Standard Neuropsychological Tests Research Articles

Validation of the European Cross-Cultural Neuropsychological Test Battery (CNTB) for the assessment of mild cognitive impairment due to Alzheimer's disease and Parkinson's disease.

The Cross-Cultural Neuropsychological Test Battery (CNTB) is a novel test battery specifically designed to reduce the impact of multiculturality in cognitive assessment. We aimed to validate the CNTB in Spaniards in patients with Alzheimer's disease (AD), including patients at mild cognitive impairment (MCI) and mild dementia stages, and Parkinson's disease with MCI (PD-MCI). Thirty patients with AD-MCI, 30 with AD-dementia (AD-D), and 30 with PD-MCI were recruited. Each clinical group was compared against a healthy control group (HC) with no differences in sex, age, or years of education. Intergroup comparisons, ROC analysis, and cut-off scores were calculated. AD-MCI scored lower than HC in those subtests associated with episodic memory and verbal fluency. AD-D also showed lower scores in executive functions and visuospatial tests. Effect sizes for all the subtests were large. PD-MCI showed lower performance than HC in memory and executive functions, particularly on error scores, with large effect sizes. Comparing AD-MCI and PD-MCI, AD-MCI had lower memory scores, while PD-MCI showed the worst performance in executive functions. CNTB showed appropriate convergent validity with standardized neuropsychological tests measuring the same cognitive domains. We obtained similar cut-off scores to previous studies performed in other populations. The CNTB showed appropriate diagnostic properties in AD and PD, including those stages with mild cognitive impairment. This supports the utility of the CNTB for the early detection of cognitive impairment in AD and PD.

Computerised cognitive assessment in patients with traumatic brain injury: an observational study of feasibility and sensitivity relative to established clinical scales.

Online technology could potentially revolutionise how patients are cognitively assessed and monitored. However, it remains unclear whether assessments conducted remotely can match established pen-and-paper neuropsychological tests in terms of sensitivity and specificity. This observational study aimed to optimise an online cognitive assessment for use in traumatic brain injury (TBI) clinics. The tertiary referral clinic in which this tool has been clinically implemented typically sees patients a minimum of 6 months post-injury in the chronic phase. Between March and August 2019, we conducted a cross-group, cross-device and factor analyses at the St. Mary's Hospital TBI clinic and major trauma wards at Imperial College NHS trust and St. George's Hospital in London (UK), to identify a battery of tasks that assess aspects of cognition affected by TBI. Between September 2019 and February 2020, we evaluated the online battery against standard face-to-face neuropsychological tests at the Imperial College London research centre. Canonical Correlation Analysis (CCA) determined the shared variance between the online battery and standard neuropsychological tests. Finally, between October 2020 and December 2021, the tests were integrated into a framework that automatically generates a results report where patients' performance is compared to a large normative dataset. We piloted this as a practical tool to be used under supervised and unsupervised conditions at the St. Mary's Hospital TBI clinic in London (UK). The online assessment discriminated processing-speed, visual-attention, working-memory, and executive-function deficits in TBI. CCA identified two significant modes indicating shared variance with standard neuropsychological tests (r=0.86, p<0.001 and r=0.81, p=0.02). Sensitivity to cognitive deficits after TBI was evident in the TBI clinic setting under supervised and unsupervised conditions (F (15,555)=3.99; p<0.001). Online cognitive assessment of TBI patients is feasible, sensitive, and efficient. When combined with normative sociodemographic models and autogenerated reports, it has the potential to transform cognitive assessment in the healthcare setting. This work was funded by a National Institute for Health Research (NIHR) Invention for Innovation (i4i) grant awarded to DJS and AH (II-LB-0715-20006).

