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Background: Rapidly growing healthcare demand associated with global population aging has spurred the development of new digital tools for the assessment of cognitive performance in older adults. Objective: To develop a fully automated Mini-Mental State Examination (MMSE) assessment model and validate the model's rating consistency. Methods: The Automated Assessment Model for MMSE (AAM-MMSE) was an about 10-min computerized cognitive screening tool containing the same questions as the traditional paper-based Chinese MMSE. The validity of the AAM-MMSE was assessed in term of the consistency between the AAM-MMSE rating and physician rating. Results: A total of 427 participants were recruited for this study. The average age of these participants was 60.6 years old (ranging from 19 to 104 years old). According to the intraclass correlation coefficient (ICC), the interrater reliability between physicians and the AAM-MMSE for the full MMSE scale AAM-MMSE was high [ICC (2,1)=0.952; with its 95% CI of (0.883,0.974)]. According to the weighted kappa coefficients results the interrater agreement level for audio-related items showed high, but for items "Reading and obey", "Three-stage command", and "Writing complete sentence" were slight to fair. The AAM-MMSE rating accuracy was 87%. A Bland-Altman plot showed that the bias between the two total scores was 1.48 points with the upper and lower limits of agreement equal to 6.23 points and −3.26 points. Conclusions: Our work offers a promising fully automated MMSE assessment system for cognitive screening with pretty good accuracy. [ABSTRACT FROM AUTHOR]

Background: Literature supports the use of serious games and virtual environments to assess cognitive functions and detect cognitive decline. This promising assessment method, however, has not yet been translated into self-administered screening instruments for pre-clinical dementia.Objective: The aim of this study is to assess the performance of a novel self-administered serious game-based test, namely the Virtual Supermarket Test (VST), in detecting mild cognitive impairment (MCI) in a sample of older adults with subjective memory complaints (SMC), in comparison with two well-established screening instruments, the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE).Methods: Two groups, one of healthy older adults with SMC (N = 48) and one of MCI patients (N = 47) were recruited from day centers for cognitive disorders and administered the VST, the MoCA, the MMSE, and an extended pencil and paper neuropsychological test battery.Results: The VST displayed a correct classification rate (CCR) of 81.91% when differentiating between MCI patients and older adults with SMC, while the MoCA displayed of CCR of 72.04% and the MMSE displayed a CCR of 64.89%.Conclusion: The three instruments assessed in this study displayed significantly different performances in differentiating between healthy older adults with SMC and MCI patients. The VST displayed a good CCR, while the MoCA displayed an average CCR and the MMSE displayed a poor CCR. The VST appears to be a robust tool for detecting MCI in a population of older adults with SMC. [ABSTRACT FROM AUTHOR]

Background: Clock Drawing Test (CDT) is a commonly used screening tool for cognitive disorders, known for its ease of administration and scoring. Despite frequent use by clinicians, CDT is criticized for its poor predictive value in mild cases of impairment. Objective: To evaluate CDT as a screening tool for early stage of cognitive impairment in biomarker-verified Alzheimer's disease (AD) and depressive disorder (DD). Methods: We analyzed CDT of 172 patients with verified AD, 70 patients with DD, in whom neurodegenerative disorder was excluded using cerebrospinal fluid biomarkers, and 58 healthy older adults. CDT was scored using the semi-quantitative (Shulman) and itemized criteria (adapted from Mendez). Results: Logistic regression showed that for both DD and AD patients with high Mini-Mental State Examination (MMSE) scores (27 and above) the significant predicting variable is uneven number spacing. As MMSE deteriorates (24-26 points), an additional error of setting clock hands is predictive of the disease. In the low MMSE condition, CDT showed an acceptable discrimination for AD (AUC itemized 0.740, Shulman 0.741) and DD (AUC itemized 0.827, Shulman 0.739) using both scoring methods. In the high MMSE condition, discrimination rates were acceptable using itemized scoring but poor using Shulman scoring for both AD (AUC itemized 0.707, Shulman 0.677) and DD (AUC itemized 0.755, Shulman 0.667) groups. Conclusion: Ideally, modern diagnostic process should take place before the cognitive performance drops beneath the healthy range. This makes CDT of little use when screening patients with very mild cognitive deficits. [ABSTRACT FROM AUTHOR]

