Predicting conversion to dementia in a memory clinic: A standard clinical approach compared with an empirically defined clustering method (latent profile analysis) for mild cognitive impairment subtyping

Place of care in the last three years of life for Medicare beneficiaries

BACKGROUND

Most older adults prefer aging in place; however, patients with advanced illness often need institutional care. Understanding place of care trajectory patterns may inform patient-centered care planning and health policy decisions. The purpose of this study was to characterize place of care trajectories during the last three years of life.

METHODS

Linked administrative, claims, and assessment data were analyzed for a 10% random sample cohort of US Medicare beneficiaries who died in 2018, aged fifty or older, and continuously enrolled in Medicare during their last five years of life. A group-based trajectory modeling approach was used to classify beneficiaries based on the proportion of days of institutional care (hospital inpatient or skilled nursing facility) and skilled home care (home health care and home hospice) used in each quarter of the last three years of life. Associations between group membership and sociodemographic and clinical predictors were evaluated.

RESULTS

The analytic cohort included 199,828 Medicare beneficiaries. Nine place of care trajectory groups were identified, which were categorized into three clusters: home, skilled home care, and institutional care. Over half (59%) of the beneficiaries were in the home cluster, spending their last three years mostly at home, with skilled home care and institutional care use concentrated in the final quarter of life. One-quarter (27%) of beneficiaries were in the skilled home care cluster, with heavy use of skilled home health care and home hospice; the remaining 14% were in the institutional cluster, with heavy use of nursing home and inpatient care. Factors associated with both the skilled home care and institutional care clusters were female sex, Black race, a diagnosis of dementia, and Medicaid insurance. Extended use of skilled home care was more prevalent in southern states, and extended institutional care was more prevalent in midwestern states.

CONCLUSIONS

This study identified distinct patterns of place of care trajectories that varied in the timing and duration of institutional and skilled home care use during the last three years of life. Clinical, socioregional, and health policy factors influenced where patients received care. Our findings can help to inform personal and societal care planning.

Machine Learning-Based Classification of Subjective Cognitive Decline, Mild Cognitive Impairment, and Alzheimer's Dementia Using Neuroimage and Plasma Biomarkers

Alzheimer's disease (AD) progresses relentlessly from the preclinical to the dementia stage. The process begins decades before the diagnosis of dementia. Therefore, it is crucial to detect early manifestations to prevent cognitive decline. Recent advances in artificial intelligence help tackle the complex high-dimensional data encountered in clinical decision-making. In total, we recruited 206 subjects, including 69 cognitively unimpaired, 40 subjective cognitive decline (SCD), 34 mild cognitive impairment (MCI), and 63 AD dementia (ADD). We included 3 demographic, 1 clinical, 18 brain-image, and 3 plasma biomarker (Aß_1-42, Aß_1-40, and tau protein) features. We employed the linear discriminant analysis method for feature extraction to make data more distinguishable after dimension reduction. The sequential forward selection method was used for feature selection to identify the 12 best features for machine learning classifiers. We used both random forest and support vector machine as classifiers. The area under the receiver operative curve (AUROC) was close to 0.9 between diseased (combining ADD and MCI) and the controls. AUROC was higher than 0.85 between SCD and controls, 0.90 between MCI and SCD, and above 0.85 between ADD and MCI. We can differentiate between adjacent phases of the AD spectrum with blood biomarkers and brain MR images with the help of machine learning algorithms.

Risk of conversion from mild cognitive impairment to dementia in low- and middle-income countries: A systematic review and meta-analysis

Introduction

With no treatment for dementia, there is a need to identify high risk cases to focus preventive strategies, particularly in low- and middle-income countries (LMICs) where the burden of dementia is greatest. We evaluated the risk of conversion from mild cognitive ompairment (MCI) to dementia in LMICs.

Methods

Medline, Embase, PsycINFO, and Scopus were searched from inception until June 30, 2020. The search was restricted to observational studies, conducted in population-based samples, with at least 1 year follow-up. There was no restriction on the definition of MCI used as long as it was clearly defined. PROSPERO registration: CRD42019130958.

