8 resultados para Use disorders
em Aston University Research Archive
Resumo:
The use of quantitative methods has become increasingly important in the study of neurodegenerative disease. Disorders such as Alzheimer's disease (AD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This article reviews the advantages and limitations of the different methods of quantifying the abundance of pathological lesions in histological sections, including estimates of density, frequency, coverage, and the use of semiquantitative scores. The major sampling methods by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are also described. In addition, the data analysis methods commonly used to analyse quantitative data in neuropathology, including analyses of variance (ANOVA) and principal components analysis (PCA), are discussed. These methods are illustrated with reference to particular problems in the pathological diagnosis of AD and dementia with Lewy bodies (DLB).
Resumo:
The role of oxidation in the development of age-related eye disease has prompted interest in the use of nutritional supplementation for prevention of onset and progression. Our aim is to highlight possible contraindications and adverse reactions of isolated or high dose ocular nutritional supplements. Web of Science and PubMed database searches were carried out, followed by a manual search of the bibliographies of retrieved articles. Vitamin A should be avoided in women who may become pregnant, in those with liver disease, and in people who drink heavily. Relationships have been found between vitamin A and reduced bone mineral density, and beta-carotene and increased risk of lung cancer in smoking males. Vitamin E and Ginkgo biloba have anticoagulant and anti-platelet effects respectively, and high doses are contraindicated in those being treated for vascular disorders. Those patients with contraindications or who are considered at risk of adverse reactions should be advised to seek specialist dietary advice via their medical practitioner. © 2005 The College of Optometrists.
Resumo:
Two contrasting multivariate statistical methods, viz., principal components analysis (PCA) and cluster analysis were applied to the study of neuropathological variations between cases of Alzheimer's disease (AD). To compare the two methods, 78 cases of AD were analyzed, each characterised by measurements of 47 neuropathological variables. Both methods of analysis revealed significant variations between AD cases. These variations were related primarily to differences in the distribution and abundance of senile plaques (SP) and neurofibrillary tangles (NFT) in the brain. Cluster analysis classified the majority of AD cases into five groups which could represent subtypes of AD. However, PCA suggested that variation between cases was more continuous with no distinct subtypes. Hence, PCA may be a more appropriate method than cluster analysis in the study of neuropathological variations between AD cases.
Resumo:
The traditional method of classifying neurodegenerative diseases is based on the original clinico-pathological concept supported by 'consensus' criteria and data from molecular pathological studies. This review discusses first, current problems in classification resulting from the coexistence of different classificatory schemes, the presence of disease heterogeneity and multiple pathologies, the use of 'signature' brain lesions in diagnosis, and the existence of pathological processes common to different diseases. Second, three models of neurodegenerative disease are proposed: (1) that distinct diseases exist ('discrete' model), (2) that relatively distinct diseases exist but exhibit overlapping features ('overlap' model), and (3) that distinct diseases do not exist and neurodegenerative disease is a 'continuum' in which there is continuous variation in clinical/pathological features from one case to another ('continuum' model). Third, to distinguish between models, the distribution of the most important molecular 'signature' lesions across the different diseases is reviewed. Such lesions often have poor 'fidelity', i.e., they are not unique to individual disorders but are distributed across many diseases consistent with the overlap or continuum models. Fourth, the question of whether the current classificatory system should be rejected is considered and three alternatives are proposed, viz., objective classification, classification for convenience (a 'dissection'), or analysis as a continuum.
Resumo:
OBJECTIVE: To review data on the effectiveness of topiramate as a mood stabilizer. DATA SOURCES: Clinical literature accessed through MEDLINE (1985-September 2001) and the manufacturer. Key search terms included topiramate, mania, mood stabilizer, and bipolar disorder. DATA SYNTHESIS: The traditional standard therapy for bipolar disorder has been lithium. Other mood stabilizers are increasingly being used to manage this complex disorder. Studies that used topiramate in bipolar disorders were evaluated. CONCLUSIONS: The present data from open trials suggest that topiramate may possibly possess antimanic properties. Controlled, double-blind studies are required to confirm this efficacy
Resumo:
OBJECTIVE: To review the effectiveness data on the use of gabapentin in bipolar disorders. DATA SOURCES: Clinical literature was accessed through MEDLINE (January 1985–November 2000). Key search terms included gabapentin, mood stabilizer, and bipolar disorder. DATA SYNTHESIS: Bipolar disorder is a complex condition that can be difficult to treat effectively. Mood stabilizers are increasingly being used to manage bipolar disorder. Studies that used gabapentin in bipolar disorders are evaluated. CONCLUSIONS: From the data presented, gabapentin cannot be recommended for treatment of bipolar disorder. Further studies are required to determine whether gabapentin has any role in the management of bipolar disorder.
Resumo:
Recent research has investigated the capability of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) descriptions to identify individuals who should receive a diagnosis of Autism Spectrum Disorder (ASD) using standardised diagnostic instruments. Building on previous research investigating behaviours essential for the diagnosis of DSM-5 ASD, the current study investigated the sensitivity and specificity of a set of 14 items derived from the Diagnostic Interview for Social and Communication Disorders (DISCO Signposting set) that have potential for signposting the diagnosis of autism according to both the new DSM-5 criteria for ASD and ICD-10 criteria for Childhood Autism. An algorithm threshold for the Signposting set was calculated in Sample 1 (n = 67), tested in an independent validation sample (Sample 2; n = 78), and applied across age and ability sub-groups in Sample 3 (n = 190). The algorithm had excellent predictive validity according to best estimate clinical diagnosis (Samples 1 and 2) and excellent agreement with established algorithms for both DSM-5 and ICD-10 (all samples). The signposting set has potential to inform our understanding of the profile of ASD in relation to other neurodevelopmental disorders and to form the basis of a Signposting Interview for use in clinical practice.
Resumo:
Healthy brain functioning depends on efficient communication of information between brain regions, forming complex networks. By quantifying synchronisation between brain regions, a functionally connected brain network can be articulated. In neurodevelopmental disorders, where diagnosis is based on measures of behaviour and tasks, a measure of the underlying biological mechanisms holds promise as a potential clinical tool. Graph theory provides a tool for investigating the neural correlates of neuropsychiatric disorders, where there is disruption of efficient communication within and between brain networks. This research aimed to use recent conceptualisation of graph theory, along with measures of behaviour and cognitive functioning, to increase understanding of the neurobiological risk factors of atypical development. Using magnetoencephalography to investigate frequency-specific temporal dynamics at rest, the research aimed to identify potential biological markers derived from sensor-level whole-brain functional connectivity. Whilst graph theory has proved valuable for insight into network efficiency, its application is hampered by two limitations. First, its measures have hardly been validated in MEG studies, and second, graph measures have been shown to depend on methodological assumptions that restrict direct network comparisons. The first experimental study (Chapter 3) addressed the first limitation by examining the reproducibility of graph-based functional connectivity and network parameters in healthy adult volunteers. Subsequent chapters addressed the second limitation through adapted minimum spanning tree (a network analysis approach that allows for unbiased group comparisons) along with graph network tools that had been shown in Chapter 3 to be highly reproducible. Network topologies were modelled in healthy development (Chapter 4), and atypical neurodevelopment (Chapters 5 and 6). The results provided support to the proposition that measures of network organisation, derived from sensor-space MEG data, offer insights helping to unravel the biological basis of typical brain maturation and neurodevelopmental conditions, with the possibility of future clinical utility.