Mild Cognitive Impairment Cases Research Articles

Patients With Congestive Heart Failure Show Greater Incidence Of Cognitive Impairment And Dementia

<h3>Background</h3> Cardiac disease, including heart failure (HF) and coronary artery disease (CAD), has been associated with cognitive decline. However, whether there are differences in the association of HF and CAD for incidence of mild cognitive impairment (MCI) or dementia, compared with a reference group, has not been extensively studied. We sought to determine whether HF, CAD, and/or exercise capacity (EC) predicts incidence of MCI or dementia. <h3>Methods</h3> The Mayo Clinic Study of Aging (MCSA), a prospective, population-based cohort study, was probed for this study. At baseline and every 15-months thereafter, subjects were evaluated for MCI and dementia using a standardized protocol involving neuropsychological testing and neurological evaluation. We grouped participants by (1) presence of HF, (2) absence of HF but presence of CAD, and (3) absence of both HF and CAD. Peak workload during maximal exercise test was used to determine EC using metabolic equivalent (MET) equations. Exercise testing data was obtained from clinical records, using the test closest to MCSA enrollment. To evaluate association with incident MCI or dementia, cox proportional hazard models were used adjusted for age, sex, and other clinical predictors of cognitive decline. Participants with MCI at baseline were excluded for MCI analysis and included as an adjustment variable for dementia analysis. <h3>Results</h3> We included 5812 MCSA participants (female: 50%; age: 70±13). Of those, 819 (14%) had HF, 1246 (21%) had CAD without HF, and 3747 participants were without HF or CAD. There were 688 (12%) participants with MCI at baseline. Mean follow-up was 3.9±3.7yrs, with 705 incident cases of MCI (14%) and 272 cases of dementia (5%). The HF group, CAD group, and EC were significant predictors of MCI and dementia (see <b>Table and Figure</b>), however, after adjustments, only HF predicted MCI (Hazard ratio: 1.57; 95% CI: 1.25-1.97; p<0.001) and dementia (Hazard ratio: 1.54; 95% CI: 1.09-2.19; p<0.05) (see <b>Table</b>). <h3>Conclusion</h3> After adjustment for age and known predictors of cognitive decline, participants with HF showed greater incidence of MCI and dementia than participants with and without CAD. Conversely, multivariate adjustment attenuated the effect of CAD without HF and baseline EC on incidence of MCI and dementia.

Temporal Speech Parameters Detect Mild Cognitive Impairment in Different Languages: Validation and Comparison of the Speech-GAP Test® in English and Hungarian.

The development of automatic speech recognition (ASR) technology allows the analysis of temporal (time-based) speech parameters characteristic of mild cognitive impairment (MCI). However, no information has been available on whether the analysis of spontaneous speech can be used with the same efficiency in different language environments. The main goal of this international pilot study is to address the question of whether the Speech-Gap Test® (S-GAP Test®), previously tested in the Hungarian language, is appropriate for and applicable to the recognition of MCI in other languages such as English. After an initial screening of 88 individuals, English-speaking (n = 33) and Hungarianspeaking (n = 33) participants were classified as having MCI or as healthy controls (HC) based on Petersen's criteria. The speech of each participant was recorded via a spontaneous speech task. Fifteen temporal parameters were determined and calculated through ASR. Seven temporal parameters in the English-speaking sample and 5 in the Hungarian-speaking sample showed significant differences between the MCI and the HC groups. Receiver operating characteristics (ROC) analysis clearly distinguished the English-speaking MCI cases from the HC group based on speech tempo and articulation tempo with 100% sensitivity, and on three more temporal parameters with high sensitivity (85.7%). In the Hungarian-speaking sample, the ROC analysis showed similar sensitivity rates (92.3%). The results of this study in different native-speaking populations suggest that changes in acoustic parameters detected by the S-GAP Test® might be present across different languages.