Background: In Kenya, many people are currently living with dementia without a formal diagnosis or support; often attributing symptoms to normal aging or as a consequence of past behaviors. Dementia screening is not commonplace within Kenya. Improving the supply (or opportunity) of dementia screening within the region may promote uptake, thus leading to more people to seek a formal diagnosis and subsequently receive support within the Kenyan healthcare system. Community Healthcare Workers (CHWs) have successfully demonstrated their value in delivering health interventions within Kenya and have strong links within local communities. Objective: To integrate and evaluate a community-level dementia screening program among older adults in rural Kenya. Methods: Through leveraging this resource, we will deliver dementia screening to older adults (≥60 years) within Makueni County, Kenya over a 6-month period. Here, we present a protocol for the process evaluation of a dementia screening program in Kenya — DEM-SKY. The process evaluation seeks to understand the adoption, implementation, continuation, and implementation determinants, using quantitative and qualitative measures. Conclusions: Gaining perspectives of different participants involved in the program (i.e., older adults, CHWs, hospital staff, and trainers), will ensure that we understand the reason for successful (or unsuccessful) delivery of DEM-SKY. [ABSTRACT FROM AUTHOR]

Background: Pre-symptomatic screening methods for detecting a higher risk of Alzheimer's disease (AD) are gaining popularity; thus, more people are seeking these tests. However, to date, not much is known about the attitudes toward pre-symptomatic AD screening. Objective: The goal of this study is to examine the psychometric properties of a tool for assessing the attitudes, barriers, and motivations to pre-symptomatic AD screening. Methods: This is a cross-sectional study performed on 208 Greek participants (189 students and 19 caregivers) provided with an online questionnaire. Psychometric properties were assessed through the examination of its construct validity (principal component analysis) and internal consistency. Results: Exploratory factor analysis revealed the presence of four factors. The first factor is labeled as "Perceived harms of testing" (10 items), the second "Acceptance of testing" (5 items), the third "Perceived benefits of testing" (6 items), and the fourth factor "Need for knowledge" (4 items). The reliability (internal consistency) of each factor separately was acceptable to good (0.70–0.87) while the internal consistency of the overall questionnaire (25 items) was good (Cronbach's α=0.82). Conclusion: PRE-ADS is a valid questionnaire that might help in the research of peoples' attitudes related to the pros and cons of pre-symptomatic screening for AD, and the development of effective counseling programs and prevention strategies. However, future research is required in the target population. [ABSTRACT FROM AUTHOR]

Background: A rapid digital instrument is needed to facilitate community-based screening of mild cognitive impairment (MCI) and Alzheimer's disease (AD) in China. Objective: We developed a voice recognition-based cognitive assessment (Shanghai Cognitive Screening, SCS) on mobile devices and evaluated its diagnostic performance. Methods: Participants (N = 251) including healthy controls (N = 98), subjective cognitive decline (SCD, N = 42), MCI (N = 80), and mild AD (N = 31) were recruited from the memory clinic at Shanghai Sixth People's Hospital. The SCS is fully self-administered, takes about six minutes and measures the function of visual memory, language, and executive function. Participants were instructed to complete SCS tests, gold-standard neuropsychological tests and standardized structural 3T brain MRI. Results: The Cronbach's alpha was 0.910 of the overall scale, indicating high internal consistency. The SCS total score had an AUC of 0.921 to detect AD (sensitivity = 0.903, specificity = 0.945, positive predictive value = 0.700, negative predictive value = 0.986, likelihood ratio = 16.42, number needed for screening utility = 0.639), and an AUC of 0.838 to detect MCI (sensitivity = 0.793, specificity = 0.671, positive predictive value = 0.657, negative predictive value = 0.803, likelihood ratio = 2.41, number needed for screening utility = 0.944). The subtests demonstrated moderate to high correlations with the gold-standard tests from their respective cognitive domains. The SCS total score and its memory scores all correlated positively with relative volumes of the whole hippocampus and almost all subregions, after controlling for age, sex, and education. Conclusion: The SCS has good diagnostic accuracy for detecting MCI and AD dementia and has the potential to facilitate large-scale screening in the general community. [ABSTRACT FROM AUTHOR]

The 1980s saw an upsurge of research in Alzheimer's disease (AD). The necessity of standardized assessment batteries became apparent, leading to the development of standardized instruments, such as the CERAD, the CAMDEX, the CSI 'D', and later the TOOLBOX. The advent of new biological markers has led to speculation in the research community about the necessity for these instruments. As the association of biomarkers with subsequent clinical dementia remains unclear, assessment batteries are still necessary, especially with growing evidence that prodromal symptoms of AD may not be cognitive decline but emotional or behavioral symptoms. Inclusion of ethnic minority groups is also essential. [ABSTRACT FROM AUTHOR]