Results

Ten thousand six hundred forty-seven articles were screened; n = 11 retained. Of the 11 studies, most were conducted in China (n = 7 studies), with only two studies from countries classified as low income. A qualitative analysis of n = 11 studies showed that similar to high-income countries the conversion rate to dementia from MCI was variable (range 6 . 0%-44 . 8%; average follow-up 3 . 7 years [standard deviation = 1 . 2]). A meta-analysis of studies using Petersen criteria (n = 6 studies), found a pooled conversion rate to Alzheimer's disease (AD) of 23 . 8% (95% confidence interval = 15 . 4%-33.4%); approximately one in four people with MCI were at risk of AD in LMICs (over 3 . 0-5 . 8 years follow-up). Risk factors for conversion from MCI to dementia included demographic (e.g., age) and health (e.g., cardio-metabolic disease) variables.

Conclusions

MCI is associated with high, but variable, conversion to dementia in LMICs and may be influenced by demographic and health factors. There is a notable absence of data from low-income settings and countries outside of China. This highlights the urgent need for research investment into aging and dementia in LMIC settings. Being able to identify those individuals with cognitive impairment who are at highest risk of dementia in LMICs is necessary for the development of risk reduction strategies that are contextualized to these unique settings.

Diagnosing Mild Cognitive Impairment Among Racially Diverse Older Adults: Comparison of Consensus, Actuarial, and Statistical Methods

BACKGROUND

Actuarial and statistical methods have been proposed as alternatives to conventional methods of diagnosing mild cognitive impairment (MCI), with the aim of enhancing diagnostic and prognostic validity, but have not been compared in racially diverse samples.

OBJECTIVE

We compared the agreement of consensus, actuarial, and statistical MCI diagnostic methods, and their relationship to race and prognostic indicators among diverse older adults.

METHODS

Participants (N = 354; M age = 71; 68% White, 29% Black) were diagnosed with MCI or normal cognition (NC) according to clinical consensus, actuarial neuropsychological criteria (Jak/Bondi), and latent class analysis (LCA). We examined associations with race/ethnicity, longitudinal cognitive and functional change, and incident dementia.

RESULTS

MCI rates by consensus, actuarial criteria, and LCA were 44%, 53%, and 41%, respectively. LCA identified three MCI subtypes (memory; memory/language; memory/executive) and two NC classes (low normal; high normal). Diagnostic agreement was substantial, but agreement of the actuarial method with consensus and LCA was weaker than the agreement between consensus and LCA. Among cases classified as MCI by actuarial criteria only, Black participants were over-represented, and outcomes were generally similar to those of NC participants. Consensus diagnoses best predicted longitudinal outcomes overall, whereas actuarial diagnoses best predicted longitudinal functional change among Black participants.

CONCLUSION

Consensus diagnoses optimize specificity in predicting dementia, but among Black older adults, actuarial diagnoses may be more sensitive to early signs of decline. Results highlight the need for cross-cultural validity in MCI diagnosis and should be explored in community- and population-based samples.

Identification of Patterns of Cognitive Impairment for Early Detection of Dementia

Early detection of dementia is crucial to devise effective interventions. Comprehensive cognitive tests, while being the most accurate means of diagnosis, are long and tedious, thus limiting their applicability to a large population, especially when periodic assessments are needed. The problem is compounded by the fact that people have differing patterns of cognitive impairment as they progress to different forms of dementia. This paper presents a novel scheme by which individual-specific patterns of impairment can be identified and used to devise personalized tests for periodic follow-up. Patterns of cognitive impairment are initially learned from a population cluster of combined normals and cognitively impaired subjects, using a set of standardized cognitive tests. Impairment patterns in the population are identified using a 2-step procedure involving an ensemble wrapper feature selection followed by cluster identification and analysis. These patterns have been shown to correspond to clinically accepted variants of Mild Cognitive Impairment (MCI), a prodrome of dementia. The learned clusters of patterns can subsequently be used to identify the most likely route of cognitive impairment, even for pre-symptomatic and apparently normal people. Baseline data of 24,000 subjects from the NACC database was used for the study.

Is the Brixton Spatial Anticipation Test sensitive to frontal dysfunction? Evidence from patients with frontal and posterior lesions

INTRODUCTION

The Brixton Spatial Anticipation Test is a widely used neuropsychological test, thought to assess executive functions and to be sensitive to frontal lobe lesions. Our aim was to investigate Brixton performance in patients with focal frontal or posterior lesions and healthy controls.

METHOD

We compared performance on the Brixton in a sample of 24 frontal patients, 18 posterior patients and 22 healthy controls. Both overall performance (total number of errors) and error types were analyzed.

