Brief Test of Attention: Normative data for the Latin American Spanish speaking adult population

Assessment of visuospatial functions in post-Covid 19 patients: beyond the traditional paradigm

Several studies indicate that some cognitive changes occur after COVID-19. Visuospatial alterations have been reported in 24% to 40%. These alterations may be useful as early biomarkers of neurodegenerative disease. Thus, we can emphasize the importance of visuospatial processes in cognition through quantitative and qualitative analysis of performance on the Clock Test (CDT) and the Rey-Osterrieth Complex Figure (FCRO). Our objective was to describe the performance of post COVID 19 patients in visuospatial tests, with different degrees of respiratory impairment and to perform a qualitative analysis of the performance to check its relationship with alterations in attention and executive functions. This will allow highlighting the executive component of the performance of the CDT and ROCF and differentiate patients with possible cognitive impairment. 77 patients with SARS-CoV-2 infection were evaluated (3 months post-infection) with a complete neuropsychological battery and MRI. Overall, there is a significant difference between FCRO and CDT, with FCRO having only 9% change and CDT having 51.9% change. Regarding the correlations observed between groups (VM Inv, VM non I and non hospitalized) the highest correlations were observed between Boston with FCRO copy (r=0.497; p=0.001) and with FCRO memory (r=0.429; p=0.001). Comparing the performance between groups by severity, significant differences were observed only in the TMT A (13.706 p=0.001) and B (9.583 p=0.008) tests and in the phonological fluency letter A (13.445 p=0.001), we observed that the group of non-hospitalized patients had a better performance. Neuropsychological deficits often have a direct impact on daily life by affecting the ability to learn and adapt. Thus, a useful strategy for the neuropsychological characterization of post-COVID-19 patients is the qualitative analysis of visuospatial abilities in conjunction with executive functions that cannot be analyzed in isolation.

Relationship between gait parameters and cognitive indexes in adult aging

PURPOSE

This study aimed to identify the most effective summary cognitive index predicted from spatio-temporal gait features (STGF) extracted from gait patterns.

METHODS

The study involved 125 participants, including 40 young (mean age: 27.65 years, 50% women), and 85 older adults (mean age: 73.25 years, 62.35% women). The group of older adults included both healthy adults and those with Mild Cognitive Impairment (MCI). Participant´s performance in various cognitive domains was evaluated using 12 cognitive measures from five neuropsychological tests. Four summary cognitive indexes were calculated for each case: 1) the z-score of Mini-Mental State Examination (MMSE) from a population norm (MMSE z-score); 2) the sum of the absolute z-scores of the patients' neuropsychological measures from a population norm (ZSum); 3) the first principal component scores obtained from the individual cognitive variables z-scores (PCCog); and 4) the Mahalanobis distance between the vector that represents the subject's cognitive state (defined by the 12 cognitive variables) and the vector corresponding to a population norm (MDCog). The gait patterns were recorded using a body-fixed Inertial Measurement Unit while participants executed four walking tasks (normal, fast, easy- and hard-dual tasks). Sixteen STGF for each walking task, and the dual-task costs for the dual tasks (when a subject performs an attention-demanding task and walks at the same time) were computed. After applied Principal Component Analysis to gait measures (96 features), a robust regression was used to predict each cognitive index and individual cognitive variable. The adjusted proportion of variance (adjusted-R2) coefficients were reported, and confidence intervals were estimated using the bootstrap procedure.

RESULTS

The mean values of adjusted-R2 for the summary cognitive indexes were as follows: 0.0248 for MMSE z-score, 0.0080 for ZSum, 0.0033 for PCCog, and 0.4445 for MDCog. The mean adjusted-R2 values for the z-scores of individual cognitive variables ranged between 0.0009 and 0.0693. Multiple linear regression was only statistically significant for MDCog, with the highest estimated adjusted-R2 value.

CONCLUSIONS

The association between individual cognitive variables and most of the summary cognitive indexes with gait parameters was weak. However, the MDCog index showed a stronger and significant association with the STGF, exhibiting the highest value of the proportion of the variance that can be explained by the predictor variables. These findings suggest that the MDCog index may be a useful tool in studying the relationship between gait patterns and cognition.

Development of criteria for cognitive dysfunction in post-COVID syndrome: the IC-CoDi-COVID approach

BACKGROUND

We aimed to develop objective criteria for cognitive dysfunction associated with the post-COVID syndrome.

METHODS

Four hundred and four patients with post-COVID syndrome from two centers were evaluated with comprehensive neuropsychological batteries. The International Classification for Cognitive Disorders in Epilepsy (IC-CoDE) framework was adapted and implemented. A healthy control group of 145 participants and a complementary data-driven approach based on unsupervised machine-learning clustering algorithms were also used to evaluate the optimal classification and cutoff points.

RESULTS

According to the developed criteria, 41.2% and 17.3% of the sample were classified as having at least one cognitive domain impaired using -1 and -1.5 standard deviations as cutoff points. Attention/processing speed was the most frequently impaired domain. There were no differences in base rates of cognitive impairment between the two centers. Clustering analysis revealed two clusters, although with an important overlap (silhouette index 0.18-0.19). Cognitive impairment was associated with younger age and lower education levels, but not hospitalization.

