New Clinical Subtypes of Parkinson Disease and Their Longitudinal Progression: A Prospective Cohort Comparison With Other Phenotypes.
Identifieur interne : 001C01 ( Ncbi/Curation ); précédent : 001C00; suivant : 001C02New Clinical Subtypes of Parkinson Disease and Their Longitudinal Progression: A Prospective Cohort Comparison With Other Phenotypes.
Auteurs : Seyed-Mohammad Fereshtehnejad [Suède] ; Silvia Rios Romenets [Canada] ; Julius B M. Anang [Canada] ; Véronique Latreille [Canada] ; Jean-François Gagnon [Canada] ; Ronald B. Postuma [Canada]Source :
- JAMA neurology [ 2168-6157 ] ; 2015.
English descriptors
- KwdEn :
- Aged, Cognitive Dysfunction (complications), Cognitive Dysfunction (diagnosis), Disease Progression, Female, Follow-Up Studies, Humans, Male, Middle Aged, Parkinson Disease (classification), Parkinson Disease (complications), Parkinson Disease (diagnosis), Phenotype, Prognosis, Prospective Studies, REM Sleep Behavior Disorder (complications), REM Sleep Behavior Disorder (diagnosis), Severity of Illness Index.
- MESH :
- classification : Parkinson Disease.
- complications : Cognitive Dysfunction, Parkinson Disease, REM Sleep Behavior Disorder.
- diagnosis : Cognitive Dysfunction, Parkinson Disease, REM Sleep Behavior Disorder.
- Aged, Disease Progression, Female, Follow-Up Studies, Humans, Male, Middle Aged, Phenotype, Prognosis, Prospective Studies, Severity of Illness Index.
Abstract
There is increasing evidence that Parkinson disease (PD) is heterogeneous in its clinical presentation and prognosis. Defining subtypes of PD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies.
DOI: 10.1001/jamaneurol.2015.0703
PubMed: 26076039
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pubmed:26076039Le document en format XML
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<front><div type="abstract" xml:lang="en">There is increasing evidence that Parkinson disease (PD) is heterogeneous in its clinical presentation and prognosis. Defining subtypes of PD is needed to better understand underlying mechanisms, predict disease course, and eventually design more efficient personalized management strategies.</div>
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