Deterioration and predictive values of semantic networks in mild cognitive impairment

2022 ◽  
Vol 61 ◽  
pp. 101025
Author(s):  
Hsin-Te Chang ◽  
Ming-Jang Chiu ◽  
Ta-Fu Chen ◽  
Meng-Ying Liu ◽  
Wan-Chun Fan ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Semantic Networks ◽  
Predictive Values

Association of Neutrophil-Lymphocyte Ratio with Mild Cognitive Impairment in Elderly Chinese Adults: A Case-control Study

2020 ◽  
Vol 16 (14) ◽  
pp. 1309-1315
Author(s):  
Peilin An ◽  
Xuan Zhou ◽  
Yue Du ◽  
Jiangang Zhao ◽  
Aili Song ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Function ◽  
Predictive Values ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Elderly Chinese ◽  
Normal Cognitive Function ◽  
The Absolute

Background: Inflammation plays a significant role in the pathophysiology of cognitive impairment in previous studies. Neutrophil-lymphocyte ratio (NLR) is a reliable measure of systemic inflammation. Objective: The aim of this study was to investigate the association between NLR and mild cognitive impairment (MCI), and further to explore the diagnostic potential of the inflammatory markers NLR for the diagnosis of MCI in elderly Chinese individuals. Methods: 186 MCI subjects and 153 subjects with normal cognitive function were evaluated consecutively in this study. Neutrophil (NEUT) count and Lymphocyte (LYM) count were measured in fasting blood samples. The NLR was calculated by dividing the absolute NEUT count by the absolute LYM count. Multivariable logistic regression was used to evaluate the potential association between NLR and MCI. NLR for predicting MCI was analyzed using Receiver Operating Characteristic (ROC) curve analysis. Results: The NLR of MCI group was significantly higher than that of subjects with normal cognitive function (2.39 ± 0.55 vs. 1.94 ± 0.51, P < 0.001). Logistic regression analysis showed that higher NLR was an independent risk factor for MCI (OR: 4.549, 95% CI: 2.623-7.889, P < 0.001). ROC analysis suggested that the optimum NLR cut-off point for MCI was 2.07 with 73.66% sensitivity, 69.28% specificity, 74.48% Positive Predictive Values (PPV) and 68.36% negative predictive values (NPV). Subjects with NLR ≥ 2.07 showed higher risk relative to NLR < 2.07 (OR: 5.933, 95% CI: 3.467-10.155, P < 0.001). Conclusion: The elevated NLR is significantly associated with increased risk of MCI. In particular, NLR level higher than the threshold of 2.07 was significantly associated with the probability of MCI.

scholarly journals Predicting outcome in mild cognitive impairment: 4-year follow-up study

2010 ◽  
Vol 197 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Jane A. Lonie ◽  
Mario A. Parra-Rodriguez ◽  
Kevin M. Tierney ◽  
Lucie L. Herrmann ◽  
Claire Donaghey ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Neuropsychological Assessment ◽  
Verbal Learning ◽  
Cognitive Screening ◽  
Prognostic Information ◽  
Predictive Values ◽  
Diagnosis And Prognosis ◽  
Demographic Indices ◽  
Sensitivity Specificity

BackgroundCognitive impairment precedes the diagnosis of Alzheimer's disease. It is unclear which psychometric measures predict dementia, and what cut-off points should be used. Replicable cognitive measures to provide information about differential diagnosis and prognosis would be clinically useful.AimsIn a prospective cohort study we investigated which measures distinguish between individuals with amnestic mild cognitive impairment (aMCI) that converts to dementia and those whose impairment does not, and which combination of measures best predicts the fate of people with aMCI.MethodForty-four participants with aMCI underwent extensive neuropsychological assessment at baseline and annually thereafter for an average of 4 years. Differences in baseline cognitive performance of participants who were converters and non-converters to clinically diagnosed dementia were analysed. Classification accuracy was estimated by sensitivity, specificity, positive and negative predictive values and using logistic regression.ResultsForty-one percent of participants had progressed to dementia by the end of study, with a mean annual conversion rate of 11%. Most (63%) showed persisting or progressive cognitive impairment, irrespective of diagnosis. The Addenbrooke's Cognitive Examination together with the discrimination index of the Hopkins Verbal Learning Test – Revised (but none of the demographic indices) differentiated the participants who were converters from the non-converters at baseline with 74% accuracy.ConclusionsTargeted neuropsychological assessment, beyond simple cognitive screening, could be used in clinical practice to provide individuals with aMCI with prognostic information and aid selective early initiation of monitoring and treatment among those who progress towards a clinically diagnosable dementia.

