Cluster subtypes of the Spanish version of the California Verbal Learning Test in a sample of adults with subjective memory complaints

Relevance of Complaint Severity in Predicting the Progression of Subjective Cognitive Decline and Mild Cognitive Impairment: A Machine Learning Approach

BACKGROUND

The presence of subjective cognitive complaints (SCCs) is a core criterion for diagnosis of subjective cognitive decline (SCD); however, no standard procedure for distinguishing normative and non-normative SCCs has yet been established.

OBJECTIVE

To determine whether differentiation of participants with SCD according to SCC severity improves the validity of the prediction of progression in SCD and MCI and to explore validity metrics for two extreme thresholds of the distribution in scores in a questionnaire on SCCs.

METHODS

Two hundred and fifty-three older adults with SCCs participating in the Compostela Aging Study (CompAS) were classified as MCI or SCD at baseline. The participants underwent two follow-up assessments and were classified as cognitively stable or worsened. Severity of SCCs (low and high) in SCD was established by using two different percentiles of the questionnaire score distribution as cut-off points. The validity of these cut-off points for predicting progression using socio-demographic, health, and neuropsychological variables was tested by machine learning (ML) analysis.

RESULTS

Severity of SCCs in SCD established considering the 5th percentile as a cut-off point proved to be the best metric for predicting progression. The variables with the main role in conforming the predictive algorithm were those related to memory, cognitive reserve, general health, and the stability of diagnosis over time.

CONCLUSION

Moderate to high complainers showed an increased probability of progression in cognitive decline, suggesting the clinical relevance of standard procedures to determine SCC severity. Our findings highlight the important role of the multimodal ML approach in predicting progression.

Does Empirically Derived Classification of Individuals with Subjective Cognitive Complaints Predict Dementia?

(1) Background: Early identification of mild cognitive impairment (MCI) in people reporting subjective cognitive complaints (SCC) and the study of progression of cognitive decline are important issues in dementia research. This paper examines whether empirically derived procedures predict progression from MCI to dementia. (2) Methods: At baseline, 192 participants with SCC were diagnosed according to clinical criteria as cognitively unimpaired (70), single-domain amnestic MCI (65), multiple-domain amnestic MCI (33) and multiple-domain non-amnestic MCI (24). A two-stage hierarchical cluster analysis was performed for empirical classification. Categorical regression analysis was then used to assess the predictive value of the clusters obtained. Participants were re-assessed after 36 months. (3) Results: Participants were grouped into four empirically derived clusters: Cluster 1, similar to multiple-domain amnestic MCI; Cluster 2, characterized by subjective cognitive decline (SCD) but with low scores in language and working memory; Cluster 3, with specific deterioration in episodic memory, similar to single-domain amnestic MCI; and Cluster 4, with SCD but with scores above the mean in all domains. The majority of participants who progressed to dementia were included in Cluster 1. (4) Conclusions: Cluster analysis differentiated between MCI and SCD in a sample of people with SCC and empirical criteria were more closely associated with progression to dementia than standard criteria.

Associations between sleep and verbal memory in subjective cognitive decline: A role for semantic clustering

Age-related reductions in slow wave activity (SWA) and increased fragmentation during sleep play a key role in memory impairment. As the prefrontal cortex is necessary for the control processes relevant to memory encoding, including utilisation of internal heuristics such as semantic clustering, and is preferentially vulnerable to sleep disturbance, our study examined how SWA and sleep fragmentation relates to memory performance in individuals with Subjective Cognitive Decline (SCD). Thirty older adults with SCD (Mean Age = 69.34, SD = 5.34) completed a neurocognitive test battery, including the California Verbal Learning Test, which was used to assess semantic clustering. One week later, participants were admitted to the laboratory for a two night visit. SWA and sleep fragmentation were captured using sleep polysomnography. Next-day memory performance was tested using the Rey Auditory Verbal Learning Test. Poorer sleep (reduced SWA; increased arousals) was associated with reduced semantic clustering, which mediated impairment on verbal memory and learning tests conducted both the day after sleep was recorded (for both SWA and arousals), and a week prior (for arousals only). We demonstrate semantic clustering mediated the well described associations between sleep and verbal memory. As these strategies are a component of cognitive training interventions, future research may examine the role of simultaneous sleep interventions for improving cognitive training outcomes.