Assessing cognitive changes in multiple sclerosis: criteria for a reliable decision

ABSTRACT Introduction Quantifying a significant cognitive change on a neuropsychological battery is essential to assess patients’ decline or recovery and offer appropriate care. The reliability of change indices is particularly important in multiple sclerosis (MS), as the course of cognitive impairment is quite unpredictable, due at least in part to substantial interindividual variability. The main objective of this study was to compare six different methods for assessing cognitive change in an MS sample: the SD method, two reliable change indices, two standardized regression-based methods (SRB), and the generalized regression-based method (GSRB). Method One hundred and twenty-three patients with clinically definite MS and 89 healthy controls underwent a battery of standardized neuropsychological tests assessing cognitive functions that are frequently affected in this disease (i.e., verbal episodic memory, working memory, processing speed and verbal fluency). Results We observed fairly similar proportions of improvement, decline or stability in the control group whatever the method. By contrast, in the MS sample, regression-based methods with one predictor (i.e., score at T1) and four predictors (i.e., score at T1 and demographic factors: age, sex, education level) detected a significant worsening more often than the reliable change indices while the GSRB method was more consistent with the RCI methods in tasks associated with ceiling effects. Conclusions The interpretation of a patient’s cognitive changes depends on which method is used. The (G)SRB methods appear to be relevant indicators for assessing cognitive change in MS. The addition of demographic factors does not seem to play an important role in the prediction of significant worsening in the MS sample, regardless of cognitive domain. For clinicians, an easy-to-use free shiny app is provided.

Neurological and (neuro)psychological sequelae in intensive care and general ward COVID-19 survivors.

Coronavirus disease 2019 (COVID-19) affects the brain, leading to long-term complaints. Studies combining brain abnormalities with objective and subjective consequences are lacking. Long-term structural brain abnormalities, neurological and (neuro)psychological consequences in COVID-19 patients admitted to the intensive care unit (ICU) or general ward were investigated. The aim was to create a multidisciplinary view on the impact of severe COVID-19 on functioning and to compare long-term consequences between ICU and general ward patients. This multicentre prospective cohort study assessed brain abnormalities (3 T magnetic resonance imaging), cognitive dysfunction (neuropsychological test battery), neurological symptoms, cognitive complaints, emotional distress and wellbeing (self-report questionnaires) in ICU and general ward (non-ICU) survivors. In al, 101 ICU and 104 non-ICU patients participated 8-10 months post-hospital discharge. Significantly more ICU patients exhibited cerebral microbleeds (61% vs. 32%, p < 0.001) and had higher numbers of microbleeds (p < 0.001). No group differences were found in cognitive dysfunction, neurological symptoms, cognitive complaints, emotional distress or wellbeing. The number of microbleeds did not predict cognitive dysfunction. In the complete sample, cognitive screening suggested cognitive dysfunction in 41%, and standard neuropsychological testing showed cognitive dysfunction in 12%; 62% reported ≥3 cognitive complaints. Clinically relevant scores of depression, anxiety and post-traumatic stress were found in 15%, 19% and 12%, respectively; 28% experienced insomnia and 51% severe fatigue. Coronavirus disease 2019 ICU survivors had a higher prevalence for microbleeds but not for cognitive dysfunction compared to general ward survivors. Self-reported symptoms exceeded cognitive dysfunction. Cognitive complaints, neurological symptoms and severe fatigue were frequently reported in both groups, fitting the post-COVID-19 syndrome.

Biological, Psychiatric, Psychosocial, and Cognitive Factors of Poststroke Depression

Depression is the most common psychiatric condition that occurs after cerebrovascular accident, especially within the first year after stroke. Poststroke depression (PSD) may occur due to environmental factors such as functional limitations in daily activities, lower quality of life, or biological factors such as damage to areas in the brain involved in emotion regulation. Although many factors are hypothesized to increase the risk of PSD, the relative contribution of these factors is not well understood. We evaluated which cross-sectional variables were associated with increased odds of PSD in our adult outpatient stroke neuropsychology clinic population. The sample included 325 patients (49.2% female; mean age of 59-years old) evaluated at an average of 8.1 months after an ischemic or hemorrhagic stroke. Variables included in logistic regression were stroke characteristics, demographics, psychosocial factors, comorbid medical problems, comorbid psychiatric conditions, and cognitive status. The Mini International Neuropsychiatric Inventory was used to determine DSM-defined PSD and anxiety disorders. A standard neuropsychological test battery was administered. PSD occurred in 30.8% of the sample. Logistic regression indicated that increased odds of PSD were associated with a comorbid anxiety disorder (5.9 times more likely to suffer from PSD, p < 0.001). Further, increased odds of PSD were associated with a history of depression treatment before stroke (3.0 times more likely to suffer from PSD), fatigue (2.8 times more likely), memory impairment (2.4 times more likely), and younger age at stroke (all p values < 0.006). Results suggest that PSD is likely multifactorial and extends the literature by demonstrating that a comorbid anxiety disorder correlated strongest with PSD. Poststroke screening and treatment plans should address not only depression but comorbid anxiety.

