scholarly journals Cut-Off Scores of an Olfactory Function Test for Mild Cognitive Impairment and Dementia

2020 ◽  
Vol 17 (10) ◽  
pp. 1021-1030 ◽  
Author(s):  
Hye Ri Kim ◽  
Sun Mi Kim ◽  
Wonshik Seong ◽  
Hyun Jin Min ◽  
Kyung Soo Kim ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Clinical Symptoms ◽  
Detection Threshold ◽  
Area Under The Curve ◽  
Olfactory Function ◽  
Odor Identification ◽  
Odor Detection ◽  
Function Tests ◽  
Odor Detection Threshold

Objective We aimed to find the optimal cut-off scores for screening of odor detection threshold, odor discrimination, and odor identification tests for detection of mild cognitive impairment (MCI) and dementia in Korean elderly.Methods A total of 195 elderly people were divided into three groups: the normal cognition (NC), MCI, and dementia groups. All participants underwent neurocognitive and olfactory function tests. We used k-means cluster analysis and receiver operating characteristic (ROC) analysis to identify the most appropriate cut-off value.Results To distinguish the MCI from NC groups, odor identification [area under the curve (AUC)=0.670, p<0.007] with a cut-off point of 7 showed greater validity for screening (sensitivity/specificity=0.462/0.837) than did other olfactory function tests. To distinguish the MCI and dementia from NC as well, odor identification (AUC=0.817, p=0.002) with a cut-off point of 7 showed the highest validity for screening (0.785/0.654). To distinguish MCI from AD, an odor detection threshold (AUC=0.722, p=0.001) with a cut-off point of 2 showed the highest validity for screening (0.785/0.654).Conclusion Olfactory function tests may be a useful screening tool for cognitive decline before clinical symptoms of dementia have completely developed. This tool can be used as a supplementary tool to enhance the sensitivity of traditional cognitive tests to screen for dementia.

scholarly journals Odor detection threshold, but not odor identification, is impaired in children with autism

2011 ◽  
Vol 20 (7) ◽  
pp. 333-340 ◽  
Author(s):  
Iva Dudova ◽  
Jan Vodicka ◽  
Marketa Havlovicova ◽  
Zdenek Sedlacek ◽  
Tomas Urbanek ◽  
...  
Keyword(s):  
Detection Threshold ◽  
Children With Autism ◽  
Odor Identification ◽  
Odor Detection ◽  
Odor Detection Threshold

scholarly journals A score based on screening tests to differentiate mild cognitive impairment from subjective memory complaints

2013 ◽  
Vol 5 (3) ◽  
pp. 16 ◽  
Author(s):  
Fábio Henrique De Gobbi Porto ◽  
Lívia Spíndola ◽  
Maira Okada De Oliveira ◽  
Patrícia Helena Figuerêdo Do Vale ◽  
Marco Orsini ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Characteristic Curve ◽  
Neuropsychological Testing ◽  
Area Under The Curve ◽  
Screening Tests ◽  
Elderly Subjects ◽  
Subjective Memory ◽  
Delayed Recall ◽  
Memory Complaints

It is not easy to differentiate patients with mild cognitive impairment (MCI) from subjective memory complainers (SMC). Assessments with screening cognitive tools are essential, particularly in primary care where most patients are seen. The objective of this study was to evaluate the diagnostic accuracy of screening cognitive tests and to propose a score derived from screening tests. Elderly subjects with memory complaints were evaluated using the Mini Mental State Examination (MMSE) and the Brief Cognitive Battery (BCB). We added two delayed recalls in the MMSE (a delayed recall and a late-delayed recall, LDR), and also a phonemic fluency test of letter P fluency (LPF). A score was created based on these tests. The diagnoses were made on the basis of clinical consensus and neuropsychological testing. Receiver operating characteristic curve analyses were used to determine area under the curve (AUC), the sensitivity and specificity for each test separately and for the final proposed score. MMSE, LDR, LPF and delayed recall of BCB scores reach statistically significant differences between groups (P=0.000, 0.03, 0.001 and 0.01, respectively). Sensitivity, specificity and AUC were MMSE: 64%, 79% and 0.75 (cut off &lt;29); LDR: 56%, 62% and 0.62 (cut off &lt;3); LPF: 71%, 71% and 0.71 (cut off &lt;14); delayed recall of BCB: 56%, 82% and 0.68 (cut off &lt;9). The proposed score reached a sensitivity of 88% and 76% and specificity of 62% and 75% for cut off over 1 and over 2, respectively. AUC were 0.81. In conclusion, a score created from screening tests is capable of discriminating MCI from SMC with moderate to good accurancy.