scholarly journals Montreal Cognitive Assessment Is Superior to Standardized Mini-Mental Status Exam in Detecting Mild Cognitive Impairment in the Middle-Aged and Elderly Patients with Type 2 Diabetes Mellitus

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Kannayiram Alagiakrishnan ◽  
Nancy Zhao ◽  
Laurie Mereu ◽  
Peter Senior ◽  
Ambikaipakan Senthilselvan
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Assessment ◽  
Predictive Values ◽  
Mini Mental Status Exam ◽  
Mental Status Exam

Aim. This study compares the usefulness of Montreal Cognitive Assessment (MoCA) to Standardized Mini-Mental Status Exam (SMMSE) for diagnosing mild cognitive impairment (MCI) in Type 2 diabetes mellitus (DM) population.Methods. This prospective pilot study enrolled 30 community dwelling adults with Type 2 DM aged 50 years and above. Subjects were assessed using both the SMMSE and MoCA for MCI. In all subjects, depression and dementia were ruled out using the DSM IV criteria, and a functional assessment was done. MCI was diagnosed using the standard test, the European consortium criteria. Sensitivity and specificity analysis, positive and negative predictive values, likelihood ratios and Kappa statistic were calculated.Results. In comparison to consortium criteria, the sensitivity and specificity of MoCA were 67% and 93% in identifying individuals with MCI, and SMMSE were 13% and 93%, respectively. The positive and negative predictive values for MoCA were 84% and 56%, and for SMMSE were 66% and 51%, respectively. Kappa statistics showed moderate agreement between MoCA and consortium criteria (kappa = 0.4) and a low agreement between SMMSE and consortium criteria (kappa = 0.07).Conclusion. In this pilot study, MoCA appears to be a better screening tool than SMMSE for MCI in the diabetic population.

scholarly journals The Inflammasome Adaptor Protein ASC in Mild Cognitive Impairment and Alzheimer’s Disease

2020 ◽  
Vol 21 (13) ◽  
pp. 4674 ◽  
Author(s):  
Xavier O. Scott ◽  
Marisa E. Stephens ◽  
Marie C. Desir ◽  
W. Dalton Dietrich ◽  
Robert W. Keane ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Memory Loss ◽  
Adaptor Protein ◽  
Therapeutic Window ◽  
Likelihood Ratios ◽  
Predictive Values ◽  
Protein Levels

Mild cognitive impairment (MCI) is characterized by memory loss in the absence of dementia and is considered the translational stage between normal aging and early Alzheimer’s disease (AD). Patients with MCI have a greater risk of advancing to AD. Thus, identifying early markers of MCI has the potential to increase the therapeutic window to treat and manage the disease. Protein levels of the inflammasome signaling proteins apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and interleukin (IL)-18 were analyzed in the serum of patients with MCI, AD and healthy age-matched donors as possible biomarkers, as well as levels of soluble amyloid precursor proteins α/β (sAPP α/β) and neurofilament light (NfL). Cut-off points and positive and negative predictive values, as well as receiver operator characteristic (ROC) curves, likelihood ratios and accuracy were determined for these proteins. Although the levels of ASC were higher in MCI and AD than in age-matched controls, protein levels of ASC were higher in MCI than in AD cases. For control vs. MCI, the area under the curve (AUC) for ASC was 0.974, with a cut-off point of 264.9 pg/mL. These data were comparable to the AUC for sAPP α and β of 0.9687 and 0.9068, respectively, as well as 0.7734 for NfL. Moreover, similar results were obtained for control vs. AD and MCI vs. AD. These results indicate that ASC is a promising biomarker of MCI and AD.

scholarly journals Cognitive-Communicative Predictors of Mild Cognitive Impairment: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 16 (4) ◽  
pp. 276-294
Author(s):  
Mi Sook Lee
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Meta Analysis ◽  
Target Population ◽  
Moderate Level ◽  
Effect Sizes ◽  
Evidence Based ◽  
Word Fluency ◽  
Predictive Values ◽  
Level Effect