Cognitive screening instruments (CSI) have variable sensitivity and specificity to the cognitive changes associated with dementia syndromes, and the most recent systematic review found insufficient evidence to support the benefit of cognitive screening tools in older adults residing within the community. Consequently, there is a critical need to improve CSI methods, which have not yet incorporated advances in psychometrics, neuroscience, and technology. The primary goal of this article is to provide a framework for transitioning from legacy CSIs to advanced dementia screening measurement. In line with ongoing efforts in neuropsychology and the call for next-generation digital assessment for early detection of AD, we propose a psychometrically advanced (including application of item response theory methods), automated selective assessment model that provides a framework to help propel an assessment revolution. Further, we present a three-phase model for modernizing CSIs and discuss critical diversity and inclusion issues, current challenges in differentiating normal from pathological aging, and ethical considerations. [ABSTRACT FROM AUTHOR]

In a recent issue of the Journal of Alzheimer's Disease, Zinman et al. investigated the role of sex in the risk of cognitive impairment in 5,969 patients with a stroke or transient ischemic attacks. Using a short validated clinical screening tool, they noted that men had a 34% higher risk of screening positive for post-stroke cognitive impairment after adjusting for age, education, and stroke severity compared to women. This study highlights that more large, prospective, and multicenter studies are needed to evaluate sex-specific changes after a stroke since sex differences exist in many aspects of stroke presentation and management. [ABSTRACT FROM AUTHOR]

Background: The self-administered iPad-based Cleveland Clinic Cognitive Battery (C3B) was designed specifically for the efficient screening of cognitive functioning of older adults in a primary care setting. Objective: 1) Generate regression-based norms from healthy participants to enable demographic corrections to facilitate clinical interpretation; 2) estimate test-retest reliability and practice effects; 3) examine ability to discriminate mild cognitive impairment (MCI) from healthy aging; 4) d etermine validity of screening in a distracting clinical environment; and 5) determine completion rates and patient satisfaction in a primary care setting. Methods: Study 1 (S1) recruited a stratified sample of 428 healthy adults, ages 18–89, to generate regression-based equations. S2 assessed 2-week test-retest reliability and practice effects in 30 healthy elders. S3 recruited 30 MCI patients and 30 demographically-matched healthy controls. In S4, 30 healthy elders self-administered the C3B in a distracting environment and in a quiet private room in counterbalanced order. In a demonstration project, 470 consecutive primary care patients were administered the C3B as part of routine clinical care (S5). Results: C3B performance was primarily influenced by age, education, and race (S1), had acceptably high test-retest reliability and minimal practice effects (S2), discriminated MCI from healthy controls (S3), was not negatively impacted by a distracting clinical environment (S4), had high completion rates (>92%) and positive ratings from primary care patients (S5). Conclusion: The C3B is a computerized cognitive screening tool that is reliable, validated, self-administered, and is conducive to integration into a busy primary care clinical workflow for detecting MCI, early Alzheimer's disease, and other related dementias. [ABSTRACT FROM AUTHOR]

Background: Detecting early-stage Alzheimer's disease (AD) is still problematic in clinical practice. This work aimed to find T1-weighted MRI-based markers for AD and mild cognitive impairment (MCI) to improve the screening process. Objective: Our assumption was to build a screening model that would be accessible and easy to use for physicians in their daily clinical routine. Methods: The multinomial logistic regression was used to detect status: AD, MCI, and normal control (NC) combined with the Bayesian information criterion for model selection. Several T1-weighted MRI-based radiomic features were considered explanatory variables in the prediction model. Results: The best radiomic predictor was the relative brain volume. The proposed method confirmed its quality by achieving a balanced accuracy of 95.18%, AUC of 93.25%, NPV of 97.93%, and PPV of 90.48% for classifying AD versus NC for the European DTI Study on Dementia (EDSD). The comparison of the two models: with the MMSE score only as an independent variable and corrected for the relative brain value and age, shows that the addition of the T1-weighted MRI-based biomarker improves the quality of MCI detection (AUC: 67.04% versus 71.08%) while maintaining quality for AD (AUC: 93.35% versus 93.25%). Additionally, among MCI patients predicted as AD inconsistently with the original diagnosis, 60% from ADNI and 76.47% from EDSD were re-diagnosed as AD within a 48-month follow-up. It shows that our model can detect AD patients a few years earlier than a standard medical diagnosis. Conclusion: The created method is non-invasive, inexpensive, clinically accessible, and efficiently supports AD/MCI screening. [ABSTRACT FROM AUTHOR]