CONCLUSIONS

We propose a harmonization of the criteria to define and classify cognitive impairment in the post-COVID syndrome. These criteria may be extrapolated to other neuropsychological batteries and settings, contributing to the diagnosis of cognitive deficits after COVID-19 and facilitating multicenter studies to guide biomarker investigation and therapies.

Validation of the Norma Latina Neuropsychological Assessment Battery in Patients with Alzheimer's Disease in Mexico

To our knowledge, this is the first study reported in the literature that has validated the Norma Latina Battery in a population of people with Alzheimer's disease (AD) in Mexico. The objective of the study was to determine the discriminant validity of the Norma Latina Battery in a group of Mexican individuals with AD and a group of heathy controls (HC). The Norma Latina Battery was administered to 234 Mexican participants (117 HC and 117 individuals with AD). Results show that: (1) the Norma Latina Battery has high discriminative capacity between groups in all domains; (2) participants with AD presented worse scores in each of the cognitive domains compared to the HC and a greater number of low scores in each of the established thresholds or cut-off points; and finally, (3) the Norma Latina Battery had optimal sensitivity and specificity, especially when a set was observed ≥5 scores below the 10th percentile or ≥4 scores below the 5th percentile. In conclusion, it is recommended that both clinicians and researchers use this battery in the evaluation of Mexican people with AD to better understand the prognosis of the disease and its subsequent treatment.

Stable Sparse Classifiers predict cognitive impairment from gait patterns

Background

Although gait patterns disturbances are known to be related to cognitive decline, there is no consensus on the possibility of predicting one from the other. It is necessary to find the optimal gait features, experimental protocols, and computational algorithms to achieve this purpose.

Purposes

To assess the efficacy of the Stable Sparse Classifiers procedure (SSC) for discriminating young and healthy older adults (YA vs. HE), as well as healthy and cognitively impaired elderly groups (HE vs. MCI-E) from their gait patterns. To identify the walking tasks or combinations of tasks and specific spatio-temporal gait features (STGF) that allow the best prediction with SSC.

Methods

A sample of 125 participants (40 young- and 85 older-adults) was studied. They underwent assessment with five neuropsychological tests that explore different cognitive domains. A summarized cognitive index (MDCog), based on the Mahalanobis distance from normative data, was calculated. The sample was divided into three groups (young adults, healthy and cognitively impaired elderly adults) using k-means clustering of MDCog in addition to Age. The participants executed four walking tasks (normal, fast, easy- and hard-dual tasks) and their gait patterns, measured with a body-fixed Inertial Measurement Unit, were used to calculate 16 STGF and dual-task costs. SSC was then employed to predict which group the participants belonged to. The classification's performance was assessed using the area under the receiver operating curves (AUC) and the stable biomarkers were identified.

Results

The discrimination HE vs. MCI-E revealed that the combination of the easy dual-task and the fast walking task had the best prediction performance (AUC = 0.86, sensitivity: 90.1%, specificity: 96.9%, accuracy: 95.8%). The features related to gait variability and to the amplitude of vertical acceleration had the largest predictive power. SSC prediction accuracy was better than the accuracies obtained with linear discriminant analysis and support vector machine classifiers.

Conclusions

The study corroborated that the changes in gait patterns can be used to discriminate between young and healthy older adults and more importantly between healthy and cognitively impaired adults. A subset of gait tasks and STGF optimal for achieving this goal with SSC were identified, with the latter method superior to other classification techniques.

Normative data of neuropsychological tests of attention and executive functions in Ecuadorian adult population

OBJECTIVE

The purpose of this study was to generate normative data for five tests of attention and executive functions (M-WCST, Stroop test, TMT, BTA, and SDMT), in a group of 322 Ecuadorian adults from Quito between the ages of 18 and 85.

METHOD

Multiple regression analyzes taking into account age, education, and gender were used to generate the normative data.

RESULTS

Age and education were significantly related to test performance such that scores decreased with age and improved as a function of education. An online calculator is provided to generate normative test scores.

CONCLUSIONS

This is the first study that presents normative data for tests of executive functions and attention in an Ecuadorian adult population. This data will improve the clinical practice of neuropsychology and help to develop the field in the country.

Normative data for tests of attention and executive functions in a sample of European Portuguese adult population

OBJECTIVE

The main goal of this study was to produce normative data for the Portuguese population on five neuropsychological tests frequently used to assess executive functions and attention: the Modified Wisconsin Card Sorting Test (M-WCST), the Stroop Color and Word Test, the Trail Making Test (TMT), the Brief Test of Attention (BTA), and the Symbol Digit Modalities Test (SDMT).

METHOD

The study included 300 individuals aged between 18 and 93 years, who had educational backgrounds ranging from 3 to 25 years.

RESULTS

The influence of age, education, and sex was explored for each measure, as well as their contribution to explain the performance variance.

CONCLUSIONS

The normative data are presented as regression-based algorithms to adjust direct and derived test scores for sex, age, and education. This study provides a calculator of normative data, derived from the results of the regression models.