 90% probabilities of inattentive symptoms without comorbidities. Cluster 6 (9,5%) had high probabilities of inattentive symptoms. Conclusions: A 6 LCC model was obtained. Four LCC were ADHD affected, one was unaffected and one with similar proportion of affected and unaffected members, which would are able to be used for genetic analyses with ADHD susceptibility gene markers.