Late combination shows that MEG adds to MRI in classifying MCI versus controls

Early detection of Alzheimer's disease (AD) is essential for developing effective treatments. Neuroimaging techniques like Magnetic Resonance Imaging (MRI) have the potential to detect brain changes before symptoms emerge. Structural MRI can detect atrophy related to AD, but it is possible that functional changes are observed even earlier. We therefore examined the potential of Magnetoencephalography (MEG) to detect differences in functional brain activity in people with Mild Cognitive Impairment (MCI) – a state at risk of early AD. We introduce a framework for multimodal combination to ask whether MEG data from a resting-state provides complementary information beyond structural MRI data in the classification of MCI versus controls. More specifically, we used multi-kernel learning of support vector machines to classify 163 MCI cases versus 144 healthy elderly controls from the BioFIND dataset. When using the covariance of planar gradiometer data in the low Gamma range (30–48 Hz), we found that adding a MEG kernel improved classification accuracy above kernels that captured several potential confounds (e.g., age, education, time-of-day, head motion). However, accuracy using MEG alone (68%) was worse than MRI alone (71%). When simply concatenating (normalized) features from MEG and MRI into one kernel (Early combination), there was no advantage of combining MEG with MRI versus MRI alone. When combining kernels of modality-specific features (Intermediate combination), there was an improvement in multimodal classification to 74%. The biggest multimodal improvement however occurred when we combined kernels from the predictions of modality-specific classifiers (Late combination), which achieved 77% accuracy (a reliable improvement in terms of permutation testing). We also explored other MEG features, such as the variance versus covariance of magnetometer versus planar gradiometer data within each of 6 frequency bands (delta, theta, alpha, beta, low gamma, or high gamma), and found that they generally provided complementary information for classification above MRI. We conclude that MEG can improve on the MRI-based classification of MCI.

Differential diagnosis of vascular cognitive impairment

Background. Vascular cognitive impairment (VCI), аccording to world statistics, is the second most common cause of cognitive impairment after Alzheimer's disease (AD). Differential diagnosis between the two most common nosological forms of cognitive impairment is not always simple and is based on the clinical characteristic, neuropsychological and neuroradiological features of the disease.&#x0D; Aim. To present a differential diagnosis between VCI and AD using the example of a clinical case of vascular mild cognitive impairment.&#x0D; Materials and methods. A 68-year-old female patient with mild cognitive impairment underwent a neuropsychological testing: the Mini-mental state exam, Frontal assessment battery, the MoCA-test, the Clock-Drawing Test, the 12 Words test, Verbal Association Technique (literal and categorical), The Trail making test (A and B), The digit symbol substitution test, The Boston naming test (40 images), EXIT-25, Beck Depression Scale, Hospital anxiety and depression scale; neuroimaging magnetic resonance imaging in T1, T2, FLAIR, DWI, SWI sequence.&#x0D; Results. On the basis of clinical data, the results of neuropsychological testing and neuroimaging, the differential diagnosis with AD, the patient was diagnosed with vascular mild cognitive impairment. Nootropic therapy (choline alfoscerate) was prescribed and recommendations on risk factors correction were given.&#x0D; Conclusion. The article describes a patient with mild VCI. This case study discusses the main differences between AD and VCI that can be used as a basis for differential diagnosis. The features of cognitive impairments in VCI and AD are described, including the predominance of attention impairment, an executive function disorder in VCI and an impairment of memory progressing according to the Ribots law in AD. Differences in visuospatial skills and language in VCI and AD are discussed. The most reliable neuroradiological signs of cerebrovascular diseases are described.

Dementia Incidence, APOE Genotype, and Risk Factors for Cognitive Decline in Aboriginal Australians