Mild cognitive impairment (MCI) is the preclinical stage and sign of dementia. It is also important for guidance in the prevention and intervention of neurological disease. The purpose of this study was to review literatures on cognitive/communicative and other predictors of MCI patients systematically, and to propose the evidence-based data including effect sizes of them using a meta-analysis method. Fifty-seven researches published since 2010, meeting the inclusion and exclusion criteria, were entered into the analysis. They were analyzed in a methodological and content level, and the effect sizes were calculated by 3 predictors. Predictive values were pooled from cognitive (10 domains), communicative (9 domains), and other (3 domains). The main findings were as follows. Firstly, the general target population for studies was older adults over the age of 55, and most studies included at least 2 types of predictors. Secondly, average effect sizes of 3 predictors in MCI were all significant. Thirdly, cognitive predictors like memory and general cognition had significant and high-level effect sizes. Fourthly, communicative predictors including comprehension and word fluency had moderate-level effect sizes significantly. Lastly, all demographic and neuropsychological (age, education, depression) predictors had significant and moderate-level effect sizes. Our results provide the evidence-based information to predict MCI. Especially, specific cognitive and communicative predictors may contribute to increase the diagnostic and prognostic accuracy in MCI. This study is also expected to present clinically available data and increase the effect in intervention for MCI.

Artificial Neural Networks Identify the Predictive Values of Risk Factors on the Conversion of Amnestic Mild Cognitive Impairment

2010 ◽  
Vol 19 (3) ◽  
pp. 1035-1040 ◽  
Author(s):  
Massimo Tabaton ◽  
Patrizio Odetti ◽  
Sergio Cammarata ◽  
Roberta Borghi ◽  
Fiammetta Monacelli ◽  
...  
Keyword(s):  
Risk Factors ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Amnestic Mild Cognitive Impairment ◽  
Predictive Values ◽  
Artificial Neural

scholarly journals On Gaps of Clinical Diagnosis of Dementia Subtypes: A Study of Alzheimer's Disease and Lewy Body Disease

2021 ◽  
Author(s):  
Hui Wei ◽  
Arjun V Masurkar ◽  
Narges Sharif Razavian
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Clinical Diagnosis ◽  
Lewy Body ◽  
False Negative ◽  
Lewy Body Disease ◽  
Clinical Dementia Rating ◽  
Predictive Values ◽  
Diagnostic Uncertainty ◽  
Specificity And Sensitivity

BACKGROUND: Alzheime's disease (AD) and Lewy body disease (LBD) are the two most common neurodegenerative dementias, and can occur in combination (AD+LBD). Due to overlapping biomarkers and symptoms, especially at early stages, clinical differentiation of these subtypes could be difficult. Yet it is unclear how the magnitude of diagnostic uncertainty varies across the dementia spectrum and demographic variables. We aimed to compare clinical diagnosis and post-mortem autopsy-confirmed pathological results to assess the clinical subtype diagnosis quality across these various factors. METHODS: We studied data from the National Alzheimer's Coordinating Center. Selection criteria included an autopsy-based neuropathological assessment for AD and/or LBD, and initial visit with Clinical Dementia Rating CDR Dementia Staging Instrument (CDR) of 0, 0.5, or 1.0 corresponding to normal, mild cognitive impairment, or mild dementia, respectively. Longitudinally, we analyzed first visits at each subsequent CDR stage, and focused on the clinical diagnosis for AD and/or LBD in these visits. This analysis included positive predictive values (PPV), specificity and sensitivity and false negative rates of the clinical diagnosis, as well as disparities in these metrics by sex, race/ethnicity, age and education. If autopsy-confirmed AD, LBD, or AD+LBD was missed, the alternative clinical diagnosis was analyzed. FINDINGS: Records of 1887 qualified participants from September 1, 2005 to August 20, 2019 were included in the study. Clinical diagnosis of AD+LBD had poor sensitivity from 2.7% (95% CI: 1.2%, 4.8%) at CDR 0.5 to 4.7% (2.1%, 7.8%) at CDR 3.0. Over 60% of participants with autopsy-confirmed AD+LBD were diagnosed clinically as AD. Clinical diagnosis of AD had low sensitivities at early dementia stage (56.8% (95% CI: 52.4%, 61.1%)) and low specificities at all stages. Among participants diagnosed as AD in the clinic, over 33% had concurrent LBD neuropathology at autopsy. Clinical diagnosis of LBD had poor PPVs from mild cognitive impairment (22% (95% CI: 12%, 33%)) to severe dementia (20% (95% CI: 9%, 33%)). Among participants diagnosed as LBD in the clinic, 32% to 54% revealed AD pathology during autopsy. When the three subtypes were missed by clinicians, "No cognitive impairment", "Undecided" and "primary progressive aphasia or behavioral variant frontotemporal dementia" were the leading primary etiologic clinical diagnosis. With increasing dementia stages, the difference in clinical diagnosis accuracy significantly increased between White and Black/African-American participants, and diagnosis quality significantly improved for males but not for females. INTERPRETATION: Our findings demonstrate that clinical diagnosis of AD, LBD and AD+LBD are inaccurate and harbor significant disparities based on race and sex. These findings have important implications for clinical management, anticipatory guidance, trial enrollment, and applicability of potential disease modifying therapies for AD. They also promote research into better biomarker-based assessment of LBD pathology.