Background: Modern prodromal Alzheimer's disease (AD) clinical trials might extend outreach to a general population, causing high screen-out rates and thereby increasing study time and costs. Thus, screening tools that cost-effectively detect mild cognitive impairment (MCI) at scale are needed. Objective: Develop a screening algorithm that can differentiate between healthy and MCI participants in different clinically relevant populations. Methods: Two screening algorithms based on the remote ki:e speech biomarker for cognition (ki:e SB-C) were designed on a Dutch memory clinic cohort (N = 121) and a Swedish birth cohort (N = 404). MCI classification was each evaluated on the training cohort as well as on the unrelated validation cohort. Results: The algorithms achieved a performance of AUC 0.73 and AUC 0.77 in the respective training cohorts and AUC 0.81 in the unseen validation cohorts. Conclusion: The results indicate that a ki:e SB-C based algorithm robustly detects MCI across different cohorts and languages, which has the potential to make current trials more efficient and improve future primary health care. [ABSTRACT FROM AUTHOR]

Wang et al. analyze Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment accuracy as screening tests for detecting dementia associated with Alzheimer's disease (AD). Such tests are at the center of controversy regarding recognition and treatment of AD. The continued widespread use of tools such as MMSE (1975) underscores the failure of advancing cognitive screening and assessment, which has hampered the development and evaluation of AD treatments. It is time to employ readily available, efficient computerized measures for population/mass screening, clinical assessment of dementia progression, and accurate determination of approaches for prevention and treatment of AD and related conditions. [ABSTRACT FROM AUTHOR]

Background: Cerebral white matter lesions (WML) are related to a higher risk of vascular and Alzheimer's dementia. Moreover, oligomerized amyloid-β (OAβ) can be measured from blood for dementia screening.Objective: We aimed to investigate the relationship of plasma OAβ levels with clinical and radiological variables in a health screening population.Methods: WML, other volumetric parameters of magnetic resonance images, cognitive assessment, and plasma OAβ level were evaluated.Results: Ninety-two participants were analyzed. The majority of participants' clinical dementia rating was 0 or 0.5 (96.7%). White matter hyperintensities (WMH) increased with age, but OAβ levels did not (r2 = 0.19, p < 0.001, r2 = 0.03, p = 0.10, respectively). No volumetric data, including cortical thickness/hippocampal volume, showed any significant correlation with OAβ. Log-WMH volume was positively correlated with OAβ (r = 0.24, p = 0.02), and this association was significant in the periventricular area. White matter signal abnormalities from 3D-T1 images were also correlated with the OAβ in the periventricular area (p = 0.039). Multivariate linear regression showed that log-WMH values were independently associated with OAβ (B = 0.879 (95% confidence interval 0.098 -1.660, p = 0.028)). Higher tertiles of WMH showed higher OAβ levels than lower tertiles showed (p = 0.044). Using a cutoff of 0.78 ng/mL, the high OAβ group had a larger WMH volume, especially in the periventricular area, than the low OAβ group (p = 0.036).Conclusion: Both WML and plasma OAβ levels can be early markers for neurodegeneration in the healthcare population. The lesions, especially in the periventricular area, might be related to amyloid pathogenesis, which strengthens the importance of WML in the predementia stage. [ABSTRACT FROM AUTHOR]

Background: Early diagnosis of Alzheimer's disease (AD) provides an opportunity for early intervention. Cognitive testing has proven to be a reliable way to identify individuals who may be at risk of AD. The Telephone Assessment for Cognitive Screening (TICS) is proficient in screening for cognitive impairment. However, its ability to identify those at risk of developing AD pathology is unknown.Objective: We aim to investigate associations between TICS scores, collected over a period of 13 years, and the cognitive status of participants at death. We also examine relationships between TICS scores and neuropathological indices of AD (CERAD score, Thal phase, and Braak stage).Methods: Between 2004 and 2017, participants from The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age underwent cognitive assessment using TICS. Scores from four time points were available for analysis. Cognitive impairment and AD pathology at death was evaluated in 101 participants.Results: TICS scores at time points 2, 3, and 4 were significantly lower in those cognitively impaired at death compared to those considered cognitively normal. There were significant negative correlations between TICS scores and CERAD score and Braak stage at time points 2 and 4. No correlations between Thal phase and TICS were found.Conclusion: Findings indicate that TICS could be used not only to screen for cognitive impairment, but also to identify individuals at risk of developing AD pathology, many years before any overt symptoms occur. Once identified, 'at risk' individuals could be targeted for early interventions which could attenuate the progression of the disease. [ABSTRACT FROM AUTHOR]

