Meta-analysis of Montreal cognitive assessment diagnostic accuracy in amnestic mild cognitive impairment

BackgroundThe Montreal Cognitive Assessment (MoCA) is one of the most widely-used cognitive screening instruments and has been translated into several different languages and dialects. Although the original validation study suggested to use a cutoff of ≤26, subsequent studies have shown that lower cutoff values may yield fewer false-positive indications of cognitive impairment. The aim of this study was to summarize the diagnostic accuracy and mean difference of the MoCA when comparing cognitively unimpaired (CU) older adults to those with amnestic mild cognitive impairment (aMCI).MethodsPubMed and EMBASE databases were searched from inception to 22 February 2022. Meta-analyses for area under the curve (AUC) and standardized mean difference (SMD) values were performed.ResultsFifty-five observational studies that included 17,343 CU and 8,413 aMCI subjects were selected for inclusion. Thirty-nine studies were used in the AUC analysis while 44 were used in the SMD analysis. The overall AUC value was 0.84 (95% CI: 0.81, 0.87) indicating good diagnostic accuracy and a large effect size was noted for the SMD analysis (Hedge’s g = 1.49, 95% CI: 1.33, 1.64). Both analyses had high levels of between-study heterogeneity. The median cutoff score for identifying aMCI was <24.Discussion and conclusionThe MoCA has good diagnostic accuracy for detecting aMCI across several different languages. The findings of this meta-analysis also support the use of 24 as the optimal cutoff when the MoCA is used to screen for suspected cognitive impairment

Cognitive Composite Score Association With Alzheimer\u27S Disease Plaque And Tangle Pathology

Background: Cognitive composite scores are used as the primary outcome measures for Alzheimer\u27s disease (AD) prevention trials; however, the extent to which these composite measures correlate with AD pathology has not been fully investigated. Since many on-going AD prevention studies are testing therapies that target either amyloid or tau, we sought to establish an association between a cognitive composite score and the underlying pathology of AD. Methods: Data from 192 older deceased and autopsied persons from the Rush Religious Order Study were used in this study. All participants were classified at their initial evaluations with a clinical diagnosis of no cognitive impairment (NCI). Of these individuals, 105 remained NCI at the time of their death while the remaining 87 progressed to mild cognitive impairment (MCI) or AD. A cognitive composite score composed of eight cognitive tests was used as the outcome measure. Individuals were classified into groups based on Consortium to Establish a Registry for Alzheimer\u27s Disease (CERAD) neuropathological diagnosis and Braak stage. Results: The rate of annualized composite score decline was significantly greater for the high CERAD (p \u3c 0.001, d = 0.56) and Braak (p \u3c 0.001, d = 0.55) groups compared with the low CERAD and Braak groups, respectively. Mixed-model repeated measure (MMRM) analyses revealed a significantly greater difference in composite score change from baseline for the high CERAD group relative to the low CERAD group after 5 years (Δ = -2.74, 95% confidence interval (CI) -5.01 to -0.47; p = 0.02). A similar analysis between low and high Braak stage groups found no significant difference in change from baseline (Δ = -0.69, 95% CI -3.03 to 1.66; p = 0.56). Conclusions: These data provide evidence that decreased cognitive composite scores were significantly associated with increased AD pathology and provide support for the use of cognitive composite scores in AD prevention trials

Plasma NfL is associated with the APOE ε4 allele, brain imaging measurements of neurodegeneration, and lower recall memory scores in cognitively unimpaired late-middle-aged and older adults

BACKGROUND: Plasma neurofilament light (NfL) is an indicator of neurodegeneration and/or neuroaxonal injury in persons with Alzheimer's disease (AD) and a wide range of other neurological disorders. Here, we characterized and compared plasma NfL concentrations in cognitively unimpaired (CU) late-middle-aged and older adults with two, one, or no copies of the APOE ε4 allele, the major genetic risk factor for AD. We then assessed plasma NfL associations with brain imaging measurements of AD-related neurodegeneration (hippocampal atrophy and a hypometabolic convergence index [HCI]), brain imaging measurements of amyloid-β plaque burden, tau tangle burden and white matter hyperintensity volume (WMHV), and delayed and total recall memory scores. METHODS: Plasma NfL concentrations were measured in 543 CU 69 ± 9 year-old participants in the Arizona APOE Cohort Study, including 66 APOE ε4 homozygotes (HM), 165 heterozygotes (HT), and 312 non-carriers (NC). Robust regression models were used to characterize plasma NfL associations with APOE ε4 allelic dose before and after adjustment for age, sex, and education. They were also used to characterize plasma NfL associations with MRI-based hippocampal volume and WMHV measurements, an FDG PET-based HCI, mean cortical PiB PET measurements of amyloid-β plaque burden and meta-region-of-interest (meta-ROI) flortaucipir PET measurements of tau tangle burden, and Auditory Verbal Learning Test (AVLT) Delayed and Total Recall Memory scores. RESULTS: After the adjustments noted above, plasma NfL levels were significantly greater in APOE ε4 homozygotes and heterozygotes than non-carriers and significantly associated with smaller hippocampal volumes (r =  - 0.43), greater tangle burden in the entorhinal cortex and inferior temporal lobes (r = 0.49, r = 0.52, respectively), and lower delayed (r =  - 0.27), and total (r =  - 0.27) recall memory scores (p < 0.001). NfL levels were not significantly associated with PET measurements of amyloid-β plaque or total tangle burden. CONCLUSIONS: Plasma NfL concentrations are associated with the APOE ε4 allele, brain imaging biomarkers of neurodegeneration, and less good recall memory in CU late-middle-aged and older adults, supporting its value as an indicator of neurodegeneration in the preclinical study of AD