Aboriginal Australians are disproportionately affected by dementia, with incidence in remote populations approximately double that of non-Indigenous populations. This study aimed to identify dementia incidence and risk factors in Aboriginal Australians residing in urban areas, which are currently unknown. A population-based cohort of Aboriginal Australians ≥60 years of age was assessed at baseline and 6-year follow-up. Life-course risk factors (baseline) were examined for incident dementia or mild cognitive impairment (MCI) through logistic regression analyses; adjustments were made for age. APOE genotyping was available for 86 people. Data were included from 155 participants 60 to 86 years of age (mean 65.70 years, SD 5.65 years; 59 male). There were 16 incident dementia cases (age-standardized rate 35.97/1,000 person-years, 95% confidence interval [CI] 18.34-53.60) and 36 combined incident MCI and dementia cases. Older age (odds ratio [OR] 2.29, 95% CI 1.42-3.70), male sex (OR 4.14, 95% CI 1.60-10.77), unskilled work history (OR 5.09, 95% CI 1.95-13.26), polypharmacy (OR 3.11, 95% CI 1.17-8.28), and past smoking (OR 0.24, 95% CI 0.08-0.75) were associated with incident MCI/dementia in the final model. APOE ε4 allele frequency was 24%; heterozygous or homozygous ε4 was associated with incident MCI/dementia (bivariate OR 3.96, 95% CI 1.25-12.50). These findings provide evidence for higher dementia incidence in Aboriginal Australians from urban areas, where the majority of Aboriginal people reside. This study also sheds light on sociodemographic, health, and genetic factors associated with incident MCI/dementia at older ages in this population, which is critical for targeted prevention strategies.

Dynamic balance deficit and the neural network in Alzheimer's disease and mild cognitive impairment

BackgroundPatients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI) exhibit balance deficits. Although only a few studies have evaluated the relationship between the brain images and balance indices. In this study, we measured balance indices, including the index of postural stability (IPS) and assessed the relationship between the brain images and their clinical motor and cognitive functional features. MethodsThe study included patients with MCI (N = 14) and patients with AD (N = 19). The primary outcome was IPS under a visual block condition and/or a proprioception block condition. In addition, 9 MCI and 8 AD patients underwent a 1.5-Tesla (1.5-T) Magnetic Resonance Imaging (MRI) scan, and the relationships between the MRI parameters and the balance indices were evaluated. ResultsThe IPS score was significantly lower in the AD group than the MCI group, but only under the closed eyes/hard surface condition. In terms of MRI, there was a significant positive correlation between the IPS and the regional betweenness centrality in the left hippocampal region. ConclusionsThe finding of a significantly lower IPS score under the closed eyes/hard surface condition in AD than in MCI cases suggests that the vestibular and/or proprioceptive systems were more severely impaired in AD than MCI cases. The results suggest that a dynamic balance disturbance due to deficits of the vestibular hippocampal pathway may be a useful marker for the diagnosis of MCI and detection of disease progression from MCI to AD.

Qualitative Assessment of Perfusion Maps Derived from Pulsed Arterial Spin Labeling Magnetic Resonance Imaging (PASL MRI) in Patients with Cognitive Disorders

Background: Dementia and its most common cause, Alzheimer's disease (AD), are growing health problems worldwide. In the pathological process, before the emergence of symptoms, magnetic resonance imaging (MRI) may be used as a non-invasive method for measuring brain perfusion. Objectives: This study aimed to investigate the feasibility and variability of brain perfusion maps derived from pulsed arterial spin labeling (PASL) MRI in a heterogeneous group of patients with cognitive disorders. Patients and Methods: In this cross-sectional study, 85 out of 134 patients with cognitive disorders, including 23 cases of AD, 24 cases of mild cognitive impairment (MCI), 31 cases of depression, and seven cases of subjective memory impairment (SMI), were considered eligible for the study. All patients were evaluated qualitatively with 3D PASL sequences, using inline cerebral blood flow (CBF) maps. Mental examinations and neuropsychological tests were also performed beforehand. Results: Based on the CBF maps, bilateral parietal hypoperfusion was significant in the AD and MCI groups (83 and 67%, respectively), compared to patients with depression or SMI (P &lt; 0.01). However, it was significantly low in depressed patients (13%), and there was no hypoperfusion in the SMI group. There was a good interobserver agreement, based on the kappa coefficient in all groups (0.78%; 95% CI: 0.65 - 0.91). Conclusion: The PASL MRI technique can be valuable for evaluating cognitive disorders, as it is non-invasive, rapid, and easily accessible. Besides, the qualitative assessment of CBF maps using this technique is reproducible and feasible in routine clinical practice.