RESULTS

We found no significant differences between frontal and posterior patients and healthy controls in overall Brixton performance. Moreover, our error analysis showed no difference between frontal patients, posterior patients and healthy controls. The only exception was that posterior patients had a greater tendency to guess and make more errors when following specific rules than healthy controls but this was no longer significant once fluid intelligence was controlled for. We also found no significant difference between the performance of patients with left lateral (n = 11), right lateral (n = 10) or superior medial (n = 18) frontal lesions and healthy controls.

CONCLUSIONS

The Brixton test is not sensitive to frontal lobe dysfunction. It is likely that the test draws on a range of cognitive abilities not specific to frontal lobe lesions. Hence, caution should be taken when drawing conclusions about its neural substrates.

Mild cognitive impairment: narrative review of taxonomies and systematic review of their prediction of incident Alzheimer's disease dementia

Early detection of Alzheimer's disease is vital for developing novel treatments. Attempts to identify the intermediate state between normal cognition and dementia have evolved over the past 50 years. Current taxonomies of mild cognitive impairment (MCI) may be criticised for their imprecise operationalisation. With the advent of biomarkers such as amyloid-beta positron emission tomography imaging in established Alzheimer's disease, much research has focused on establishing which factors predict progression from MCI to Alzheimer's disease dementia. In this review, we discuss the historical context of MCI before reviewing the literature of MCI subtypes and their risk of progression to Alzheimer's disease dementia. Finally, we summarise the literature and discuss limitations and weaknesses of how the construct is operationalised and implemented, before offering suggestions for development of the concept of MCI. We conclude that MCI must be empirically defined for the sake of its predictive validity to identify Alzheimer's disease before dementia develops.

[¹⁸F]THK5351 PET Imaging in Patients with Mild Cognitive Impairment

Background and Purpose

Mild cognitive impairment (MCI) is a condition with diverse clinical outcomes and subgroups. Here we investigated the topographic distribution of tau in vivo using the positron emission tomography (PET) tracer [¹⁸F]THK5351 in MCI subgroups.

Methods

This study included 96 participants comprising 38 with amnestic MCI (aMCI), 21 with nonamnestic MCI (naMCI), and 37 with normal cognition (NC) who underwent 3.0-T MRI, [¹⁸F]THK5351 PET, and detailed neuropsychological tests. [¹⁸F]flutemetamol PET was also performed in 62 participants. The aMCI patients were further divided into three groups: 1) verbal-aMCI, only verbal memory impairment; 2) visual-aMCI, only visual memory impairment; and 3) both-aMCI, both visual and verbal memory impairment. Voxel-wise statistical analysis and region-of-interest -based analyses were performed to evaluate the retention of [¹⁸F]THK5351 in the MCI subgroups. Subgroup analysis of amyloid-positive and -negative MCI patients was also performed. Correlations between [¹⁸F]THK5351 retention and different neuropsychological tests were evaluated using statistical parametric mapping analyses.

Results

[¹⁸F]THK5351 retention in the lateral temporal, mesial temporal, parietal, frontal, posterior cingulate cortices and precuneus was significantly greater in aMCI patients than in NC subjects, whereas it did not differ significantly between naMCI and NC participants. [¹⁸F] THK5351 retention was greater in the both-aMCI group than in the verbal-aMCI and visualaMCI groups, and greater in amyloid-positive than amyloid-negative MCI patients. The cognitive function scores were significantly correlated with cortical [¹⁸F]THK5351 retention.

Conclusions

[¹⁸F]THK5351 PET might be useful for identifying distinct topographic patterns of [¹⁸F]THK5351 retention in subgroups of MCI patients who are at greater risk of the progression to Alzheimer's dementia.

Plasma Aβ42 and Total Tau Predict Cognitive Decline in Amnestic Mild Cognitive Impairment

Levels of amyloid-β (Aβ) and tau peptides in brain have been associated with Alzheimer disease (AD). The current study investigated the abilities of plasma Aβ42 and total-tau (t-tau) levels in predicting cognitive decline in subjects with amnestic mild cognitive impairment (MCI). Plasma Aβ42 and t-tau levels were quantified in 22 participants with amnestic MCI through immunomagnetic reduction (IMR) assay at baseline. The cognitive performance of participants was measured through neuropsychological tests at baseline and annual follow-up (average follow-up period of 1.5 years). The predictive value of plasma Aβ42 and t-tau for cognitive status was evaluated. We found that higher levels of Aβ42 and t-tau are associated with lower episodic verbal memory performance at baseline and cognitive decline over the course of follow-up. While Aβ42 or t-tau alone had moderate-to-high discriminatory value in the identification of future cognitive decline, the product of Aβ42 and t-tau offered greater differential value. These preliminary results might suggest that high levels of plasma Aβ42 and t-tau in amnestic MCI are associated with later cognitive decline. A further replication with a larger sample over a longer time period to validate and determine their long-term predictive value is warranted.

