Cognitive screening for adult psychiatric outpatients: Comparison of the Cognivue® to the Montreal Cognitive Assessment

Montreal Cognitive Assessment (MoCA) as a screening tool for cognitive impairment in early stages of psychosis

Background

Cognitive alterations have been reported in early stages of psychosis including people with First Episode Psychosis (FEP), Clinical High-Risk Mental State (CHR), and Psychotic-Like Experience (PLE). This study aimed to compare the cognitive function in early stages of psychosis using the Montreal Cognitive Assessment (MoCA), a low-cost and brief assessment tool of cognitive functions.

Methods

A total of 154 individuals, including 35 with FEP, 38 CHR, 44 PLE, and 37 healthy controls (HC), were evaluated with the MoCA in Santiago, Chile. We calculated the mean total score of the MoCA and the standard deviation of the mean. Groups were assessed for a trend to lower scores in a pre-determined sequence (HC > PLE > CHR > FEP) using the Jonckheere-Terpstra test (TJT).

Results

The mean total MoCA scores were 24.8 ± 3.3 in FEP, 26.4 ± 2.4 in CHR, 26.4 ± 2.3 in PLE, and 27.2 ± 1.8 in HC. The analyses revealed a significant trend (p < 0.05) toward lower MoCA individual domain scores and MoCA total scores in the following order: HC > PLE > CHR > FEP. The mean total scores of all groups were above the cut-off for cognitive impairment (22 points).

Conclusions

The MoCA describes lower scores in cognition across early stages of psychosis and may be a useful low-cost assessment instrument in early intervention centers of poorly resourced settings.

Cognitive Assessment with Cognivue Clarity®: Psychometric Properties and Normative Ranges in a Diverse Population

Background

Detecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer's disease (AD) studies. Cognivue Clarity® is an FDA-cleared computerized 10-minute cognitive screening platform using adaptive psychophysics to detect cognitive impairment.

Objective

Test the ability of Cognivue Clarity to measure cognitive performance in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

Methods

This study enrolled 452 participants across 6 US study sites and completed both Cognivue Clarity device and RBANS. Psychometric properties and exploratory factor analysis of Cognivue Clarity were explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted.

Results

Participants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had ≤12 years of education, 31.2% were African American and 9.2% were Hispanic. Cognivue Clarity had strong internal consistency, test-retest reliability and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness-of-fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. Cognivue Clarity had strong correlations with RBANS.

Conclusions

Our study supports the use of Cognivue Clarity as an easy-to-use, brief, and valid cognitive assessment that measures cognitive performance. In the correct clinical setting, Cognivue Clarity may identify individuals with likely cognitive impairment who could be candidates for AD research studies.

The Mediating Role of Cortical Atrophy on the Relationship between the Resilience Index and Cognitive Function: Findings from the Healthy Brain Initiative

Background

Lifestyle factors are linked to differences in brain aging and risk for Alzheimer's disease, underscored by concepts like 'cognitive reserve' and 'brain maintenance'. The Resilience Index (RI), a composite of 6 factors (cognitive reserve, physical and cognitive activities, social engagement, diet, and mindfulness) provides such a holistic measure.

Objective

This study aims to examine the association of RI scores with cognitive function and assess the mediating role of cortical atrophy.

Methods

Baseline data from 113 participants (aged 45+, 68% female) from the Healthy Brain Initiative were included. Life course resilience was estimated with the RI, cognitive performance with Cognivue®, and brain health using a machine learning derived Cortical Atrophy Score (CAS). Mediation analysis probed the relationship between RI, cognitive outcomes, and cortical atrophy.

Results

In age and sex adjusted models, the RI was significantly associated with CAS (β= -0.25, p = 0.006) and Cognivue® scores (β= 0.32, p < 0.001). The RI-Cognivue® association was partially mediated by CAS (β= 0.07; 95% CI [0.02, 0.14]).

Conclusions

Findings revealed that the collective effect of early and late-life lifestyle resilience factors on cognition are partially explained by their association with less brain atrophy. These findings underscore the value of comprehensive lifestyle assessments in understanding the risk and progression of cognitive decline and Alzheimer's disease in an aging population.