Cognitive function is mediated by deficit accumulation in older, long-term breast cancer survivors.

This study aims to examine whether cognitive function in older, long-term breast cancer survivors is both a direct effect of cancer and cancer treatments and an indirect effect mediated by deficit accumulation. Female breast cancer survivors who had been diagnosed and treated at age 60 or older and were 5-15-year survivors (N = 220) and age- and education-matched non-cancer controls (N = 123) were assessed at enrollment and at 8-, 16-, and 24-month follow-ups with standard neuropsychological tests and the comprehensive geriatric assessment which was used to calculate the deficit accumulation frailty index (DAFI). Blood or saliva samples for APOE genotyping were collected at enrollment. Participants were purposely recruited so that approximately 50% had a history of treatment with chemotherapy or and 50% were not exposed to chemotherapy. Latent variable mediation analysis revealed that cognitive performance was mediated by deficit accumulation for all three domains. The direct effect of cancer diagnosis and treatment history was significant for the Language domain (p = 0.04), a trend for the learning and memory domain (p = 0.054), and non-significant for the attention, processing speed, executive function (APE) domain. Carrying the APOE ε4 allele had a significant negative direct effect on the APE domain (p = 0.05) but no indirect effect through deficit accumulation. Cognitive function in older, long-term breast cancer survivors appears to be primarily mediated through deficit accumulation. These findings have important clinical implications suggesting that the most effective intervention to prevent or slow cognitive aging in older cancer survivors may be through prevention or management of comorbidities and interventions that maintain functional capacity (exercise, physical therapy) and social and mental health.

Higher hippocampal diffusivity values in welders are associated with greater R2* in the red nucleus and lower psychomotor performance

IntroductionChronic excessive welding exposure may be related to higher metal accumulation and structural differences in different subcortical structures. We examined how welding affected brain structures and their associations with metal exposure and neurobehavioral consequences. MethodsStudy includes 42 welders and 31 controls without a welding history. Welding-related structural differences were assessed by volume and diffusion tensor imaging (DTI) metrics in basal ganglia, red nucleus (RN), and hippocampus. Metal exposure was estimated by both exposure questionnaires and whole blood metal levels. Brain metal accumulations were estimated by R1 (for Mn) and R2* (for Fe). Neurobehavioral status was assessed by standard neuropsychological tests. ResultsCompared to controls, welders displayed higher hippocampal mean (MD), axial (AD), and radial diffusivity (RD) (p’s < 0.036), but similar DTI or volume in other ROIs (p’s > 0.117). Welders had higher blood metal levels (p’s < 0.004), higher caudate and RN R2* (p’s < 0.014), and lower performance on processing/psychomotor speed, executive function, and visuospatial processing tasks (p’s < 0.046). Higher caudate and RN R2* were associated with higher blood Fe and Pb (p’s < 0.043), respectively. RN R2* was a significant predictor of all hippocampal diffusivity metrics (p’s < 0.006). Higher hippocampal MD and RD values were associated with lower Trail Making Test-A scores (p’s < 0.025). A mediation analysis of both groups revealed blood Pb indirectly affected hippocampal diffusivity via RN R2* (p’s < 0.041). DiscussionWelding-related higher hippocampal diffusivity metrics may be associated with higher RN R2* and lower psychomotor speed performance. Future studies are warranted to test the role of Pb exposure in these findings.