Mild cognitive impairment in maintenance hemodialysis patients: a cross-sectional survey and cohort study

Introduction

Few studies focused on mild cognitive impairment (MCI) in maintenance hemodialysis (MHD) patients. This study was conducted to survey the prevalence, the potent risk factors of MCI in MHD patients, and further observe the progress of MCI in a period of 6 months.

Methodology

Mini-Mental State Examination, and Montreal Cognitive Assessment were used to assess cognitive condition. MHD patients were enrolled from The First Affiliated Hospital of Nanjing Medical University, who had a stable hemodialysis history for more than 3 months.

Results

Sixty-four MHD patients and 54 general subjects were finally included. The average age of both groups was more than 60 years. The prevalence of MCI in the MHD group was significantly higher than that in general population (60.9% vs 29.6%, P<0.05). Spearman correlation analysis indicated that MCI was related to age, comorbidities, education years, uric acid, serum albumin, and blood pressure. The prevalence and severity of MCI in the MHD group remained unchanged during the 6 months (prevalence: 59.5%–66.6%, MoCA scores: 22.9–22.5).

Conclusion

MHD patients sustain a fairly high prevalence of MCI. Multiple risk factors influence the incidence and progression of MCI in MHD patients. More attention should be paid to this special population.

Neurocognitive Impairment and Associated Genetic Aspects in HIV Infection

HIV enters the central nervous system (CNS) early after infection. HIV-associated neurocognitive disorders (HAND) remain a serious complication of HIV infection despite available antiretroviral therapy (ART). Neurocognitive deficits observed in HAND are heterogeneous, suggesting a variability in individuals' susceptibility or resiliency to the detrimental CNS effects of HIV infection. This chapter reviews primary host genomic changes (immune-related genes, genes implicated in cognitive changes in primary neurodegenerative diseases), epigenetic mechanisms, and genetic interactions with ART implicated in HIV progression or HAND/neurocognitive complications of HIV. Limitations of the current findings include diversity of the HAND phenotype and limited replication of findings across cohorts. Strategies to improve the precision of future (epi)genetic studies of neurocognitive consequences of HIV infection are offered.

Empiric neurocognitive performance profile discovery and interpretation in HIV infection

The measurement and determinants of HIV-associated neurocognitive disorders (HAND) are under intense debate. We used latent profile analysis (LPA) and machine learning to define neurocognitive performance profiles and identify their associated risk factors in HIV patients receiving antiretroviral therapy (ART). Neurocognitive performance was assessed by a multidomain neuropsychological test battery. LPA was used to define individual neurocognitive profiles. Random forest analyses (RFA) identified the most important factors distinguishing each profile. Three profiles emerged from the LPA: profile 1 (P1, n = 159) achieved the highest performance, while profile 2 (P2, n = 163) had lowered executive functions and verbal memory, and profile 3 (P3, n = 59) was globally impaired. RFA achieved good prediction (area under the curve ≥ 0.80) only for global impairment (P3). Non-North American descent was the dominant predictor of P3, followed by factors coinciding with non-North American descent (female sex and toxoplasma seropositivity). Additional predictors included unemployment, current depressive symptoms, lower nadir CD4, and longstanding HIV. Restricting analyses to North Americans pointed to the additional importance of ART achieving high CSF levels and older age in prediction of P3. HAND diagnoses were most common in the globally impaired profile (P3 = 89.8%), followed by the group with reduced higher-order neurocognitive performance (P2 = 16.6%). Thus, implementation of LPA and RFA empirically distinguished three distinct neurocognitive performance profiles in this HIV-infected cohort while also highlighting potential risk factors and their relative importance to neurocognitive impairment. These data-driven analytical methods pointed to discernible demographic, HIV- and treatment-related risk factor constellations in patients born outside and within North America that might influence diagnostic and therapeutic decisions.

