scholarly journals Predicting On-Road Driving Skills, Fitness to Drive, and Prospective Accident Risk in Older Drivers and Drivers with Mild Cognitive Impairment: The Importance of Non-Cognitive Risk Factors

2021 ◽  
Vol 79 (1) ◽  
pp. 401-414
Author(s):  
Max Toepper ◽  
Philipp Schulz ◽  
Thomas Beblo ◽  
Martin Driessen
Keyword(s):  
Risk Factors ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Older Drivers ◽  
Accident Risk ◽  
Fitness To Drive ◽  
Cognitive Predictors ◽  
Driving Skills ◽  
Cognitive Risk ◽  
Cognitive Risk Factors

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.

scholarly journals Presurgical Identification of Patients With Glioblastoma at Risk for Cognitive Impairment at 3-Month Follow-up

Neurosurgery ◽  
2020 ◽  
Author(s):  
Sophie J M Rijnen ◽  
Elke Butterbrod ◽  
Geert-Jan M Rutten ◽  
Margriet M Sitskoorn ◽  
Karin Gehring
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
Risk Factor ◽  
Cognitive Impairment ◽  
Regression Models ◽  
Cognitive Domains ◽  
Cognitive Risk ◽  
Postoperative Cognitive Impairment ◽  
Over Time ◽  
Cognitive Risk Factors

Abstract BACKGROUND Pre- and postoperative cognitive deficits have repeatedly been demonstrated in patients with glioblastoma (GBM). OBJECTIVE To identify presurgical risk factors that facilitate the identification of GBM patients at risk for postoperative cognitive impairment. METHODS Patients underwent neuropsychological assessment using Central Nervous System Vital Signs 1 d before (T0) and 3 mo after surgery (T3). Patients’ standardized scores on 7 cognitive domains were compared to a normative sample using one-sample z tests. Reliable change indices with correction for practice effects were calculated to assess cognitive changes in individual patients over time. Logistic regression models were performed to assess presurgical sociodemographic, clinical, psychological, and cognitive risk factors for postoperative cognitive impairments. RESULTS At T0, 208 patients were assessed, and 136 patients were retested at T3. Patients showed significantly lower performance both prior to and 3 mo after surgery on all cognitive domains compared to healthy controls. Improvements and declines over time occurred respectively in 11% to 32% and 6% to 26% of the GBM patients over the domains. The regression models showed that low preoperative cognitive performance posits a significant risk factor for postoperative cognitive impairment on all domains, and female sex was a risk factor for postoperative impairments in Visual Memory. CONCLUSION We demonstrated preoperative cognitive risk factors that enable the identification of GBM patients who are at risk for cognitive impairment 3 mo after surgery. This information can help to inform patients and clinicians at an early stage, and emphasizes the importance of recognizing, assessing, and actively dealing with cognitive functioning in the clinical management of GBM patients.

Elucidating the risk factors for progression from amyloid-negative amnestic mild cognitive impairment to dementia

2020 ◽  
Vol 17 ◽  
Author(s):  
Hyung-Ji Kim ◽  
Jae-Hong Lee ◽  
E-nae Cheong ◽  
Sung-Eun Chung ◽  
Sungyang Jo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Amnestic Mild Cognitive Impairment ◽  
Amyloid Pet ◽  
Clinical Progression ◽  
Amnestic Mci

Background: Amyloid PET allows for the assessment of amyloid β status in the brain, distinguishing true Alzheimer’s disease from Alzheimer’s disease-mimicking conditions. Around 15–20% of patients with clinically probable Alzheimer’s disease have been found to have no significant Alzheimer’s pathology on amyloid PET. However, a limited number of studies had been conducted this subpopulation in terms of clinical progression. Objective: We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI). Methods: This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloidnegative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET. Results: During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer’s disease-like pattern despite the lack of evidence for significant Alzheimer’s disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices. Conclusion: Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer’s diseasemimicking dementia are warranted.

scholarly journals Risk factors for developing dementia in type 2 diabetes mellitus patients with mild cognitive impairment

2019 ◽  
Vol Volume 15 ◽  
pp. 167-175 ◽  
Author(s):  
Oana Albai ◽  
Mirela Frandes ◽  
Romulus Timar ◽  
Deiana Roman ◽  
Bogdan Timar
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment

Analyses of Visuospatial and Visuoperceptual Errors as Predictors of Dementia in Parkinson’s Disease Patients with Subjective Cognitive Decline and Mild Cognitive Impairment

2020 ◽  
pp. 1-11
Author(s):  
Iván Galtier ◽  
Antonieta Nieto ◽  
María Mata ◽  
Jesús N. Lorenzo ◽  
José Barroso
Keyword(s):  
Risk Factors ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Poor Performance ◽  
Subjective Cognitive Decline ◽  
Independent Risk Factors

