scholarly journals Subjective cognitive and motoric complaints as predictors of motoric cognitive risk syndrome

2021 ◽  
Vol 17 (S10) ◽  
Author(s):  
Emmeline Ayers ◽  
Joe Verghese
Keyword(s):  
2006 ◽  
Author(s):  
Andrew J. Cook ◽  
Douglas E. DeGood
Keyword(s):  

2021 ◽  
Vol 79 (1) ◽  
pp. 401-414
Author(s):  
Max Toepper ◽  
Philipp Schulz ◽  
Thomas Beblo ◽  
Martin Driessen

Background: On-road driving behavior can be impaired in older drivers and particularly in drivers with mild cognitive impairment (MCI). Objective: To determine whether cognitive and non-cognitive risk factors for driving safety may allow an accurate and economic prediction of on-road driving skills, fitness to drive, and prospective accident risk in healthy older drivers and drivers with MCI, we examined a representative combined sample of older drivers with and without MCI (N = 74) in an observational on-road study. In particular, we examined whether non-cognitive risk factors improve predictive accuracy provided by cognitive factors alone. Methods: Multiple and logistic hierarchical regression analyses were utilized to predict different driving outcomes. In all regression models, we included cognitive predictors alone in a first step and added non-cognitive predictors in a second step. Results: Results revealed that the combination of cognitive and non-cognitive risk factors significantly predicted driving skills (R2adjusted = 0.30) and fitness to drive (81.2% accuracy) as well as the number (R2adjusted = 0.21) and occurrence (88.3% accuracy) of prospective minor at-fault accidents within the next 12 months. In all analyses, the inclusion of non-cognitive risk factors led to a significant increase of explained variance in the different outcome variables. Conclusion: Our findings suggest that a combination of the most robust cognitive and non-cognitive risk factors may allow an economic and accurate prediction of on-road driving performance and prospective accident risk in healthy older drivers and drivers with MCI. Therefore, non-cognitive risk factors appear to play an important role.


Author(s):  
Ilaria Bortone ◽  
Chiara Griseta ◽  
Petronilla Battista ◽  
Fabio Castellana ◽  
Luisa Lampignano ◽  
...  

2021 ◽  
pp. 1-14
Author(s):  
Helena M. Blumen ◽  
Emily Schwartz ◽  
Gilles Allali ◽  
Olivier Beauchet ◽  
Michele Callisaya ◽  
...  

Background: The motoric cognitive risk (MCR) syndrome is a pre-clinical stage of dementia characterized by slow gait and cognitive complaint. Yet, the brain substrates of MCR are not well established. Objective: To examine cortical thickness, volume, and surface area associated with MCR in the MCR-Neuroimaging Consortium, which harmonizes image processing/analysis of multiple cohorts. Methods: Two-hundred MRIs (M age 72.62 years; 47.74%female; 33.17%MCR) from four different cohorts (50 each) were first processed with FreeSurfer 6.0, and then analyzed using multivariate and univariate general linear models with 1,000 bootstrapped samples (n-1; with resampling). All models adjusted for age, sex, education, white matter lesions, total intracranial volume, and study site. Results: Overall, cortical thickness was lower in individuals with MCR than in those without MCR. There was a trend in the same direction for cortical volume (p = 0.051). Regional cortical thickness was also lower among individuals with MCR than individuals without MCR in prefrontal, insular, temporal, and parietal regions. Conclusion: Cortical atrophy in MCR is pervasive, and include regions previously associated with human locomotion, but also social, cognitive, affective, and motor functions. Cortical atrophy in MCR is easier to detect in cortical thickness than volume and surface area because thickness is more affected by healthy and pathological aging.


2021 ◽  
pp. 111362
Author(s):  
Reshma Aziz Merchant ◽  
Yiong Huak Chan ◽  
Richard Jor Yeong Hui ◽  
Chris Tung Tsoi ◽  
Sing Cheer Kwek ◽  
...  

2020 ◽  
pp. 135910532093419
Author(s):  
Sydney C Timmer-Murillo ◽  
Joshua C Hunt ◽  
Timothy Geier ◽  
Karen J Brasel ◽  
Terri A deRoon-Cassini

The current study examined how the injured trauma survivor screen (ITSS), a hospital-administered screener of posttraumatic stress disorder (PTSD) and depression, differentially predicted PTSD symptom cluster severity. Participants from a Level 1 trauma center ( n = 220) completed the ITSS while inpatient and PTSD symptoms were assessed one-month post discharge. Perceived life threat and intentionality of injury were key predictors of avoidance, re-experiencing, and hyperarousal symptom clusters. However, negative alterations in mood and cognition cluster seemed best predicted by mood and cognitive risk factors. Therefore, the ITSS provides utility in differentially predicting symptom clusters and treatment planning after traumatic injury.


1993 ◽  
Vol 70 (1-2) ◽  
pp. 13-27 ◽  
Author(s):  
Keith H. Claypoole ◽  
Brenda D. Townes ◽  
Ann C. Collier ◽  
Christina Marra ◽  
W. T. Longstreth ◽  
...  

2017 ◽  
Vol 4 ◽  
Author(s):  
Jagadish K. Chhetri ◽  
Piu Chan ◽  
Bruno Vellas ◽  
Matteo Cesari

2003 ◽  
Vol 17 (4) ◽  
pp. 347-358 ◽  
Author(s):  
Jennifer A. Steinberg ◽  
Brandon E. Gibb ◽  
Lauren B. Alloy ◽  
Lyn Y. Abramson

Previous work has established a relationship between reports of childhood emotional maltreatment and cognitive vulnerability to depression, as well as an association between cognitive vulnerability and self-referent information-processing biases. Findings from this study of individuals at low (LR) and high (HR) cognitive risk for depression revealed a relationship between reports of childhood emotional maltreatment and current information processing biases. Specifically, individuals with greater childhood emotional maltreatment exhibited more negative self-referent information processing. Moreover, cognitive risk mediated the relationship between childhood emotional maltreatment and these information-processing biases. Testing an alternate model, information-processing biases also mediated the relationship between childhood emotional maltreatment and cognitive risk.


Sign in / Sign up

Export Citation Format

Share Document