Cognitive and SPECT characteristics predict progression of Parkinson's disease in newly diagnosed patients.
Identifieur interne : 000F30 ( PubMed/Checkpoint ); précédent : 000F29; suivant : 000F31Cognitive and SPECT characteristics predict progression of Parkinson's disease in newly diagnosed patients.
Auteurs : Kathy Dujardin [France] ; Luc Defebvre [France] ; Alain Duhamel ; Pascal Lecouffe ; Pascal Rogelet ; Marc Steinling ; Alain Destée [France]Source :
- Journal of neurology [ 0340-5354 ] ; 2004.
English descriptors
- KwdEn :
- Aged, Brain Mapping, Cerebrovascular Circulation (physiology), Cognition (physiology), Cohort Studies, Disease Progression, Factor Analysis, Statistical, Female, Follow-Up Studies, Functional Laterality (physiology), Humans, Iodine Radioisotopes (metabolism), Male, Middle Aged, Neuropsychological Tests (statistics & numerical data), Parkinson Disease (diagnostic imaging), Parkinson Disease (physiopathology), Predictive Value of Tests, Tomography, Emission-Computed, Single-Photon.
- MESH :
- chemical , metabolism : Iodine Radioisotopes.
- diagnostic imaging : Parkinson Disease.
- physiology : Cerebrovascular Circulation, Cognition, Functional Laterality.
- physiopathology : Parkinson Disease.
- statistics & numerical data : Neuropsychological Tests.
- Aged, Brain Mapping, Cohort Studies, Disease Progression, Factor Analysis, Statistical, Female, Follow-Up Studies, Humans, Male, Middle Aged, Predictive Value of Tests, Tomography, Emission-Computed, Single-Photon.
Abstract
To identify features in cognitive functioning and regional cerebral blood flow (rCBF) in newly diagnosed Parkinson's disease (PD) patients and to determine whether these factors are able to predict the progression of the disease in general and the development of cognitive decline in particular.
DOI: 10.1007/s00415-004-0549-2
PubMed: 15592735
Affiliations:
- France
- Hauts-de-France, Nord-Pas-de-Calais
- Lille
- Université Lille 2, Université Lille Nord de France
Links toward previous steps (curation, corpus...)
Links to Exploration step
pubmed:15592735Le document en format XML
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<front><div type="abstract" xml:lang="en">To identify features in cognitive functioning and regional cerebral blood flow (rCBF) in newly diagnosed Parkinson's disease (PD) patients and to determine whether these factors are able to predict the progression of the disease in general and the development of cognitive decline in particular.</div>
</front>
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<DateCreated><Year>2004</Year>
<Month>12</Month>
<Day>13</Day>
</DateCreated>
<DateCompleted><Year>2005</Year>
<Month>03</Month>
<Day>14</Day>
</DateCompleted>
<DateRevised><Year>2016</Year>
<Month>11</Month>
<Day>24</Day>
</DateRevised>
<Article PubModel="Print"><Journal><ISSN IssnType="Print">0340-5354</ISSN>
<JournalIssue CitedMedium="Print"><Volume>251</Volume>
<Issue>11</Issue>
<PubDate><Year>2004</Year>
<Month>Nov</Month>
</PubDate>
</JournalIssue>
<Title>Journal of neurology</Title>
<ISOAbbreviation>J. Neurol.</ISOAbbreviation>
</Journal>
<ArticleTitle>Cognitive and SPECT characteristics predict progression of Parkinson's disease in newly diagnosed patients.</ArticleTitle>
<Pagination><MedlinePgn>1383-92</MedlinePgn>
</Pagination>
<Abstract><AbstractText Label="OBJECTIVE" NlmCategory="OBJECTIVE">To identify features in cognitive functioning and regional cerebral blood flow (rCBF) in newly diagnosed Parkinson's disease (PD) patients and to determine whether these factors are able to predict the progression of the disease in general and the development of cognitive decline in particular.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">50 previously treatment-naive PD patients participated in the study. Cognitive assessment and SPECT were performed twice: at the time of diagnosis and then 3 years later. Six patients died or refused to continue. The Mattis dementia rating scale, the WAIS-R digit span test, a word list learning/recall test, a word fluency task and the Stroop word-colour test were used to assess cognitive function. rCBF was measured in 10 pairs of regions of interest. Principal component analysis of the data from the final examination was used to determine which variables allowed the formation of patient subgroups. Thereafter, factorial discriminant analysis (FDA) was performed in order to obtain a predictive model of these final classes.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">A stepwise procedure enabled the identification of 3 clusters (26, 16 and 2 patients). As the patients in the smallest cluster met the criteria for dementia at the final examination, they were discarded from further analyses. All the cognitive variables contributed to the constitution of the two other clusters. Age, educational level and all the rCBF parameters also contributed but to a lesser extent. Comparison of these groups showed reduced overall cognitive efficiency and an exacerbated subcorticofrontal syndrome in the 16-patient cluster. FDA showed that the best predictive model for the final classes was based on 7 variables: educational level, semantic and alternating word fluency, Stroop interference index and the right medial frontal, left parietal and left lenticular nucleus rCBF findings.</AbstractText>
<AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">Even though both cognitive and rCBF parameters help predict the progression of newly diagnosed PD patients and bearing in mind the limitations of the SPECT method used here, it appears that the contribution of cognitive assessment is greater than that of rCBF measurement.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Dujardin</LastName>
<ForeName>Kathy</ForeName>
<Initials>K</Initials>
<AffiliationInfo><Affiliation>Neurologie et Pathologie du Mouvement Neurologie A, Hôpital Salengro Centre Hospitalier Universitaire, 59037, Lille Cedex, France. dujardin@univ-lille3.fr</Affiliation>
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<Author ValidYN="Y"><LastName>Defebvre</LastName>
<ForeName>Luc</ForeName>
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<Author ValidYN="Y"><LastName>Duhamel</LastName>
<ForeName>Alain</ForeName>
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<ForeName>Pascal</ForeName>
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<Author ValidYN="Y"><LastName>Rogelet</LastName>
<ForeName>Pascal</ForeName>
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<Author ValidYN="Y"><LastName>Steinling</LastName>
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<Initials>M</Initials>
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<ForeName>Alain</ForeName>
<Initials>A</Initials>
</Author>
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<MeshHeading><DescriptorName UI="D010300" MajorTopicYN="N">Parkinson Disease</DescriptorName>
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<MeshHeading><DescriptorName UI="D011237" MajorTopicYN="N">Predictive Value of Tests</DescriptorName>
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<country name="France"><region name="Hauts-de-France"><name sortKey="Dujardin, Kathy" sort="Dujardin, Kathy" uniqKey="Dujardin K" first="Kathy" last="Dujardin">Kathy Dujardin</name>
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