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.

scholarly journals Association between ApoE ε4 Carrier Status and Cardiovascular Risk Factors on Mild Cognitive Impairment among Mexican Older Adults

2021 ◽  
Vol 11 (1) ◽  
pp. 68
Author(s):  
Sara G. Aguilar-Navarro ◽  
Itzel I. Gonzalez-Aparicio ◽  
José Alberto Avila-Funes ◽  
Teresa Juárez-Cedillo ◽  
Teresa Tusié-Luna ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Cognitive Impairment ◽  
Cardiovascular Risk ◽  
Mild Cognitive Impairment ◽  
Cardiovascular Risk Factors ◽  
Apoe Genotype ◽  
Carrier Status ◽  
Apoe Ε4 ◽  
Increased Risk

Mild cognitive impairment (MCI) (amnestic or non-amnestic) has different clinical and neuropsychological characteristics, and its evolution is heterogeneous. Cardiovascular risk factors (CVRF), such as hypertension, diabetes, or dyslipidemia, and the presence of the Apolipoprotein E ε4 (ApoE ε4) polymorphism have been associated with an increased risk of developing Alzheimer’s disease (AD) and other dementias but the relationship is inconsistent worldwide. We aimed to establish the association between the ApoE ε4 carrier status and CVRF on MCI subtypes (amnestic and non-amnestic) in Mexican older adults. Cross-sectional study including 137 older adults (n = 63 with normal cognition (NC), n = 24 with amnesic, and n = 50 with non-amnesic MCI). Multinomial logistic regression models were performed in order to determine the association between ApoE ε4 polymorphism carrier and CVRF on amnestic and non-amnestic-MCI. ApoE ε4 carrier status was present in 28.8% participants. The models showed that ApoE ε4 carrier status was not associated neither aMCI nor naMCI condition. The interaction term ApoE ε4 × CVRF was not statistically significant for both types of MCI. However, CVRF were associated with both types of MCI and the association remained statistically significant after adjustment by sex, age, and education level. The carrier status of the ApoE genotype does not contribute to this risk.

Cognitive Risk Factors and Neuropsychological Performance in HIV Infection

1993 ◽  
Vol 70 (1-2) ◽  
pp. 13-27 ◽  
Author(s):  
Keith H. Claypoole ◽  
Brenda D. Townes ◽  
Ann C. Collier ◽  
Christina Marra ◽  
W. T. Longstreth ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hiv Infection ◽  
Neuropsychological Performance ◽  
Cognitive Risk ◽  
Cognitive Risk Factors

scholarly journals Development of a Sex-Specific Risk Scoring System for Predicting Cognitive Normal to Mild Cognitive Impairment (SRSS-CNMCI)

2021 ◽  
Author(s):  
Wen Luo ◽  
Hao Wen ◽  
Shuqi Ge ◽  
Chunzhi Tang ◽  
Xiufeng Liu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
High Risk ◽  
Scoring System ◽  
External Validation ◽  
Scoring Systems ◽  
Cutoff Point ◽  
Risk Scoring ◽  
Risk Scoring System

Abstract Objective: We aim to develop a sex-specific risk scoring system for predicting cognitive normal (CN) to mild cognitive impairment (MCI), abbreviated SRSS-CNMCI, to provide a reliable tool for the prevention of MCI.Methods: Participants aged 61-90 years old with a baseline diagnosis of CN and an endpoint diagnosis of MCI were screened from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database with at least one follow-up. Multivariable Cox proportional hazards models were used to identify risk factors associated with conversion from CN to MCI and to build risk scoring systems for male and female groups. Receiver operating characteristic (ROC) curve analysis was applied to determine the risk probability cutoff point corresponding to the optimal prediction effect. We ran an external validation of the discrimination and calibration based on the Harvard Aging Brain Study (HABS) database.Results: A total of 471 participants, including 240 women (51%) and 231 men (49%), aged 61 to 90 years, were included in the study cohort for subsequent primary analysis. The final multivariable models and the risk scoring systems for females and males included age, APOE ε4, Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR). The scoring systems for females and males revealed C statistics of 0.902 (95% CI 0.840-0.963) and 0.911 (95% CI 0.863-0.959), respectively, as measures of discrimination. The cutoff point of high and low risk was 33% in females, and more than 33% was considered high risk, while more than 9% was considered high risk for males. The external validation effect of the scoring systems was good: C statistic 0.950 for the females and C statistic 0.965 for the males. Conclusions: Our parsimonious model accurately predicts conversion from CN to MCI with four risk factors and can be used as a predictive tool for the prevention of MCI.

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