The Brief Odor Detection Test (B-ODT) for Very Early Diagnosis of Cognitive Decline: A Preliminary Study

2017 ◽  
Vol 18 (2) ◽  
pp. 197-210
Author(s):  
Dimitra Savvoulidou ◽  
Efthymia Totikidou ◽  
Chariklia Varvesiotou ◽  
Magda Iakovidou ◽  
Ourania Sfakianaki ◽  
...  
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Adult Population ◽  
Detection Threshold ◽  
Community Dwelling ◽  
Odor Detection ◽  
Olfactory Impairment ◽  
Older Adult Population ◽  
Community Dwelling Older Adults

Olfactory impairment in older adults is associated with cognitive decline. This study describes the development of a Brief Odor Detection Test (B-ODT), and its pilot administration in community-dwelling older adults. The study aimed at examining whether the test could differentiate older adults with very mild cognitive impairment from their cognitively healthy counterparts. The sample consisted of 34 older adults (22 women), aged from 65 to 87 years. Participants were divided into two groups according to their general cognitive functioning. Odor detection was measured via vanillin solutions at the following concentrations: 150 mg/L, 30 mg/L, 15 mg/L, 3 mg/L, and .03 mg/L. The first condition of the test involved a scale administration of vanillin solutions. The second condition examined the change in air odour and it required vanillin solution of 30 mg/L and a metric ruler of 30 cm. The examiner had to place the solution at a specific distance point from each nostril. Odour identification sensitivity was secondarily measured. The results showed statistically significant differences in odour detection threshold between the two groups. In the unirhinal testing, left nostril differences of the two groups were definite. Hence, the B-ODT seems a promising instrument for very early cognitive impairment screening in older adult population.

scholarly journals 12-year prediction of mild cognitive impairment aided by Alzheimer’s brain signatures at mean age 56

2021 ◽  
Author(s):  
McKenna E Williams ◽  
Jeremy A Elman ◽  
Linda K McEvoy ◽  
Ole A Andreassen ◽  
Anders M Dale ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Mean Diffusivity ◽  
Area Under The Curve ◽  
Polygenic Risk Score ◽  
Age Difference ◽  
Cognitively Normal ◽  
Brain Age

Abstract Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer’s disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Toward that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: 1) a validated MRI-derived Alzheimer’s disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and 2) a novel gray matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246–367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51–60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer’s disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61–71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply aging-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P=0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently-derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step toward improving very early identification of Alzheimer’s disease risk and the potential value of mean diffusivity and/or multimodal brain signatures.

scholarly journals To Explore the Predictive Power of Visuomotor Network Dysfunctions in Mild Cognitive Impairment and Alzheimer’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Justine Staal ◽  
Francesco Mattace-Raso ◽  
Hennie A. M. Daniels ◽  
Johannes van der Steen ◽  
Johan J. M. Pel
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Support Vector Machine ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Predictive Power ◽  
Area Under The Curve ◽  
Classification Performance ◽  
Support Vector ◽  
Potential Biomarker

BackgroundResearch into Alzheimer’s disease has shifted toward the identification of minimally invasive and less time-consuming modalities to define preclinical stages of Alzheimer’s disease.MethodHere, we propose visuomotor network dysfunctions as a potential biomarker in AD and its prodromal stage, mild cognitive impairment with underlying the Alzheimer’s disease pathology. The functionality of this network was tested in terms of timing, accuracy, and speed with goal-directed eye-hand tasks. The predictive power was determined by comparing the classification performance of a zero-rule algorithm (baseline), a decision tree, a support vector machine, and a neural network using functional parameters to classify controls without cognitive disorders, mild cognitive impaired patients, and Alzheimer’s disease patients.ResultsFair to good classification was achieved between controls and patients, controls and mild cognitive impaired patients, and between controls and Alzheimer’s disease patients with the support vector machine (77–82% accuracy, 57–93% sensitivity, 63–90% specificity, 0.74–0.78 area under the curve). Classification between mild cognitive impaired patients and Alzheimer’s disease patients was poor, as no algorithm outperformed the baseline (63% accuracy, 0% sensitivity, 100% specificity, 0.50 area under the curve).Comparison with Existing Method(s)The classification performance found in the present study is comparable to that of the existing CSF and MRI biomarkers.ConclusionThe data suggest that visuomotor network dysfunctions have potential in biomarker research and the proposed eye-hand tasks could add to existing tests to form a clear definition of the preclinical phenotype of AD.

scholarly journals Predicting the future development of mild cognitive impairment in the cognitively healthy elderly

2020 ◽  
Author(s):  
Bryan Strange ◽  
Linda Zhang ◽  
Alba Sierra-Marcos ◽  
Eva Alfayate ◽  
Jussi Tohka ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Memory ◽  
Statistical Tests ◽  
Treatment Strategies ◽  
Area Under The Curve ◽  
Predictive Performance ◽  
Healthy Individuals ◽  
Healthy Elderly ◽  
Out Of Sample