Lower visual processing speed relates to greater subjective cognitive complaints in community-dwelling healthy older adults.

Subjective cognitive complaints in older age may reflect subtle objective impairments in basic cognitive functions that might foreshadow broader cognitive problems. Such cognitive functions, however, are not captured by standard neuropsychological testing. Visual processing speed is a basic visual attention function that underlies the performance of cognitive tasks relying on visual stimuli. Here, we test the hypothesis that lower visual processing speed correlates with greater subjective cognitive complaints in healthy older adults from the community. To do so, we assessed a sample of 30 healthy, cognitively normal older adults (73.07 ± 7.73 years old; range: 60-82; 15 females) with respect to individual subjective cognitive complaints and visual processing speed. We quantified the degree of subjective cognitive complaints with two widely-used questionnaires: the Memory Functioning Questionnaire and the Everyday Cognition. We used verbal report tasks and the theory of visual attention to estimate a visual processing speed parameter independently from motor speed and other visual attention parameters, i.e., visual threshold, visual short-term memory storage capacity, top-down control, and spatial weighting. We found that lower visual processing speed correlated with greater subjective complaints and that this relationship was not explained by age, education, or depressive symptoms. The association with subjective cognitive complaints was specific to visual processing speed, as it was not observed for other visual attention parameters. These results indicate that subjective cognitive complaints reflect a reduction in visual processing speed in healthy older adults. Together, our results suggest that the combined assessment of subjective cognitive complaints and visual processing speed has the potential to identify individuals at risk for cognitive impairment before the standard tests show any abnormal results.

Vascular comorbidity is associated with decreased cognitive functioning in inflammatory bowel disease

Reports of cognitive impairment in inflammatory bowel disease (IBD) have been mixed. IBD and cardiovascular disease are often co-morbid, yet it remains unknown whether vascular comorbidity confers a risk for decreased cognitive functioning, as observed in other populations. Participants with IBD were recruited from a longitudinal study of immune-mediated disease. Participants were administered a standardized neuropsychological test protocol, evaluating information processing speed, verbal learning and memory, visual learning and memory, and verbal fluency/executive function. Cognitive test scores were standardized using local regression-based norms, adjusting for age, sex, and education. Vascular risk was calculated using a modified Framingham Risk Score (FRS). We tested the association between FRS and cognitive test scores using a quantile regression model, adjusting for IBD type. Of 84 IBD participants, 54 had ulcerative colitis and 30 had Crohn’s disease; mean (SD) age was 53.36 (13.95) years, and a high proportion were females (n = 58). As the risk score (FRS) increased, participants demonstrated lower performance in information processing speed (β = − 0.12; 95% CI − 0.24, − 0.006) and verbal learning (β = − 0.14; 95% CI − 0.28, − 0.01) at the 50th percentile. After adjusting for IBD type and disease activity, higher FRS remained associated with lower information processing speed (β = − 0.14; 95% CI − 0.27, − 0.065). Vascular comorbidity is associated with lower cognitive functioning in persons with IBD, particularly in the area of information processing speed. These findings suggest that prevention, identification, and treatment of vascular comorbidity in IBD may play a critical role for improving functional outcomes in IBD.

Development of a home-based cognitive test for cognitive monitoring in subjective cognitive decline with high risk of Alzheimer's disease.

Subjective cognitive decline (SCD) indicates a self-perceived persistent cognitive worsening despite of normal performance in standard neuropsychological tests. Owing to its heterogeneity and potential risk of Alzheimer's disease, baseline biomarkers to predict cognitive decline are important. In the present study, we developed a home-based cognitive test (HCT) to monitor cognitive changes regularly without visiting hospitals. This study aims to compare cognitive and biomarker trajectories during a 48-month period between amyloid positive SCD and amyloid negative SCD subjects. Data will be collected from a prospective observational cohort study conducted in South Korea. Eighty participants with SCD aged ≥ 60 years are eligible for the study. All participants undergo annual neuropsychological tests and neurological examinations, bi-annual brain MRI scans and plasma amyloid markers, and baseline florbetaben Positron Emission Tomography scans. The amyloid burden and regional volumes will be measured. Cognitive and biomarker changes will be compared between the amyloid-positive SCD and amyloid negative SCD groups. Validation would be performed to assess reliability and feasibility of HCT. This study would suggest a perspective on SCD in terms of cognitive and biomarker trajectories. Baseline characteristics and biomarker status might affect faster cognitive decline and future biomarker trajectories. In addition, HCT could be an alternative option of in-person neuropsychological tests to track cognitive changes without visiting hospitals.