The Evaluation Value of Diffusion-Weighted Imaging for Brain Injury in Patients after Deep Hypothermic Circulatory Arrest

Objective

Cerebral complications may occur after surgery with deep hypothermic circulatory arrest (DHCA). Diffusion-weighted imaging (DWI) has shown promising results in detecting early changes of cerebral ischemia. However, studies in human models are limited. Here, we examined the significance of DWI for detecting brain injury in postoperative patients after DHCA.

Methods

Twelve patients who had undergone selective cerebral perfusion with DHCA were enrolled. All patients underwent magnetic resonance imaging (MRI) examinations before and after the operation with T1-weighted phase (T1W) and T2-weighted phase (T2W). Magnetic resonance angiography (3D TOF) was applied to observe intracranial arterial communication situations. DWI was employed to calculate the apparent diffusion coefficient (ADC) values. The neurocognitive function of patients was assessed preoperatively and postoperatively using the Montreal Cognitive Assessment Scale (MoCA), Hamilton Depression Scale (HAMD), and Hamilton Anxiety Scale (HAMA).

Results

The ADC values of the whole brain of patients after surgery were significantly higher than before surgery (P = 0.003). However, no significant difference in the ADC values of other regions before and after the operation was observed. There was no significant effect on the postoperative cognitive function of patients after surgery, but visual-spatial and executive abilities were significantly reduced, while psychological anxiety (P = 0.005) and depression levels (P < 0.05) significantly increased. Correlation analysis revealed a significant association between ADC change values and depression change values (P < 0.05).

Conclusion

DHCA demonstrated no significant effect on the cognitive function of patients but could affect the mood of patients. On the other hand, DWI demonstrated promising efficiency and accuracy in evaluating brain injury after DHCA.

Now is the Time to Improve Cognitive Screening and Assessment for Clinical and Research Advancement

Alzheimer’s disease (AD) is the only cause of death ranked in the top ten globally without precise early diagnosis or effective means of prevention or treatment. Further, AD was identified as a pandemic [1] well before COVID-19 was dubbed a 21st century pandemic [2]. And now, with the realization of the prominent secondary impacts of pandemics, there is a growing, widespread recognition of the tremendous magnitude of the impending burden from AD in an aging world population in the coming decades [3]. This appreciation has amplified the growing and pressing need for a new, efficacious, and practical platform to detect and track cognitive decline, beginning in the preliminary (prodromal) phases of the disease, sensitively, accurately, effectively, reliably, efficiently, and remotely [4–7]. Moreover, the parallel necessity of clarifying and understanding risk factors, developing successful prevention strategies [8–17], and discovering and monitoring viable and effective treatments could all benefit from accurate and efficient screening and assessment platforms. Modern recognition of AD [18] as a common affliction of the elderly began in 1968 with a paper by Blessed, Tomlinson, & Roth [19] in which two tests, one a brief assessment of cognitive function and the other a measure of daily function, demonstrated impairment which was associated with the postmortem counts of neurofibrillary tangles, composed mainly of microtubule-associated protein-tau (tau), in the brain, though not to senile plaques, composed mainly of amyloid-β (Aβ). Even in more recent analyses, the tangles correspond with the severity of dementia more than the plaques [20, 21]. Since 1960, a plethora of cognitive tests, paper and pencil [22, 23], simple screening models [24], and computerized [25–27], have been developed to assess the dysfunction associated with AD. However, there has been limited application of Modern Test Theory, which includes Item Characteristic Curve Analysis, used in the technological development of such tools [28–31], along with widespread failure to understand the underlying AD pathological process to guide test development [32, 33]. The lack of such development has likely been a major contributor to the failure of the field to develop timely screening approaches for AD [34, 35], inaccurate assessment of the progression of AD [36], and even now, failure to find an effective approach to stopping AD.

Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer's Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

BACKGROUND

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer's disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD.

OBJECTIVE

We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test.

METHODS

Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent.

RESULTS

A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260).

CONCLUSION

MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.