Cognitive practice effects delay diagnosis of MCI: Implications for clinical trials.

IntroductionPractice effects (PEs) on cognitive tests obscure decline, thereby delaying detection of mild cognitive impairment (MCI). Importantly, PEs may be present even when there are performance declines, if scores would have been even lower without prior test exposure. We assessed how accounting for PEs using a replacement‐participants method impacts incident MCI diagnosis.MethodsOf 889 baseline cognitively normal (CN) Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 722 returned 1 year later (mean age = 74.9 ± 6.8 at baseline). The scores of test‐naïve demographically matched “replacement” participants who took tests for the first time were compared to returnee scores at follow‐up. PEs—calculated as the difference between returnee follow‐up scores and replacement participants scores—were subtracted from follow‐up scores of returnees. PE‐adjusted cognitive scores were then used to determine if individuals were below the impairment threshold for MCI. Cerebrospinal fluid amyloid beta, phosphorylated tau, and total tau were used for criterion validation. In addition, based on screening and recruitment numbers from a clinical trial of amyloid‐positive individuals, we estimated the effect of earlier detection of MCI by accounting for cognitive PEs on a hypothetical clinical trial in which the key outcome was progression to MCI.ResultsIn the ADNI sample, PE‐adjusted scores increased MCI incidence by 19% (P < .001), increased proportion of amyloid‐positive MCI cases (+12%), and reduced proportion of amyloid‐positive CNs (–5%; P’s < .04). Additional calculations showed that the earlier detection and increased MCI incidence would also substantially reduce necessary sample size and study duration for a clinical trial of progression to MCI. Cost savings were estimated at ≈$5.41 million.DiscussionDetecting MCI as early as possible is of obvious importance. Accounting for cognitive PEs with the replacement‐participants method leads to earlier detection of MCI, improved diagnostic accuracy, and can lead to multi‐million‐dollar cost reductions for clinical trials.

POSA182 Progression of Mild Cognitive Impairment Cases to Alzheimer's Disease: Life Study

Mild cognitive impairment (MCI) is the transitional stage between normal cognitive aging and dementia. In 2021, the US Food and Drug Administration approved the use of aducanumab for the treatment of Alzheimer's disease (AD). Collecting data on MCI-to-AD progression would be useful for future evaluations of its effectiveness. This study aimed to characterize the progression of new MCI cases in Japan using claims data.

Attention-deficit/hyperactivity disorder as a risk factor for dementia and mild cognitive impairment: a population-based register study.

AbstractBackgroundPrevious research has indicated that attention-deficit/hyperactivity disorder (ADHD) is associated with an increased risk for dementia, but studies are scarce and inconclusive. We aimed to investigate the association between ADHD, and dementia and mild cognitive impairment (MCI). Additionally, we aimed to investigate the impact of comorbid conditions, educational attainment, head injuries, other developmental disorders, and sex on the association.MethodsThe study population consisted of 3,591,689 individuals born between 1932 and 1963, identified from Swedish population-based registers. Cases of ADHD, dementia and MCI were defined according to ICD diagnostic codes and ATC codes for medication prescriptions. A Cox proportional hazards model was used to test the associations between ADHD, and dementia and MCI.ResultsIndividuals with ADHD had an increased risk for dementia and MCI. After adjusting for sex and birth year, a hazard ratio (HR) was 2.92 (95% confidence interval 2.40–3.57) for dementia, and 6.21 (5.25–7.35) for MCI. Additional adjustment for psychiatric disorders (depression, anxiety, substance use disorder, and bipolar disorder) substantially attenuated the associations, HR = 1.62 (1.32–1.98) for dementia, and 2.54 (2.14–3.01) for MCI. Common metabolic disorders (hypertension, type 2 diabetes, and obesity), sleep disorders, head injuries, educational attainment, and other developmental disorders, had a limited impact on the association. The association between ADHD and dementia was stronger in men.ConclusionsADHD is a potential risk factor for dementia and MCI, although the risk significantly attenuates after controlling for psychiatric disorders. Further research is needed to confirm these findings and to explore underlying mechanisms of the associations.