Binary classification threatens the validity of cognitive impairment detection.

Neuropsychological literature reports varying prevalence of cognitive impairment within patient populations, despite assessment with standardized neuropsychological tests. Within the domain of oncology, the International Cognition and Cancer Task Force (ICCTF) proposed standard cutoff points to harmonize the operationalization of cognitive impairment. We evaluated how this binary classification affects agreement between two highly comparable test batteries. Two hundred non-central nervous system (non-CNS) cancer patients who finished treatment (56% females; median age 53 yrs) completed traditional tests and their online equivalents in a counterbalanced design. Following ICCTF standards, impairment was defined as a score of ≥ 1.5 standard deviations (SDs) below normative means on two tests and/or ≥ 2 SDs below normative means on one test. Agreement of classification between traditional and online assessment was evaluated using Cohen's κ. Additional Monte Carlo simulations were conducted to demonstrate how different cutoff points and test characteristics affect agreement. The correlation between total scores of traditional and online assessment was .78. Proportions of impaired patients did not differ between assessment methods: 40% using traditional tests and 38% using online equivalents, χ²(1) = .17, p < .68. Nevertheless, within-person agreement in impairment classification between traditional and online assessment was merely fair (K = .35). Monte Carlo simulations showed similarly low agreement scores (K = .41 for 1.5 SD; K = .33 for 2 SD criterion). Our results show that binary classification can lead to a situation where two highly similar batteries fail to identify the same individuals as impaired. Additional simulations suggest that within-person agreement between assessment methods using binary classification is inherently low. Modern statistical tools may help to improve validity of impairment detection. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The association of subjective sleep characteristics and plasma biomarkers of Alzheimer's disease pathology in older cognitively unimpaired adults with higher amyloid-β burden.

We aimed to investigate the association of subjective sleep characteristics and plasma Alzheimer's disease (AD) biomarkers in older cognitively unimpaired adults with higher amyloid-β (Aβ) burden. Unimpaired cognition was determined by education-adjusted performance for the Mini-Mental State Examination and exclusion of dementia and mild cognitive impairment via standardized neuropsychological tests. We used Pittsburgh Sleep Quality Index (PSQI) to assess subjective sleep quality. The participants also underwent examination of plasma AD biomarkers and 18F-florbetapir PET scan. Correlation and multiple linear regression analyses were used to investigate the association between subjective sleep characteristics and AD biomarkers. A total of 335 participants were included and 114 were Aβ-PET positive. Multivariable regression analysis showed sleep duration > 8h and sleep disturbance were associated with Aβ deposition in total participants. Two multiple linear regression models were applied and the results revealed in participants with Aβ-PET (+), falling asleep at ≥ 22:00 to ≤ 23:00 was associated with higher levels of Aβ42 and Aβ42/40. Other associations with higher Aβ42/40 and standard uptake value ratio contained sleep efficiency value, sleep efficiency ≥ 75%, no/mild daytime dysfunction and PSQI score ≤ 5. Higher p-Tau-181 level was associated with sleep latency > 30min in Aβ-PET (+) group and moderate/severe sleep disturbance in Aβ-PET (-) group. Our data suggests sleep duration ≤ 8h and no/mild sleep disturbance may be related to less Aβ burden. In participants with Aβ deposition, falling asleep at 22:00 to 23:00, higher sleep efficiency (at least ≥ 75%), no/mild daytime dysfunction, sleep latency ≤ 30min, and good sleep quality may help improve AD pathology.

Exercise Associated with Cognitive Function in Older Men with Prostate Cancer Undergoing Androgen Deprivation Therapy.

