scholarly journals Risk of progression from subjective cognitive decline to mild cognitive impairment: The role of study setting

2018 ◽  
Vol 14 (6) ◽  
pp. 734-742 ◽  
Author(s):  
Beth E. Snitz ◽  
Tianxiu Wang ◽  
Yona Keich Cloonan ◽  
Erin Jacobsen ◽  
Chung-Chou H. Chang ◽  
...  
Author(s):  
Deepti Marchment ◽  
Dennis Chan

Mild cognitive impairment (MCI) is a descriptive term that in essence refers to the presence of cognitive impairment out of keeping with normal ageing but of insufficient severity to constitute dementia. Debate continues as to whether MCI represents a discrete syndrome, a transitional state, or a prodrome for a variety of neurodegenerative diseases: it is at present considered to be heterogeneous both in terms of clinical presentation and aetiology. This chapter outlines how the concept of MCI has evolved to its current form and summarizes its diagnostic criteria, epidemiology, prognosis, underlying aetiologies, and pathophysiology. It briefly covers related phenomena such as subjective cognitive decline and mild behavioural impairment. It explores the role of biomarkers and neuroimaging in investigating MCI in clinical and research settings and finally concludes with a proposed clinician’s approach to the diagnosis and management of MCI.


2019 ◽  
Vol 266 (2) ◽  
pp. 487-497 ◽  
Author(s):  
Salvatore Mazzeo ◽  
Sonia Padiglioni ◽  
Silvia Bagnoli ◽  
Laura Bracco ◽  
Benedetta Nacmias ◽  
...  

Author(s):  
Dylan J. Jester ◽  
Ross Andel ◽  
Katerina Cechová ◽  
Jan Laczó ◽  
Ondrej Lerch ◽  
...  

Abstract Objective: To compare cognitive phenotypes of participants with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI), estimate progression to MCI/dementia by phenotype and assess classification error with machine learning. Method: Dataset consisted of 163 participants with SCD and 282 participants with aMCI from the Czech Brain Aging Study. Cognitive assessment included the Uniform Data Set battery and additional tests to ascertain executive function, language, immediate and delayed memory, visuospatial skills, and processing speed. Latent profile analyses were used to develop cognitive profiles, and Cox proportional hazards models were used to estimate risk of progression. Random forest machine learning algorithms reported cognitive phenotype classification error. Results: Latent profile analysis identified three phenotypes for SCD, with one phenotype performing worse across all domains but not progressing more quickly to MCI/dementia after controlling for age, sex, and education. Three aMCI phenotypes were characterized by mild deficits, memory and language impairment (dysnomic aMCI), and severe multi-domain aMCI (i.e., deficits across all domains). A dose–response relationship between baseline level of impairment and subsequent risk of progression to dementia was evident for aMCI profiles after controlling for age, sex, and education. Machine learning more easily classified participants with aMCI in comparison to SCD (8% vs. 21% misclassified). Conclusions: Cognitive performance follows distinct patterns, especially within aMCI. The patterns map onto risk of progression to dementia.


2018 ◽  
Vol 15 (3) ◽  
pp. 219-228 ◽  
Author(s):  
Jiri Cerman ◽  
Ross Andel ◽  
Jan Laczo ◽  
Martin Vyhnalek ◽  
Zuzana Nedelska ◽  
...  

Background: Great effort has been put into developing simple and feasible tools capable to detect Alzheimer's disease (AD) in its early clinical stage. Spatial navigation impairment occurs very early in AD and is detectable even in the stage of mild cognitive impairment (MCI). Objective: The aim was to describe the frequency of self-reported spatial navigation complaints in patients with subjective cognitive decline (SCD), amnestic and non-amnestic MCI (aMCI, naMCI) and AD dementia and to assess whether a simple questionnaire based on these complaints may be used to detect early AD. Method: In total 184 subjects: patients with aMCI (n=61), naMCI (n=27), SCD (n=63), dementia due to AD (n=20) and normal controls (n=13) were recruited. The subjects underwent neuropsychological examination and were administered a questionnaire addressing spatial navigation complaints. Responses to the 15 items questionnaire were scaled into four categories (no, minor, moderate and major complaints). Results: 55% of patients with aMCI, 64% with naMCI, 68% with SCD and 72% with AD complained about their spatial navigation. 38-61% of these complaints were moderate or major. Only 33% normal controls expressed complaints and none was ranked as moderate or major. The SCD, aMCI and AD dementia patients were more likely to express complaints than normal controls (p's<0.050) after adjusting for age, education, sex, depressive symptoms (OR for SCD=4.00, aMCI=3.90, AD dementia=7.02) or anxiety (OR for SCD=3.59, aMCI=3.64, AD dementia=6.41). Conclusion: Spatial navigation complaints are a frequent symptom not only in AD, but also in SCD and aMCI and can potentially be detected by a simple and inexpensive questionnaire.


Author(s):  
Iván Galtier ◽  
Antonieta Nieto ◽  
María Mata ◽  
Jesús N. Lorenzo ◽  
José Barroso

ABSTRACT Objective: Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in Parkinson’s disease (PD) are considered as the risk factors for dementia (PDD). Posterior cortically based functions, such as visuospatial and visuoperceptual (VS-VP) processing, have been described as predictors of PDD. However, no investigations have focused on the qualitative analysis of the Judgment of Line Orientation Test (JLOT) and the Facial Recognition Test (FRT) in PD-SCD and PD-MCI. The aim of this work was to study the VS-VP errors in JLOT and FRT. Moreover, these variables are considered as predictors of PDD. Method: Forty-two PD patients and 19 controls were evaluated with a neuropsychological protocol. Patients were classified as PD-SCD and PD-MCI. Analyses of errors were conducted following the procedure described by Ska, Poissant, and Joanette (1990). Follow-up assessment was conducted to a mean of 7.5 years after the baseline. Results: PD-MCI patients showed a poor performance in JLOT and FRT total score and made a greater proportion of severe intraquadrant (QO2) and interquadrant errors (IQO). PD-SCD showed a poor performance in FRT and made mild errors in JLOT. PD-MCI and QO2/IQO errors were independent risk factors for PDD during the follow-up. Moreover, the combination of both PD-MCI diagnosis and QO2/IQO errors was associated with a greater risk. Conclusions: PD-MCI patients presented a greater alteration in VS-VP processing observable by the presence of severe misjudgments. PD-SCD patients also showed mild difficulties in VS-SP functions. Finally, QO2/IQO errors in PD-MCI are a useful predictor of PDD, more than PD-MCI diagnosis alone.


2021 ◽  
Author(s):  
Noel Valencia ◽  
Johann Lehrner

Summary Background Visuo-Constructive functions have considerable potential for the early diagnosis and monitoring of disease progression in Alzheimer’s disease. Objectives Using the Vienna Visuo-Constructional Test 3.0 (VVT 3.0), we measured visuo-constructive functions in subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD), and healthy controls to determine whether VVT performance can be used to distinguish these groups. Materials and methods Data of 671 participants was analyzed comparing scores across diagnostic groups and exploring associations with relevant clinical variables. Predictive validity was assessed using Receiver Operator Characteristic curves and multinomial logistic regression analysis. Results We found significant differences between AD and the other groups. Identification of cases suffering from visuo-constructive impairment was possible using VVT scores, but these did not permit classification into diagnostic subgroups. Conclusions In summary, VVT scores are useful indicators for visuo-constructive impairment but face challenges when attempting to discriminate between several diagnostic groups.


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