The Resilience Index: A Quantifiable Measure of Brain Health and Risk of Cognitive Impairment and Dementia.

There is increasing interest in lifestyle modification and integrative medicine approaches to treat and/or prevent mild cognitive impairment (MCI) and Alzheimer's disease and related dementias (ADRD). To address the need for a quantifiable measure of brain health, we created the Resilience Index (RI). This cross-sectional study analyzed 241 participants undergoing a comprehensive evaluation including the Clinical Dementia Rating and neuropsychological testing. Six lifestyle factors including physical activity, cognitive activity, social engagements, dietary patterns, mindfulness, and cognitive reserve were combined to derive the RI (possible range of scores: 1-378). Psychometric properties were determined. The participants (39 controls, 75 MCI, 127 ADRD) had a mean age of 74.6±9.5 years and a mean education of 15.8±2.6 years. The mean RI score was 138.2±35.6. The RI provided estimates of resilience across participant characteristics, cognitive staging, and ADRD etiologies. The RI showed moderate-to-strong correlations with clinical and cognitive measures and very good discrimination (AUC: 0.836; 95% CI: 0.774-0.897) between individuals with and without cognitive impairment (diagnostic odds ratio = 8.9). Individuals with high RI scores (> 143) had better cognitive, functional, and behavioral ratings than individuals with low RI scores. Within group analyses supported that controls, MCI, and mild ADRD cases with high RI had better cognitive, functional, and global outcomes than those with low RI. The RI is a brief, easy to administer, score and interpret assessment of brain health that incorporates six modifiable protective factors. Results from the RI could provide clinicians and researchers with a guide to develop personalized prevention plans to support brain health.

Longitudinal characterization of mild cognitive impairment and dementia in World Trade Center responders at midlife

AbstractBackgroundThough the Montreal Cognitive Assessment (MoCA) is validated for cross‐sectional assessment, there is limited guidance as to methods for reliably identifying incident cases of Mild Cognitive Impairment (MCI) and dementia. The goal of this study was to examine characteristics of individuals identified as having MCI and dementia using different diagnostic routines.MethodsWorld Trade Center (WTC) responders are a unique population, not only because of the historic significance of the traumatic exposures many endured while onsite following the terrorist attacks in New York City on 9/11/2001 but also given responders participation in a long‐term monitoring program established by the Centers for Disease Control (CDC) in 2002 to monitor the long‐term effects of WTC exposures on health outcomes. Since 2014, we have administered the MoCA to responders over at least three assessments (n=2,370). The MoCA was administered by trained research staff; alternate versions were used to account for learning. Seven diagnostic routines were examined that variably examined adjusting for learning, objective evidence of functional limitations, and cognitive decline to identify one with the least variability in outcome. Stability of diagnostic outcome was the primary outcome. Follow‐up studies in subsets of the population included a detailed computer‐assisted neuropsychological examination, measures of physical functional limitations, a cross‐sectional sample of plasma based biomarkers measured using Simoa (e.g., b‐Amyloid1‐40, b‐Amyloid1‐42, Total‐Tau, Glial Fibrillary Acidic Protein, and Neurofilament‐Light), a cross‐sectional assessment of cortical thickness, and a self‐reported version of the Mild Behavioral Checklist.Results8.0% of responders were male, 4.3% were Black, and 7.7% were Hispanic. The mean age at initial MoCA assessment was 52.6 years old (SD=8.1). There was enormous variability in longitudinal stability in MCI and dementia diagnostic outcomes between different longitudinal diagnostic routines (Spearman’s r=0.22‐0.86). Though domain‐specific sub‐scales with high internal consistency (a=0.92‐0.97) were available, the most stable definition relied on MoCA scores adjusted for learning and expected within‐person test‐retest score distributions. MCI and dementia identified using all diagnostic routines were variably associated poorer cognitive functioning and with biomarkers.ConclusionThis study gives guidance about differences between methods relying on the MoCA to longitudinally screen WTC responders for MCI and dementia at midlife.