To examine associations between exercise and cognitive function in older men undergoing hormone therapy for prostate cancer. Men ≥ 65years old with prostate cancer, currently undergoing androgen deprivation therapy for ≥ 6months (n = 50), completed the Godin-Shephard Leisure-Time Physical Activity Questionnaire, and standard neuropsychological tests. Pearson's correlations and linear regressions were used to examine associations between exercise and cognitive performance. Exercise was significantly positively correlated with performance on tests of memory, attention, and executive function. Linear regressions showed that when controlling for age and education, exercise remained a significant predictor of attention and executive function performance (p < 0.05), and showed moderate, but statistically non-significant effects on memory performance (p < 0.10). Greater exercise is associated with better functioning in multiple cognitive domains in men with prostate cancer undergoing hormone therapy, providing proof-of-concept evidence that exercise may be a feasible intervention to limit cognitive dysfunction in prostate cancer patients.

Effects of prism adaptation and visual scanning training on perceptual and response bias in unilateral spatial neglect

ABSTRACT In some patients with unilateral spatial neglect, symptoms reflect impaired lateralized spatial attention and representation (perceptual bias) whereas in others the inability to respond to stimuli located in contralesional space (response bias). Here, we investigated whether prismatic adaptation (PA) and visual scanning training (VST) differentially affect perceptual and response bias and whether rehabilitation outcome depends on the type of bias underlying symptoms. Two groups of neglect patients in the subacute phase were evaluated before, immediately after, and two weeks following 10 days of PA (n = 9) or VST (n = 9). Standard neuropsychological tests (i.e., Behavioural Inattentional Test, Diller cancellation test, and Line Bisection test) were administered to assess neglect symptoms, while the Landmark task was used to disentangle perceptual and response biases. Performance on the Landmark task revealed that PA was more effective in improving the perceptual bias, while VST mainly modulated the response bias. Neuropsychological tests performance suggested that VST is better suited to modulate neglect in patients with response bias, while PA may be effective in patients with both types of bias. These findings may offer novel insights into the efficacy of PA and VST in the rehabilitation of perceptual and response biases in patients with neglect.

Multi-Disease Validation of the RUDAS for Cognitive Screening in Alzheimer's Disease, Parkinson's Disease, and Multiple Sclerosis.

The Rowland Universal Dementia Assessment Scale (RUDAS) is a cognitive test with favorable diagnostic properties for detecting dementia and a low influence of education and cultural biases. We aimed to validate the RUDAS in people with Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS). We enrolled one hundred and fifty participants (60 with AD, 30 with PD, 60 with MS, and 120 healthy controls (HC)). All clinical groups completed a comprehensive neuropsychological battery, RUDAS, and standard cognitive tests of each disorder: MMSE, SCOPA-COG, and Symbol Digit Modalities Test. Intergroup comparisons between clinical groups and HC and ROC curves were estimated. Random Forest algorithms were trained and validated to detect cognitive impairment using RUDAS and rank the most relevant scores. The RUDAS scores were lower in patients with AD, and patients with PD and MS showed cognitive impairment compared to healthy controls. Effect sizes were generally large. The total score was the most discriminative, followed by the memory score. Correlations with standardized neuropsychological tests were moderate to high. Random Forest algorithms obtained accuracies over 80-90% using the RUDAS for diagnosing AD and cognitive impairment associated with PD and MS. Our results suggest the RUDAS is a valid test candidate for multi-disease cognitive screening tool in AD, PD, and MS.

Hybridized Deep Learning Approach for Detecting Alzheimer's Disease.