Identifying measures that predict future cognitive impairment in healthy individuals is necessary to inform treatment strategies for candidate dementia-preventative and modifying interventions. Here, we derive such measures by studying converters who transitioned from cognitively normal at baseline to mild-cognitive impairment (MCI) in a longitudinal study of 1213 elderly participants. We first establish reduced grey matter density (GMD) in left entorhinal cortex (EC) as a biomarker for impending cognitive decline in healthy individuals, employing a matched sampling control for several dementia risk-factors, thereby mitigating the potential effects of bias on our statistical tests. Next, we determine the predictive performance of baseline demographic, genetic, neuropsychological and MRI measures by entering these variables into an elastic net-regularized classifier. Our trained statistical model classified converters and controls with validation Area-Under-the-Curve>0.9, identifying only delayed verbal memory and left EC GMD as relevant predictors for classification. This performance was maintained on test classification of out-of-sample converters and controls. Our results suggest a parsimonious but powerful predictive model for MCI development in the cognitively healthy elderly.

Relationship between the Differences of Odor Detection Threshold Values Measured by Different Methods and some of the Physicochemical Properties

2013 ◽  
Vol 807-809 ◽  
pp. 451-455 ◽  
Author(s):  
Di Fang ◽  
Jie Min Liu ◽  
Qin Yi
Keyword(s):  
Physicochemical Properties ◽  
Functional Group ◽  
Saturated Vapor ◽  
Detection Threshold ◽  
Threshold Values ◽  
Odor Detection ◽  
Linear Relationships ◽  
Odor Detection Threshold ◽  
The Difference ◽  
The Relationship

The amount of sample can enter the nasal cavity depends on the physiochemical characteristics such as distribution, volatility and solubility. It can be suspected that the difference of odor detection threshold (ODT) measured by different methods is related to the physicochemical properties of compounds. To investigate the relationship between ODT differences and the physicochemical properties of compounds, ODT values of four series of organic compounds were measured by triangle odor bag method and gas chromatography and olfactometry method; the results were compared and the absolute differences were calculated. Relationship between ODT differences and the type of functional group and some of the physicochemical properties of compounds was analyzed. The results showed the type of functional group had significant effect on the differences. Certain linear relationships between the logarithmic value of differences and the logarithmic values of saturated vapor pressure and molecular weight were observed.

Combined Memory and Executive Function Tests Can Screen Mild Cognitive Impairment and Converters to Dementia in a Community: The Osaki-Tajiri Project

2009 ◽  
Vol 33 (2) ◽  
pp. 103-110 ◽  
Author(s):  
Eriko Nakata ◽  
Mari Kasai ◽  
Masashi Kasuya ◽  
Kyoko Akanuma ◽  
Mitsue Meguro ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Executive Function ◽  
Mild Cognitive Impairment ◽  
Function Tests

scholarly journals Detection of mild cognitive impairment and early stage dementia with an audio-recorded cognitive scale

2013 ◽  
Vol 25 (8) ◽  
pp. 1325-1333 ◽  
Author(s):  
Margaret C. Sewell ◽  
Xiaodong Luo ◽  
Judith Neugroschl ◽  
Mary Sano
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Memory ◽  
Early Stage ◽  
Neuropsychological Testing ◽  
Area Under The Curve ◽  
Cognitive Domain ◽  
Screening Measures

ABSTRACTBackground: Physicians often miss diagnosis of mild cognitive impairment (MCI) or early dementia and screening measures can be insensitive to very mild impairments. Other cognitive assessments may take too much time or be frustrating to seniors. This study examined the ability of an audio-recorded scale, developed in Australia, to detect MCI or mild Alzheimer's disease (AD) and compared cognitive domain-specific performance on the audio-recorded scale to in-person battery and common cognitive screens.Method: Seventy-six patients from the Mount Sinai Alzheimer's Disease Research Center were recruited. Patients were aged 75 years or older, with clinical diagnosis of AD or MCI (n = 51) or normal control (n = 25). Participants underwent in-person neuropsychological testing followed by testing with the audio-recorded cognitive screen (ARCS).Results: ARCS provided better discrimination between normal and impaired elderly individuals than either the Mini-Mental State Examination or the clock drawing test. The in-person battery and ARCS analogous variables were significantly correlated, most in the 0.4 to 0.7 range, including verbal memory, executive function/attention, naming, and verbal fluency. The area under the curve generated from the receiver operating characteristic curves indicated high and equivalent discrimination for ARCS and the in-person battery (0.972 vs. 0.988; p = 0.23).Conclusion: The ARCS demonstrated better discrimination between normal controls and those with mild deficits than typical screening measures. Performance on cognitive domains within the ARCS was well correlated with the in-person battery. Completion of the ARCS was accomplished despite mild difficulty hearing the instructions even in very elderly participants, indicating that it may be a useful measure in primary care settings.

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