Predictors of Incident Mild Cognitive Impairment and Its Course in a Diverse Community-Based Population.

Background and ObjectivesTo investigate sociodemographic and medical predictors of incident mild cognitive impairment (MCI) and subsequent course of MCI at follow-up, including sustained MCI diagnosis, classification as cognitively normal, and progression to dementia.MethodsWithin a community-based cohort, diagnoses of MCI were made with a published algorithm. Diagnosis of dementia was based on clinical consensus. Cox regressions estimated hazard ratios of incident MCI associated with several predictors. Modified Poisson regressions estimated relative risks associated with predictors of diagnostic status at follow-up after incidence.ResultsAmong 2,903 cognitively normal participants at baseline, 752 developed MCI over an average of 6.3 (SD 4.5) years (incidence rate 56 per 1,000 person-years). Presence of APOE ε4 and higher medical burden increased risk of incident MCI, while more years of education, more leisure activities, and higher income decreased this risk. Of the incident MCI cases, after an average of 2.4 years of follow-up, 12.9% progressed to dementia, 9.6% declined in functioning and did not meet the algorithmic criteria for MCI but did not meet the clinical criteria for dementia, 29.6% continued to meet MCI criteria, and 47.9% no longer met MCI criteria. Multidomain MCI, presence of APOE ε4, depressive symptoms, and antidepressant use increased the risk of progression to dementia.DiscussionThis community-based study showed that almost half of the individuals with incident MCI diagnoses were classified as cognitively normal at follow-up. Predictors of incident MCI demonstrably differed from those of subsequent MCI course; these findings can refine expectations for cognitive and functional course of those presenting with MCI.

Age-Related Cognitive Decline and Prevalence of Mild Cognitive Impairment in the Iwaki Health Promotion Project.

The Iwaki Health Promotion Project (IHPP) is a community-based study for the prevention of lifestyle-related diseases and improvement of quality of life. Between 2014 and 2017, a total of 4,442 Iwaki town residents from 19 to 93 years of age participated in annual surveys to clarify the natural course of age-related cognitive decline and mild cognitive impairment (MCI). Modified OLD and SED-11Q questionnaires, MMSE, Logical Memory II, educational history, and APOE genotypes were examined at the first screening. MCI and dementia were diagnosed at the second examination by detailed neurological examination, CDR, and MRI, and followed for 3 years. Spline regression analyses based on a linear mixed model was adopted for statistical analysis. MMSE scores declined with age from 55 to 64 years. There was also interaction between levels of education and ages. At the second examination, 56 MCI and 5 dementia patients were identified. None of the MCI cases progressed to dementia during the 3 years. During follow-up examinations, 13 cases showed improved MMSE scores (0.95 point/year), 5 remained stable, and 7 deteriorated (-0.83 point/year). Five cases showed improved CDR-SOB scores (-0.28 point/year), 9 remained stable, and 6 deteriorated (0.3 point/year). IHPP revealed that age- and education-related cognitive decline began and advanced from 55 years of age. The prevalence of MCI and dementia was estimated to be 5.9%in the Iwaki town cohort over 60 yeas of age. About 30%of MCI cases showed progression of cognitive decline.

Elderly Patients with Mild Cognitive Impairment Exhibit Altered Gut Microbiota Profiles.

Background As a transitional state between normal aging and Alzheimer's disease (AD), mild cognitive impairment (MCI) is characterized by a worse cognitive decline than that of natural aging. The association between AD and gut microbiota has been reported in a number of studies; however, microbial research regarding MCI remains limited. Methods This study examined 48 participants, of whom 22 were MCI cases and 26 were normal control cases. Fecal samples were collected for 16S ribosomal RNA (rRNA) quantitative arrays and bioinformatics analysis. Results A principal coordinates analysis (PCoA) and nonmetric multidimensional scaling (NMDS) both demonstrated that the microbial composition of participants with MCI deviated from that of healthy control participants. Multiple bacterial species were significantly increased (e.g., Staphylococcus intermedius) or decreased (e.g., Bacteroides salyersiae) in samples from the MCI group. Conclusion The composition of gut microbiota differed between normal control and MCI cases. This is the first study to identify a signature series of species in the gut microbiota of individuals with MCI. The results provide a new direction for the future development of an early diagnosis and probiotic regimen.