Alzheimer's disease (AD) is mainly a neurodegenerative sickness. The primary characteristics are neuronal atrophy, amyloid deposition, and cognitive, behavioral, and psychiatric disorders. Numerous machine learning (ML) algorithms have been investigated and applied to AD identification over the past decades, emphasizing the subtle prodromal stage of mild cognitive impairment (MCI) to assess critical features that distinguish the disease's early manifestation and instruction for early detection and treatment. Identifying early MCI (EMCI) remains challenging due to the difficulty in distinguishing patients with cognitive normality from those with MCI. As a result, most classification algorithms for these two groups perform poorly. This paper proposes a hybrid Deep Learning Approach for the early detection of Alzheimer's disease. A method for early AD detection using multimodal imaging and Convolutional Neural Network with the Long Short-term memory algorithm combines magnetic resonance imaging (MRI), positron emission tomography (PET), and standard neuropsychological test scores. The proposed methodology updates the learning weights, and Adam's optimization is used to increase accuracy. The system has an unparalleled accuracy of 98.5% in classifying cognitively normal controls from EMCI. These results imply that deep neural networks may be trained to automatically discover imaging biomarkers indicative of AD and use them to identify the illness accurately.

Validation of the cross-cultural dementia screening test in Alzheimer's disease and Parkinson's disease.

The Cross-Cultural Dementia (CCD) is a new screening tool to evaluate cognitive impairment based on a cross-cultural perspective to reduce the bias of education, and language and cultural differences. We aimed to evaluate the diagnostic properties of the CCD in Spaniards for the assessment of patients with Alzheimer's disease in mild cognitive impairment (AD-MCI) and mild dementia stages (AD-D) and patients with mild cognitive impairment associated with Parkinson's disease (PD-MCI). Sixty participants with AD (50% MCI) and thirty with PD-MCI were enrolled. Each clinical group was compared against a healthy control group (HC) with the same number of participants and no significant differences in age, education, and sex. A comprehensive neuropsychological test battery and CCD were completed. Intergroup comparisons, ROC curves, and cut-off scores were calculated for the study of diagnostic properties. Intergroup differences were found in accordance with the cognitive profile of each clinical condition. Memory measures (Objects test) were especially relevant for the classification between AD and HC. Memory and executive function scores (Sun-Moon and Dots tests) were useful in the case of PD-MCI and HC. Furthermore, CCD described differences in executive functions and speed scores comparing AD-MCI and PD-MCI. Correlations between standardized neuropsychological tests and CCD measures supported the convergent validity of the test. CCD showed good discrimination properties and cut-off scores for dementia and extended its application to a sample of prodromal stages of AD and PD with mild cognitive impairment.

Driving Assessment for Persons with Dementia: How and when?

Dementia is a progressive neurodegenerative disease leading to deterioration in cognitive and physical skills. Driving is an important instrumental activity of daily living, essential for independence. However, this is a complex skill. A moving vehicle can be a dangerous tool in the hand of someone who cannot maneuver it properly. As a result, the assessment of driving capacity should be part of the management of dementia. Moreover, dementia comprises of different etiologies and stages consisting of different presentations. As a result, this study aims to identify driving behaviors common in dementia and compare different assessment methods. A literature search was conducted using the PRISMA checklist as a framework. A total of forty-four observational studies and four meta-analyses were identified. Study characteristics varied greatly with regards to methodology, population, assessments, and outcome measures used. Drivers with dementia performed generally worse than cognitively normal drivers. Poor speed maintenance, lane maintenance, difficulty managing intersections and poor response to traffic stimuli were the most common behaviors in drivers with dementia. Naturalistic driving, standardized road assessments, neuropsychological tests, participant self-rating and caregiver rating were the most common driving assessment methods used. Naturalistic driving and on-road assessments had the highest predictive accuracy. Results on other forms of assessments varied greatly. Both driving behaviors and assessments were influenced by different stages and etiologies of dementia at varying degrees. Methodology and results in available research are varied and inconsistent. As a result, better quality research is required in this field.

Brain microdialysate tau dynamics predict functional and neurocognitive recovery after poor-grade subarachnoid haemorrhage.