Application of robust regression in translational neuroscience studies with non-Gaussian outcome data

Linear regression is one of the most used statistical techniques in neuroscience, including the study of the neuropathology of Alzheimer’s disease (AD) dementia. However, the practical utility of this approach is often limited because dependent variables are often highly skewed and fail to meet the assumption of normality. Applying linear regression analyses to highly skewed datasets can generate imprecise results, which lead to erroneous estimates derived from statistical models. Furthermore, the presence of outliers can introduce unwanted bias, which affect estimates derived from linear regression models. Although a variety of data transformations can be utilized to mitigate these problems, these approaches are also associated with various caveats. By contrast, a robust regression approach does not impose distributional assumptions on data allowing for results to be interpreted in a similar manner to that derived using a linear regression analysis. Here, we demonstrate the utility of applying robust regression to the analysis of data derived from studies of human brain neurodegeneration where the error distribution of a dependent variable does not meet the assumption of normality. We show that the application of a robust regression approach to two independent published human clinical neuropathologic data sets provides reliable estimates of associations. We also demonstrate that results from a linear regression analysis can be biased if the dependent variable is significantly skewed, further indicating robust regression as a suitable alternate approach

A classification system for teachers’ motivational behaviors recommended in self-determination theory interventions

Teachers’ behavior is a key factor that influences students’ motivation. Many theoretical models have tried to explain this influence, with one of the most thoroughly researched being self-determination theory (SDT). We used a Delphi method to create a classification of teacher behaviors consistent with SDT. This is useful because SDT-based interventions have been widely used to improve educational outcomes. However, these interventions contain many components. Reliably classifying and labeling those components is essential for implementation, reproducibility, and evidence synthesis. We used an international expert panel (N = 34) to develop this classification system. We started by identifying behaviors from existing literature, then refined labels, descriptions, and examples using the Delphi panel’s input. Next, the panel of experts iteratively rated the relevance of each behavior to SDT, the psychological need that each behavior influenced, and its likely effect on motivation. To create a mutually exclusive and collectively exhaustive list of behaviors, experts nominated overlapping behaviors that were redundant, and suggested new ones missing from the classification. After three rounds, the expert panel agreed upon 57 teacher motivational behaviors (TMBs) that were consistent with SDT. For most behaviors (77%), experts reached consensus on both the most relevant psychological need and influence on motivation. Our classification system provides a comprehensive list of TMBs and consistent terminology in how those behaviors are labeled. Researchers and practitioners designing interventions could use these behaviors to design interventions, to reproduce interventions, to assess whether these behaviors moderate intervention effects, and could focus new research on areas where experts disagreed. (PsycInfo Database Record (c) 2023 APA, all rights reserved

A classification system for teachers’ motivational behaviors recommended in self-determination theory interventions.

Teachers’ behavior is a key factor that influences students’ motivation. Many theoretical models have tried to explain this influence, with one of the most thoroughly researched being self-determination theory (SDT). We used a Delphi method to create a classification of teacher behaviors consistent with SDT. This is useful because SDT-based interventions have been widely used to improve educational outcomes. However, these interventions contain many components. Reliably classifying and labeling those components is essential for implementation, reproducibility, and evidence synthesis.We used an international expert panel (N = 34) to develop this classification system. We started by identifying behaviors from existing literature, then refined labels, descriptions, and examples using the Delphi panel’s input. Next, the panel of experts iteratively rated the relevance of each behavior to SDT, the psychological need that each behavior influenced, and its likely effect on motivation. To create a mutually exclusive and collectively exhaustive list of behaviors, experts nominated overlapping behaviors that were redundant, and suggested new ones missing from the classification. After three rounds, the expert panel agreed upon 57 teacher motivational behaviors (TMBs) that were consistent with SDT. For most behaviors (77%), experts reached consensus on both the most relevant psychological need and influence on motivation. Our classification system provides a comprehensive list of TMBs and consistent terminology in how those behaviors are labeled. Researchers and practitioners designing interventions could use these behaviors to design interventions, to reproduce interventions, to assess whether these behaviors moderate intervention effects, and could focus new research on areas where experts disagreed