Multiple Connection Pattern Combination From Single-Mode Data for Mild Cognitive Impairment Identification.

Mild cognitive impairment (MCI) is generally considered to be a key indicator for predicting the early progression of Alzheimer’s disease (AD). Currently, the brain connection (BC) estimated by fMRI data has been validated to be an effective diagnostic biomarker for MCI. Existing studies mainly focused on the single connection pattern for the neuro-disease diagnosis. Thus, such approaches are commonly insufficient to reveal the underlying changes between groups of MCI patients and normal controls (NCs), thereby limiting their performance. In this context, the information associated with multiple patterns (e.g., functional connectivity or effective connectivity) from single-mode data are considered for the MCI diagnosis. In this paper, we provide a novel multiple connection pattern combination (MCPC) approach to combine different patterns based on the kernel combination trick to identify MCI from NCs. In particular, sixty-three MCI cases and sixty-four NC cases from the ADNI dataset are conducted for the validation of the proposed MCPC method. The proposed method achieves 87.40% classification accuracy and significantly outperforms methods that use a single pattern.

What Are the Key Points of Treatment for Cases of Mild Cognitive Impairment? Based on the Evaluation of Cognitive Function Tasks in the ADASJcog

Background/Aims: The aims of this study were to identify the degree of atrophy of the hippocampus in image findings and which cognitive function items should be focused on when treating mild cognitive impairment. Methods: A total of 66 cases with mild cognitive impairment were included in the study over a 1.5-year observation period. MR images were used to assess hippocampal atrophy, and cognitive function was assessed by the ADASJcog test. Results: In the mild dementia group, there was a hierarchical difference in the 4 cognitive impairments in which each degree was significantly higher hierarchically. In the normally improved group, memory and act dysfunction was significantly improved, and in deteriorated cases, memory, orientation, and act dysfunction increased significantly. The normally improved group tended to have lighter hippocampal atrophy than the deteriorating group. Discussion: In early treatment of mild cognitive impairment, it is important to focus on which cognitive items to treat, but there are no reports that present them numerically. Because it is not clear, there may be a risk that dementia may progress due to stunned treatment. It became clear that it was meaningful to show it, and it was the orientation and act function. Conclusion: It was suggested that hippocampal atrophy should be kept within the normal range and that the key treatment was mainly to improve memory and act dysfunction without reducing orientation function.

Abstract 10561: Attending Cardiac Rehabilitation Reduces Incidence of Dementia but Not Mild Cognitive Impairment in Patients with Coronary Artery Disease

Introduction: Coronary artery disease (CAD) has been associated with cognitive decline. Cardiac rehabilitation (CR) is a class 1A recommendation for patients with CAD as it reduces future cardiac events and mortality. However, the impact of CR on incidence of mild cognitive impairment (MCI) and dementia has not been extensively studied. We investigated the association of CAD on incidence of MCI and dementia; and whether CR attendance reduces incidence of MCI and dementia in patients with CAD Methods: The Mayo Clinic Study of Aging (MCSA), a prospective, population-based cohort was probed for this study. At baseline and every 15-months thereafter, subjects were evaluated for MCI and dementia using a standardized protocol. Data on CR participation were collected via record linkage to the Rochester Epidemiology Project. To evaluate association with incident MCI or dementia, cox proportional hazard models were used and adjusted for age, sex, and clinical predictors of cognitive decline. Participants with MCI at baseline were excluded for MCI analysis and adjusted for in dementia analysis. Results: We included 5960 MCSA participants (female: 50%; age: 70±13). Of those, 1934 participants (32%) had CAD and 702 (12%) had MCI at baseline. Mean follow-up was 3.9±3.7yrs, with 760 incident cases of MCI (13%) and 290 cases of dementia (5%). CAD was a significant predictor of MCI and dementia, although after adjustment for other clinical predictors, CAD was only associated with MCI incidence ( Table 1, Figure ). Incidence of dementia was reduced in CAD patients who had a greater attendance at CR when adjusted for other predictors of cognitive decline ( Table 2 ). Attendance at CR did not reduce incidence of MCI ( Table 2 ). Conclusions: CAD was a significant predictor of MCI and dementia. In patients with CAD, a higher attendance of CR was associated with reduced incidence of dementia but not MCI. Specific CR programming and outcome targets may be needed to prevent MCI in patients with CAD.