Subarachnoid haemorrhage is a devastating disease that results in neurocognitive deficits and a poor functional outcome in a considerable proportion of patients. In this study, we investigated the prognostic value of microtubule-associated tau protein measured in the cerebral microdialysate for long-term functional and neuropsychological outcomes in poor-grade subarachnoid haemorrhage patients. We recruited 55 consecutive non-traumatic subarachnoid haemorrhage patients who underwent multimodal neuromonitoring, including cerebral microdialysis. Mitochondrial dysfunction was defined as lactate-to-pyruvate ratio >30 together with pyruvate >70 mmol/L and metabolic distress as lactate-to-pyruvate ratio >40. The multidimensional 12-month outcome was assessed by means of the modified Rankin scale (poor outcome: modified Rankin scale ≥4) and a standardized neuropsychological test battery. We used multivariable generalized estimating equation models to assess associations between total microdialysate-tau levels of the first 10 days after admission and hospital complications and outcomes. Patients were 56 ± 12 years old and presented with a median Hunt & Hess score of 5 (interquartile range: 3-5). Overall mean total microdialysate-tau concentrations were highest within the first 24 h (5585 ± 6291 pg/mL), decreased to a minimum of 2347 ± 4175 pg/mL on Day 4 (P < 0.001) and remained stable thereafter (P = 0.613). Higher total microdialysate-tau levels were associated with the occurrence of delayed cerebral ischaemia (P = 0.001), episodes of metabolic distress (P = 0.002) and mitochondrial dysfunction (P = 0.034). Patients with higher tau levels had higher odds for a poor 12-month functional outcome (adjusted odds ratio: 2.61; 95% confidence interval: 1.32-5.17; P = 0.006) and impaired results in the trail making test-B (adjusted odds ratio: 3.35; 95% confidence interval: 1.16-9.68; P = 0.026) indicative of cognitive flexibility. Total microdialysate-tau levels significantly decreased over the first 10 days (P < 0.05) in patients without delayed cerebral ischaemia or good functional outcomes and remained high in those with delayed cerebral ischaemia and poor 12-month outcomes, respectively. Dynamic changes of total tau in the cerebral microdialysate may be a useful biomarker for axonal damage associated with functional and neurocognitive recovery in poor-grade subarachnoid haemorrhage patients. In contrast, ongoing axonal damage beyond Day 3 after bleeding indicates a higher risk for delayed cerebral ischaemia as well as a poor functional outcome.

Neuropathological Validation of the Alzheimer’s Questionnaire

AbstractBackgroundThe Alzheimer’s Questionnaire (AQ) is a brief, informant‐based screening tool that has demonstrated good diagnostic accuracy in identifying clinical Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI). The AQ has been further validated by its correlations with established informant‐ and performance‐based cognitive assessments as well as with standard neuropsychological tests. Recent evidence has also demonstrated that the AQ correlates well with PET‐based measures of amyloid plaque. The aim of this study is to validate the AQ with the hallmark neuritic plaque (NP) and neurofibrillary tangle (NFT) pathology of AD.MethodData from 205 prospectively‐followed autopsy cases classified as AD (n=90), aMCI (n=42), or cognitively unimpaired (CU, n=73) were used in this analysis. The average age at death was 87.07±7.84 years with the average interval between the last clinical assessment and death of 16.48±14.32 months. Semi‐quantitative measures of NP and NFT pathology from five brain regions were used to assess total plaque and total tangle loads which were then correlated with the AQ, Clinical Dementia Rating Sum of Boxes (CDR‐SOB), and the Mini‐Mental State Exam (MMSE). Spearman correlations were used in the primary analyses and were followed up with robust regression models that adjusted for age at death, sex, education, and APOE ε4 carrier status.ResultThe AQ correlated significantly with NP load (r=0.37, p&lt;0.001) and NFT load (r=0.57, p&lt;0.001). These associations remained significant after covariate adjustment (NP: β=0.28, 95% CI: (0.21, 0.34), p&lt;0.001; NFT: β=0.22, 95% CI: (0.17, 0.28), p&lt;0.001). The MMSE and CDR‐SOB showed similar correlations with NP load (r=‐0.37, r=0.35, respectively) and NFT load (r=‐0.58, r=0.55, respectively).ConclusionThese findings extend previous clinical and neuroimaging findings of the AQ showing that it correlates well with the hallmark NP and NFT pathology of AD and provide additional confidence to clinicians who use the AQ to screen for AD‐related cognitive impairment.