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1.
J Parkinsons Dis ; 7(2): 385-395, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28387684

RESUMO

BACKGROUND: Methods to detect early cognitive decline and account for heterogeneity of deficits in Parkinson's disease (PD) are needed. Quantitative methods such as latent class analysis (LCA) offer an objective approach to delineate discrete phenotypes of impairment. OBJECTIVE: To identify discrete neurocognitive phenotypes in PD patients without dementia. METHODS: LCA was applied to a battery of 8 neuropsychological measures to identify cognitive subtypes in a cohort of 199 non-demented PD patients. Two measures were analyzed from each of four domains: executive functioning, memory, visuospatial abilities, and language. Additional analyses compared groups on clinical characteristics and cognitive diagnosis. RESULTS: LCA identified 3 distinct groups of PD patients: an intact cognition group (54.8%), an amnestic group (32.2%), and a mixed impairment group with dysexecutive, visuospatial and lexical retrieval deficits (13.1%). The two impairment groups had significantly lower instrumental activities of daily living ratings and greater motor symptoms than the intact group. Of those diagnosed as cognitively normal according to MDS criteria, LCA classified 23.2% patients as amnestic and 9.9% as mixed cognitive impairment. CONCLUSIONS: Non-demented PD patients exhibit distinct neuropsychological profiles. One-third of patients with LCA-determined impairment were diagnosed as cognitively intact by expert consensus, indicating that classification using a statistical algorithm may improve detection of initial and subtle cognitive decline. This study also demonstrates that memory impairment is common in non-demented PD even when cognitive impairment is not clinically apparent. This study has implications for predicting eventual emergence of significant cognitive decline, and treatment trials for cognitive dysfunction in PD.


Assuntos
Doença de Parkinson/classificação , Doença de Parkinson/diagnóstico , Idoso , Amnésia/complicações , Cognição , Disfunção Cognitiva/complicações , Função Executiva , Feminino , Humanos , Masculino , Testes Neuropsicológicos , Doença de Parkinson/complicações , Doença de Parkinson/psicologia
2.
Childs Nerv Syst ; 28(10): 1701-14, 2012 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-22828866

RESUMO

PURPOSE: Based on the success of deep brain stimulation (DBS) in the treatment of adult disorders, it is reasonable to assume that the application of DBS in the pediatric population is an emerging area worthy of study. The purpose of this paper is to outline the current movement disorder indications for DBS in the pediatric population, and to describe areas of investigation, including possible medically refractory psychiatric indications. METHODS: We performed a structured review of the English language literature from 1990 to 2011 related to studies of DBS in pediatrics using Medline and PubMed search results. RESULTS: Twenty-four reports of DBS in the pediatric population were found. Based on published data on the use of DBS for pediatric indications, there is a spectrum of clinical evidence for the use of DBS to treat different disorders. Dystonia, a disease associated with a low rate of remission and significant disability, is routinely treated with DBS and is currently the most promising pediatric application of DBS. We caution the application of DBS to conditions associated with a high remission rate later in adulthood, like obsessive-compulsive disorder and Tourette's syndrome. Moreover, epilepsy and obesity are currently being investigated as indications for DBS in the adult population; however, both are associated with significant morbidity in pediatrics. CONCLUSION: While currently dystonia is the most promising application of DBS in the pediatric population, multiple conditions currently being investigated in adults also afflict children and adolescents, and thus warrant further research.


Assuntos
Encefalopatias/terapia , Estimulação Encefálica Profunda/métodos , Pediatria , Bases de Dados Factuais/estatística & dados numéricos , Humanos , Estudos Retrospectivos
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