Informant-reported cognitive symptoms that predict amnestic mild cognitive impairment

<p>Abstract</p> <p>Background</p> <p>Differentiating amnestic mild cognitive impairment (aMCI) from normal cognition is difficult in clinical settings. Self-reported and informant-reported memory complaints occur often in both clinical groups, which then necessitates the use of a comprehensive neuropsychological examination to make a differential diagnosis. However, the ability to identify cognitive symptoms that are predictive of aMCI through informant-based information may provide some clinical utility in accurately identifying individuals who are at risk for developing Alzheimer's disease (AD).</p> <p>Methods</p> <p>The current study utilized a case-control design using data from an ongoing validation study of the Alzheimer's Questionnaire (AQ), an informant-based dementia assessment. Data from 51 cognitively normal (CN) individuals participating in a brain donation program and 47 aMCI individuals seen in a neurology practice at the same institute were analyzed to determine which AQ items differentiated aMCI from CN individuals.</p> <p>Results</p> <p>Forward stepwise multiple logistic regression analysis which controlled for age and education showed that 4 AQ items were strong indicators of aMCI which included: repetition of statements and/or questions [OR 13.20 (3.02, 57.66)]; trouble knowing the day, date, month, year, and time [OR 17.97 (2.63, 122.77)]; difficulty managing finances [OR 11.60 (2.10, 63.99)]; and decreased sense of direction [OR 5.84 (1.09, 31.30)].</p> <p>Conclusions</p> <p>Overall, these data indicate that certain informant-reported cognitive symptoms may help clinicians differentiate individuals with aMCI from those with normal cognition. Items pertaining to repetition of statements, orientation, ability to manage finances, and visuospatial disorientation had high discriminatory power.</p

Morphological and Pathological Evolution of the Brain Microcirculation in Aging and Alzheimer’s Disease

Key pathological hallmarks of Alzheimer’s disease (AD), including amyloid plaques, cerebral amyloid angiopathy (CAA) and neurofibrillary tangles do not completely account for cognitive impairment, therefore other factors such as cardiovascular and cerebrovascular pathologies, may contribute to AD. In order to elucidate the microvascular changes that contribute to aging and disease, direct neuropathological staining and immunohistochemistry, were used to quantify the structural integrity of the microvasculature and its innervation in three oldest-old cohorts: 1) nonagenarians with AD and a high amyloid plaque load; 2) nonagenarians with no dementia and a high amyloid plaque load; 3) nonagenarians without dementia or amyloid plaques. In addition, a non-demented (ND) group (average age 71 years) with no amyloid plaques was included for comparison. While gray matter thickness and overall brain mass were reduced in AD compared to ND control groups, overall capillary density was not different. However, degenerated string capillaries were elevated in AD, potentially suggesting greater microvascular “dysfunction” compared to ND groups. Intriguingly, apolipoprotein ε4 carriers had significantly higher string vessel counts relative to non-ε4 carriers. Taken together, these data suggest a concomitant loss of functional capillaries and brain volume in AD subjects. We also demonstrated a trend of decreasing vesicular acetylcholine transporter staining, a marker of cortical cholinergic afferents that contribute to arteriolar vasoregulation, in AD compared to ND control groups, suggesting impaired control of vasodilation in AD subjects. In addition, tyrosine hydroxylase, a marker of noradrenergic vascular innervation, was reduced which may also contribute to a loss of control of vasoconstriction. The data highlight the importance of the brain microcirculation in the pathogenesis and evolution of AD

Cardiovascular risk factors for mild cognitive impairment

The relationship between cardiovascular conditions and the presence of Alzheimer\u27s disease (AD) has been well-documented in a number of recent studies. Generally, the presence of cardiovascular conditions such as high total cholesterol and hypertension have been shown to significantly increase the risk for the development of AD. Given the results of these studies, it is possible that these same risk factors might also increase the risk of developing mild cognitive impairment (MCI). An analysis of 216 subjects (119 cognitively normal (CN), 77 aMCI, 20 naMCI) found that after adjusting for age, education, ethnicity, and gender, only hemoglobin A1c (HbA1c) showed a significant effect for aMCI [OR = 1.75 (1.02, 2.99) p=0.04]. Age and education also showed significant effects that were consistent with previous studies. Given recent studies linking Type 2 diabetes with AD, this finding appears to strengthen the link between diabetes-related disease processes and aMCI/AD disease processes