Cortical atrophy pattern-based subtyping predicts prognosis of amnestic MCI: an individual-level analysis

We categorized patients with amnestic mild cognitive impairment (aMCI) based on cortical atrophy patterns and evaluated whether the prognosis differed across the subtypes. Furthermore, we developed a classifier that learns the cortical atrophy pattern and predicts subtypes at an individual level. A total of 662 patients with aMCI were clustered into 3 subtypes based on cortical atrophy patterns. Of these, 467 patients were followed up for more than 12 months, and the median follow-up duration was 43 months. To predict individual-level subtype, we used a machine learning-based classifier with a 10-fold cross-validation scheme. Patients with aMCI were clustered into 3 subtypes: medial temporal atrophy, minimal atrophy (Min), and parietotemporal atrophy (PT) subtypes. The PT subtype had higher prevalence of APOE ε4 carriers, amyloid PET positivity, and greater risk of dementia conversion than the Min subtype. The accuracy for binary classification was 89.3% (MT vs. Rest), 92.6% (PT vs. Rest), and 86.6% (Min vs. Rest). When we used ensemble model of 3 binary classifiers, the accuracy for predicting the aMCI subtype at an individual level was 89.6%. Patients with aMCI with the PT subtype were more likely to have underlying Alzheimer's disease pathology and showed the worst prognosis. Our classifier may be useful for predicting the prognosis of individual aMCI patients.

A computerized test for the assessment of mild cognitive impairment subtypes in sentence processing

This study examines thesentence processing ability of mild cognitive impairment (MCI) subtypes. In addition to standard MCI neuropsychological tests, an experimental approach was applied to assess language. 133 people (93 MCI/40 controls) participated in novel computerized sentence processing tasks. Results presented statistically significant differences between MCI/controls andMCI subtypes (ANOVA):(a) duration F(2,92) = 19.259,p < .001) in sentence construction; (b) correct answers (F(2, 89) = 8.560,p < .001) and duration (F2,89) = 15.525,p < .001)in text comprehension; (c) correct answers (F(2, 92) = 8.975,p < .001) andduration (F(2, 92) = 4.360,p = .016) in metaphoric sentences comprehension; (d) correct answers (F(2, 92) = 12.836,p < .001) andduration (F(2, 92) = 10.974,p < .001) in verb form generation. Subtle changes in MCIsubtypes could affect sentence processing and provide useful information for cognitive decline risk estimation and screening purposes.

Meta-Analysis of Social Cognition in Mild Cognitive Impairment

Social cognitive abilities are impaired in Alzheimer disease and other dementias. Recent studies suggested that social cognitive abilities might be also impaired in mild cognitive impairment (MCI). Current meta-analysis aimed to summarize available evidence for deficits in theory of mind (ToM) and emotion recognition in MCI. In this meta-analysis of 17 studies, facial emotion recognition and ToM performances of 513 individuals with MCI and 693 healthy controls were compared. Mild cognitive impairment was associated with significant impairments falling in the medium effect sizes range in ToM ( d = 0.63) and facial emotion recognition ( d = 0.58). Among individual emotions, recognition of fear and sadness were particularly impaired. There were no significant between-group differences in recognition of disgust, happiness, and surprise. Social cognitive deficits were more severe in multidomain MCI. There is a need for longitudinal studies investigating the potential role of social cognitive impairment in predicting conversion to dementia.

Heterogeneity of Neuropsychological Impairment in HIV Infection: Contributions from Mild Cognitive Impairment

Despite longstanding acknowledgement of the heterogeneity of HIV-associated neurocognitive disorders (HAND), existing HAND diagnostic methods classify according to the degree of impairment, without regard to the pattern of neuropsychological strengths and weaknesses. Research in mild cognitive impairment (MCI) has demonstrated that classifying individuals into subtypes by both their level and pattern of impairment, using either conventional or statistical methods, has etiologic and prognostic utility. Methods for characterizing the heterogeneity of MCI provide a framework that can be applied to other disorders and may be useful in clarifying some of the current challenges in the study of HAND. A small number of studies have applied these methods to examine the heterogeneity of neurocognitive function among individuals with HIV. Most have supported the existence of multiple subtypes of neurocognitive impairment, with some evidence for distinct clinicodemographic features of these subtypes, but a number of gaps exist. Following a review of diagnostic methods and challenges in the study of HAND, we summarize the literature regarding conventional and empirical subtypes of MCI and HAND and identify directions for future research regarding neurocognitive heterogeneity in HIV infection.