Carotid intima-media thickness and risk of mild cognitive impairment: A systematic review and meta-analysis.

Mild cognitive impairment (MCI) is an early phase of cognitive decline signalling the beginning of severe neurological diseases. Carotid intima-media thickness (cIMT) has shown some correlation with MCI development. This study was conducted to investigate the impact of elevated cIMT on the risk of MCI in adults. A literature search was conducted in PubMed, EMBASE, Cochrane Library, Scopus, Google Scholar and CINAHL databases till 30July 2021, with keywords: ('Carotid Intima-Media Thickness' OR 'cIMT' OR 'IMT' AND 'Cognitive Impairment' OR 'Cognition' OR 'Cognitive Decline' AND 'Mild Cognitive Impairment' OR 'MCI'). Pooled standardized mean difference (SMD)/odds ratio (OR) and 95% confidence interval (CI) were determined for factor-disease association using either fixed (when I2 <50%) or random effect (when I2 >50%) models. Eight studies involving 1,585MCI cases and 6,700 normal subjects were included in our meta-analysis which showed no significant association of increased cIMT with the risk of MCI [SMD 1.17, 95% CI -0.09 to 2.42]. However, sensitivity analysis revealed an outlier study significantly affecting the effect size. On omitting the outlier study, the re-evaluated meta-analysis revealed a significant association of cIMT with the risk of MCI [SMD 0.52, 95% CI 0.26 to 0.78]. This significant association was also observed during subgroup analysis in Caucasian population [SMD 0.65, 95% CI 0.13 to 1.18] but not in Asian population [SMD 0.39, 95% CI -0.01 to 0.79]. Elevated cIMT poses a potential risk for MCI. However, more population-based studies are required to corroborate these findings.

How Well Does Subjective Cognitive Decline Correspond to Objectively Measured Cognitive Decline? Assessment of 10-12 Year Change.

Although not strongly correlated with current objective cognitive ability, subjective cognitive decline (SCD) is a risk factor for Alzheimer's disease. Most studies focus on SCD in relation to future decline rather than objective prior decline that it purportedly measures. We evaluated whether self-report of cognitive decline-as a continuous measure-corresponds to objectively-assessed episodic memory and executive function decline across the same period. 1,170 men completed the Everyday Cognition Questionnaire (ECog) at mean age 68 assessing subjective changes in cognitive ability relative to 10 years prior. A subset had mild cognitive impairment (MCI), but MCI was diagnosed without regard to subjective decline. Participants completed up to 3 objective assessments of memory and executive function (M = 56, 62, and 68 years). Informant-reported ECogs were completed for 1,045 individuals. Analyses controlled for depression and anxiety symptoms assessed at mean age 68. Participant-reported ECog scores were modestly associated with objective decline for memory (β= -0.23, 95%CI [-0.37, -0.10]) and executive function (β= -0.19, 95%CI [-0.33, -0.05]) over the same time period. However, these associations were nonsignificant after excluding MCI cases. Results were similar for informant ratings. Participant-rated ECog scores were more strongly associated with concurrent depression and anxiety symptoms, (β= 0.44, 95%CI [0.36,0.53]). Continuous SCD scores are correlated with prior objective cognitive changes in non-demented individuals, though this association appears driven by individuals with current MCI. However, participants' current depression and anxiety ratings tend to be strongly associated with their SCD ratings. Thus, what primarily drives SCD ratings remains unclear.