Diagnostic accuracy of early cognitive indicators in mild cognitive impairment

Establishing Reference Values for a New Computerized Cognitive Function Test Program for Children

OBJECTIVE

To establish reference values for the computerized cognitive test and evaluate cognitive function improvements across different age groups, we introduce the computerized Cognitive Function Test program (eCFT), specifically designed for children. We aimed to establish eCFT reference values and assess cognitive function improvements across different age groups.

METHODS

We included children aged 3-6 years with confirmed normal cognition based on the Korean Developmental Screening Test for Infants and Children and Kaufman Assessment Battery for Children-II. The eCFT consists of 8 subtests for visual perception, attention, memory, and executive function.

RESULTS

A total of 66 participants (36 males and 30 females) with an average age of 4.4 years participated. The age 6 group consistently outperformed both age group 3 and 4 in terms of correct responses. With regard to the completed stage, the "selective auditory stimulus" test findings were 2.0 and 3.9 for the age 3 and age 6 groups, respectively (p<0.05). The "trail-making" test findings were 1.7, 2.1, 2.6, and 2.8, respectively (between ages 3 and 6, p<0.01; between ages 4 and 6, p<0.05); moreover, the age 5 group surpassed the age 3 group (2.6 and 1.7, respectively, p<0.05).

CONCLUSION

The eCFT is an easily accessible tool to evaluate cognitive function in young children. We introduce reference values with a cutoff range for preschool-aged children, enabling early intervention for those with cognitive impairment. Given its accessibility and relatively short evaluation time, the eCFT has potential for clinical use.

The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders

BACKGROUND

The increasing prevalence of neurocognitive disorders (NCDs) in the aging population worldwide has become a significant concern due to subjectivity of evaluations and the lack of precise diagnostic methods and specific indicators. Developing personalized diagnostic strategies for NCDs has therefore become a priority.

RESULTS

Multimodal electroencephalography (EEG) data of a matched cohort of normal aging (NA) and NCDs seniors were recorded, and their faecal samples and urine exosomes were collected to identify multi-omics signatures and metabolic pathways in NCDs by integrating metagenomics, proteomics, and metabolomics analysis. Additionally, experimental verification of multi-omics signatures was carried out in aged mice using faecal microbiota transplantation (FMT). We found that NCDs seniors had low EEG power spectral density and identified specific microbiota, including Ruminococcus gnavus, Enterocloster bolteae, Lachnoclostridium sp. YL 32, and metabolites, including L-tryptophan, L-glutamic acid, gamma-aminobutyric acid (GABA), and fatty acid esters of hydroxy fatty acids (FAHFAs), as well as disturbed biosynthesis of aromatic amino acids and TCA cycle dysfunction, validated in aged mice. Finally, we employed a support vector machine (SVM) algorithm to construct a machine learning model to classify NA and NCDs groups based on the fusion of EEG data and multi-omics profiles and the model demonstrated 92.69% accuracy in classifying NA and NCDs groups.

CONCLUSIONS

Our study highlights the potential of multi-omics profiling and EEG data fusion in personalized diagnosis of NCDs, with the potential to improve diagnostic precision and provide insights into the underlying mechanisms of NCDs. Video Abstract.

The Value of Clock Drawing Process Assessment in Screening for Mild Cognitive Impairment and Alzheimer's Dementia

Many clock drawing test (CDT) scoring systems focus on drawing results and lack drawing process assessments. This study created a CDT scoring procedure with drawing process assessment and explored its diagnostic value in screening for mild cognitive impairment (MCI) and early Alzheimer's disease (AD) from normal control (NC). We used logistic regression and receiver operating characteristic (ROC) curves to determine a new, sensitive scoring system for AD and MCI patients in a derivation cohort. The new scoring method was then compared to two common scoring systems and externally validated in a second cohort. We developed a new scoring system named CDT5, which contained one process assessment item: remember setting time without asking. Compared with two published scoring systems, CDT5 had better discriminatory power in distinguishing AD patients from NCs in derivation (area under the ROC curve [area under the curve, AUC] = .890) and validation (AUC = .867) cohorts. Three scoring systems had poor diagnostic accuracy at discriminating MCI patients from controls, with CDT5 being the most sensitive (78.57%). Adding the drawing process in CDT helps accurately detect patients with early AD, but its role in identifying patients with MCI needs to be further explored.

Diagnostic accuracy of CompCog: reaction time as a screening measure for mild cognitive impairment

BACKGROUND

Reaction time is affected under different neurological conditions but has not been much investigated considering all types of mild cognitive impairment (MCI).

OBJECTIVE

This study investigated the diagnostic accuracy of CompCog, a computerized cognitive screening battery focusing on reaction time measurements.

METHODS

A sample of 52 older adults underwent neuropsychological assessments, including CompCog, and medical appointments, to be classified as a control group or be diagnosed with MCI. The accuracy of CompCog for distinguishing between the two groups was calculated.

RESULTS

The results from diagnostic accuracy analyses showed that the AUCs of ROC curves were as high as 0.915 (CI 0.837-0.993). The subtest with the highest sensitivity and specificity (choice reaction time subtest) had 91.7% sensitivity and 89.3% specificity. The logistic regression final model correctly classified 92.3% of individuals, with 92.9% specificity and 91.7% sensitivity, and included only four variables from different subtests.

CONCLUSIONS

In summary, the study showed that reaction time assessed through CompCog is a good screening measure to differentiate between normal aging and MCI. Reaction time measurements in milliseconds were more accurate than correct answers. This test can form part of routine clinical tests to achieve the objectives of screening for MCI, indicating further procedures for investigation and diagnosis and planning interventions.

Evidence of the validity of a novel version of the computerized cognitive screening battery CompCog

Although the availability of the computer-based assessment has increased over the years, neuropsychology has not carried out a significant paradigm shift since the personal computer’s popularization in the 1980s. To keep up with the technological advances of healthcare and neuroscience in general, more efforts must be made in the field of clinical neuropsychology to develop and validate new and more technology-based instruments, especially considering new variables and paradigms when compared to paper and pencil tests.

Mild cognitive impairment history and current procedures in low- and middle-income countries: a brief review

Mild cognitive impairment (MCI) is a widely studied concept that has changed over time. Epidemiology, diagnosis, costs, prognostics, screening procedures, and categorization have been extensively discussed. However, unified guidelines are still not available, especially considering differences between low- and middle-income countries (LMIC) and high-income countries (HIC).