Problems in Classifying Mild Cognitive Impairment (MCI): One or Multiple Syndromes?

As the conceptual, methodological, and technological advances applied to dementias have evolved the construct of mild cognitive impairment (MCI), one problem encountered has been its classification into subtypes. Here, we aim to revise the concept of MCI and its subtypes, addressing the problems of classification not only from the psychometric point of view or by using alternative methods, such as latent class analysis, but also considering the absence of normative data. In addition to the well-known influence of certain factors on cognitive function, such as educational level and cultural traits, recent studies highlight the relevance of other factors that may significantly affect the genesis and evolution of MCI: subjective memory complaints, loneliness, social isolation, etc. The present work will contemplate the most relevant attempts to clarify the issue of MCI categorization and classification, combining our own data with that from recent studies which suggest the role of relevant psychosocial factors in MCI.

Longitudinal Assessment of Verbal Learning and Memory in Amnestic Mild Cognitive Impairment: Practice Effects and Meaningful Changes

Objectives: To identify learning effects and meaningful changes in amnestic mild cognitive impairment (aMCI) at a follow-up assessment.

Method: The Spanish version of the California Verbal Learning Test (CVLT) was administered to a sample of 274 adults of age over 50 years with subjective memory complains (SMC), including single and multiple domain aMCI groups and participants with SMC but without cognitive impairment (SMC group). The Wilcoxon test was used to compare results at baseline and after 18 months in short and long recall, and standardized regression-based (SRB) methods were used to study meaningful changes.

Results: Scores were significantly higher at follow-up for short and long-delayed recall in all groups indicating generalized practice effect. SRB scores indicated a significant decline in recall in a higher proportion of participants with aMCI than in SMC group.

Discussion: Patients with multiple and single domain aMCI benefit from practice in a verbal learning memory test. The SRB approach revealed a higher incidence of meaningful decline in short and long-delay recall and recognition in the aMCI groups than in the SMC group. Specifically, compared to SMC participants, single-domain aMCI individuals declined in a higher proportion in all measures, and multiple-domain aMCI individuals in long delay free recall.

Comparison Between an Empirically Derived and a Standard Classification of Amnestic Mild Cognitive Impairment From a Sample Of Adults With Subjective Cognitive Complaints

Objective: The aim of this study is to compare an empirically derived classification of amnestic mild cognitive impairment (aMCI) from a sample of adults with subjective cognitive complaints by using cluster analysis of their performance on the California Verbal Learning Test (CVLT) with a classification of aMCI based on standard clinical criteria. Method: Three hundred ninety-one individuals aged 48 years and older were diagnosed as aMCI or healthy controls. Cluster analysis of the CVLT performance was conducted, followed by logistic regression analysis. Results: A two-cluster solution performed on the CVLT measures correctly classified 98.0% of the aMCI patients and 73.4% of the healthy controls diagnosed by using standard aMCI criteria. Discussion: The empirically derived classification of aMCI is consistent with the classification based on standard criteria; however, standard criteria should also be considered to prevent false positives.

Confirmatory factor analysis of the Spanish version of the California Verbal Learning Test in a sample of middle-aged and older adults with subjective memory complaints

INTRODUCTION

Assessment of the ability to retain new information is of special interest in the second half of life because of age-related changes, especially in those individuals at risk of cognitive impairment. The California Verbal Learning Test (CVLT) is one of the most common auditory-verbal learning tests used to test episodic memory. The objective of this paper is to study the stability of the factorial structure of the Spanish version of CVLT in a sample of adults aged 50-87 years with subjective memory complaints (SMCs).

METHOD

Performance at baseline and follow-up assessment (about 18 months later) was analyzed in 301 participants. Models including one, two, three, and four factors were tested, by comparing the results of confirmatory factor analysis and structural equation models of relations between the factors at baseline and follow-up.

RESULTS

The two-factor models (accurate and inaccurate memory) yielded the best fit. The model establishing a relationship between these two factors at baseline and follow-up provided a good fit.

CONCLUSION

CVLT performance in a sample of middle-aged and old adults with SMCs was separated into two factors differentiating accurate recollection and errors. A structural equation modeling (SEM) model relating data from both assessments replicated these findings.