Mild cognitive impairment and dementia in older patients attending a general hospital in south India: DSM-5 standards and correlates

2018 ◽  
Vol 31 (1) ◽  
pp. 133-138 ◽  
Author(s):  
Abu P. Varghese ◽  
J. Prasad ◽  
K. S. Jacob
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
General Hospital ◽  
Economic Status ◽  
Screening Instruments ◽  
Predictive Values ◽  
Cognitive Domains ◽  
Dsm 5 ◽  
Co Morbidity ◽  
Sensitivity Specificity

ABSTRACTBackground and Aims:The changes in DSM-5 diagnostic criteria for dementia (Major neurocognitive disorder (NCD)) and mild cognitive impairment (mild NCD) mandate a re-evaluation of screening instruments. This study attempted to validate screening instruments, identify optimum threshold, and describe their indices of efficacy.Method:Consecutive people above the age of 65 years attending the outpatient department of a general hospital were recruited. They were assessed using the Mini-Mental State Examination and the Vellore Screening Instruments for Dementia and were evaluated against the DSM-5 standard. Bivariate and multivariate statistics were obtained. Receiver-operating-characteristic curves were drawn, optimum thresholds obtained, sensitivity, specificity, and predictive values calculated.Results:One hundred and thirty four older people were recruited. The majority were women, married, with low levels of education, not employed, living with family, and had medical co-morbidity. A minority satisfied DSM-5 criteria for major (1.5%) and mild NCD (36.5%). The factors associated with NCD were older age, fewer years of education, and lower socio-economic status. MMSE, VSID patient, and VSID informant scores were significantly associated with NCD. The indices of efficacy for the MMSE and VSID patient version were modest for identifying Mild NCD. However, their performance in identifying major NCD was better. Nevertheless, optimal thresholds for recognition differed markedly from their originally recommended cut-offs.Conclusions:The DSM-5 standards, with new and different cognitive domains, mandate a revaluation and recalibration of existing screening instruments. Ideally, new screening instruments, which match the cognitive domains and DSM-5 standard should be developed.

scholarly journals The “Alzheimer's Type” Profile of Semantic Clustering in Amnestic Mild Cognitive Impairment

2014 ◽  
Vol 20 (4) ◽  
pp. 402-412 ◽  
Author(s):  
Paula M. McLaughlin ◽  
Matthew J. Wright ◽  
Michael LaRocca ◽  
Peter T. Nguyen ◽  
Edmond Teng ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Healthy Aging ◽  
Verbal Learning ◽  
Semantic Networks ◽  
Amnestic Mild Cognitive Impairment ◽  
California Verbal Learning Test ◽  
Short Delay ◽  
Semantic Clustering ◽  
Memory Strategy

AbstractImpairments in learning and recall have been well established in amnestic mild cognitive impairment (aMCI). However, a relative dearth of studies has examined the profiles of memory strategy use in persons with aMCI relative to those with Alzheimer's disease (AD). Participants with aMCI, nonamnestic MCI, AD, and healthy older adults were administered the California Verbal Learning Test-II (CVLT-II). Measures of semantic clustering and recall were obtained across learning and delayed recall trials. In addition, we investigated whether deficits in semantic clustering were related to progression from healthy aging to aMCI and from aMCI to AD. The aMCI group displayed similar semantic clustering performance as the AD participants, whereas the AD group showed greater impairments on recall relative to the aMCI participants. Control participants who progressed to aMCI showed reduced semantic clustering at the short delay at baseline compared to individuals who remained diagnostically stable across follow-up visits. These findings show that the ability to engage in an effective memory strategy is compromised in aMCI, before AD has developed, suggesting that disruptions in semantic networks are an early marker of the disease. (JINS, 2014, 20, 1–11)

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