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Biomedical subjects

D Dickson

Publications and source records attributed to D Dickson.

At least 145 records · Page 8Linked to original sources
PubMed1996

Associations of status and change measures of neuropsychological function with pathologic changes in elderly, originally nondemented subjects.

OBJECTIVE: To describe the association between status and change of neuropsychological function and postmortem neuropathologic findings in subjects with Alzheimer's disease, vascular dementia, normal aging, and pathologic aging. DESIGN: Volunteer cohort study. SETTING: Volunteers were interviewed and tested in outpatient-clinical research offices. PARTICIPANTS: Nondemented, healthy, community-residing subjects, initially between 75 and 85 years of age, who participated in the Bronx Aging Study and had at least 2 years of neuropsychological data and quantitative neuropathologic examinations. MAIN OUTCOME MEASURES: Initial summary neuropsychological score, rate of change score. RESULTS: Summary neuropsychological scores at baseline in subjects who subsequently developed pathologically confirmed Alzheimer's disease or vascular dementia were 0.8 z units lower than those of subjects classified in the normal or pathologic aging subgroups (P < .05). Subjects with Alzheimer's disease showed more neuropsychological change over time than subjects in the normal or pathologic aging groups (P < .001). Normal subjects and subjects with pathologic aging did not differ in baseline scores or rate of change. Level of education was strongly associated with initial neuropsychological scores (P < .004), but not with change scores. CONCLUSIONS: Among elderly, initially nondemented subjects who were followed up until death, subjects with pathologically confirmed Alzheimer's disease or vascular dementia had lower neuropsychological scores at initial evaluation than normal subjects or subjects with pathologic aging. Subjects with Alzheimer's disease had a more rapid rate of decline than normal subjects or subjects with pathologic aging.

Aged↗
PubMed1996

What can artificial neural networks teach us about neurodegenerative disorders with extrapyramidal features?

Artificial neural networks (ANNs), computer paradigms that can learn, excel in pattern recognition tasks such as disease diagnosis. Artificial neural networks operate in two different learning modes: supervised, in which a known diagnostic outcome is presented to the ANN, and unsupervised, in which the diagnostic outcome is not presented. A supervised learning ANN could emulate human expert diagnostic performance and identify relevant predictive markers in the diagnostic task, while an unsupervised learning ANN could suggest reasonable alternative diagnostic classification criteria. In the present study, we used ANN methodology to try to overcome the neuropathological difficulties in differentiating the subtypes of progressive supranuclear palsy (PSP), and in differentiating PSP from postencephalitic parkinsonism (PEP) and corticobasal degeneration, or Pick's disease from corticobasal degeneration. First, we applied supervised learning ANN to classify 62 cases of these disorders and to identify diagnostic markers that distinguish them. In a second experiment, we used unsupervised learning ANN to investigate possible alternative nosological classifications. Artificial neural networks input data for each case consisted of values representing histological features, including neurofibrillary tangles, neuronal loss and gliosis found in multiple brain sampling areas. The supervised learning ANN achieved excellent accuracy in classifying PSP but had difficulty classifying the other disorders. This method identified a few features that might help to differentiate PEP, supported currently proposed criteria for Pick's disease, corticobasal degeneration and typical PSP, but detected no features to characterize the atypical subtype of PSP. In general, unsupervised learning ANN supported the present nosological classification for PSP, PEP, Pick's disease and corticobasal degeneration, although it overlapped some groups. Artificial neural networks methodology appears promising for studying neurodegenerative disorders.

Basal Ganglia Diseases↗
PubMed1996

Validity and reliability of the preliminary NINDS neuropathologic criteria for progressive supranuclear palsy and related disorders.

We investigated the validity and reliability of diagnoses made by eight neuropathologists who used the preliminary NINDS neuropathologic diagnostic criteria for progressive supranuclear palsy (PSP) and related disorders. The specific disorders were typical, atypical, and combined PSP, postencephalitic parkinsonism, corticobasal ganglionic degeneration, and Pick's disease. These disorders were chosen because of the difficulties in their neuropathologic differentiation. We assessed validity by measuring sensitivity and positive predictive value. Reliability was evaluated by measuring pairwise and group agreement. From a total of 62 histologic cases, each neuropathologist independently classified 16 to 19 cases for the pairwise analysis and 5 to 6 cases for the group analysis. The neuropathologists were unaware of the study design, unfamiliar with the assigned cases, and initially had no clinical information about the cases. Our results showed that with routine sampling and staining methods, neuropathologic examination alone was not fully adequate for differentiating the disorders. The main difficulties were discriminating the subtypes of PSP and separating postencephalitic parkinsonism from PSP. Corticobasal ganglionic degeneration and Pick's disease were less difficult to distinguish from PSP. The addition of minimal clinical information contributed to the accuracy of the diagnosis. On the basis of results obtained, we propose clinicopathologic diagnostic criteria to improve on the NINDS criteria.

Aged↗
PubMed1996

Familial and sporadic Alzheimer's disease: neuropathology cannot exclude a final common pathway.

Whether all etiologic forms of Alzheimer's disease (AD) share a final common pathway is a major issue. We determined the severity and regional distribution of neuronal loss, amyloid plaques, neuritic plaques (NPs), and neurofibrillary tangles (NFTs), and calculated the ratio of neuronal loss to NPs and NFTs in brains of 19 familial AD (FAD) patients with linkage to chromosome 14, six AD patients with mutations of chromosome 21 (codon 717 of the beta-amyloid percursor protein gene), and 11 sporadic AD (SAD) patients. There was no difference in the pattern of distribution of the various pathologic features or in the ratio of neuronal loss to NPs or NFTs in any AD group. However, FAD groups could be distinguished from SAD by the greater severity and the lack of influence of apolipoprotein E genotype on pathology. These differences may reflect differences in age at onset rather than different etiopathologic mechanisms. The similarity of pathologic findings in the different AD groups provides evidence for a final common pathophysiologic pathway in AD.

Age of Onset↗