Background: Many issues persist in the today's Alzheimer's disease (AD) screening and the breakthrough method is desired.Objective: We aim to validate the association between venous reflux and AD, and to develop a new method for AD screening.Methods: We examined spontaneous echo contrast, area, diameter, retrograde velocity, and anterograde velocity of the bilateral cervical internal jugular vein (IJV) using carotid ultrasonography.Results: A total of 112 patients participated in this study, with 26 diagnosed as AD. The proportion of both or either IJV spontaneous echo contrast (+) occupied 25 of total 26 AD patients, which showed 96.2%of sensitivity and 98.5%negative predictive value. The IJV velocities also showed significant correlation with AD diagnosis, although the IJV area or diameter did not.Conclusion: Our results indicate that the validation of the spontaneous echo contrast or velocities of the IJV are convenient AD diagnosis screening methods and that the venous reflux disturbance correlates with AD development. [ABSTRACT FROM AUTHOR]

Background: For care planning and support, under-detection and late diagnosis of Alzheimer's disease (AD) is a great challenge. Models of Patient-Engagement for Alzheimer's Disease (MOPEAD) is an EU-funded project aiming at testing different strategies to improve this situation.Objective: To make a cost-consequence analysis of MOPEAD.Methods: Four screening strategies were tested in five countries (Germany, the Netherlands, Slovenia, Spain, and Sweden): 1) a web-approach; 2) Open-House initiative; 3) in primary care; and 4) by diabetes specialists. Persons-at-risk of AD in all strategies were offered referral to a hospital-based specialist. The primary health-economic outcome was the cost per true-positive case (TP) of AD from the screened population.Results: Of 2,847 screened persons, 1,121 screened positive (39%), 402 were evaluated at memory clinics (14%), and 236 got an AD diagnosis (8%). The cost per TP of those screened was €3,115 with the web-approach, €2,722 with the Open-House, €1,530 in primary care, and €1,190 by diabetes specialists. Sensitivity analyses that more likely reflect the real-world situation confirmed the results. The number-needed-to-screen was 30 with the web-approach, 8 with the Open-House and primary care, and 6 with the diabetes specialists.There were country differences in terms of screening rates, referrals to memory clinics, staff-types involved, and costs per TP.Conclusion: In primary care and by the diabetes specialist, the costs per TP/screened population were lowest, but the capacity of such settings to identify cases with AD-risk must be discussed. Hence new diagnostic strategies such as web-solutions and Open-House initiatives may be valuable after modifications. [ABSTRACT FROM AUTHOR]

Background: Widespread dementia detection could increase clinical trial candidates and enable appropriate interventions. Since the Clock Drawing Test (CDT) can be potentially used for diagnosing dementia-related disorders, it can be leveraged to develop a computer-aided screening tool.Objective: To evaluate if a machine learning model that uses images from the CDT can predict mild cognitive impairment or dementia.Methods: Images of an analog clock drawn by 3,263 cognitively intact and 160 impaired subjects were collected during in-person dementia evaluations by the Framingham Heart Study. We processed the CDT images, participant's age, and education level using a deep learning algorithm to predict dementia status.Results: When only the CDT images were used, the deep learning model predicted dementia status with an area under the receiver operating characteristic curve (AUC) of 81.3% ± 4.3%. A composite logistic regression model using age, level of education, and the predictions from the CDT-only model, yielded an average AUC and average F1 score of 91.9% ±1.1% and 94.6% ±0.4%, respectively.Conclusion: Our modeling framework establishes a proof-of-principle that deep learning can be applied on images derived from the CDT to predict dementia status. When fully validated, this approach can offer a cost-effective and easily deployable mechanism for detecting cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: Medical imaging methods such as PET and MRI aid clinical assessment of Alzheimer's disease (AD). Less expensive, less technically demanding, and more widely deployable technologies are needed to expand objective screening for diagnosis, treatment, and research. We previously reported brain tissue near-infrared optical spectroscopy (NIR) in vitro indicating the potential to meet this need.Objective: To determine whether completely non-invasive, clinical, NIR in vivo can distinguish AD patients from age-matched controls and to show the potential of NIR as a clinical screen and monitor of therapeutic efficacy.Methods: NIR spectra were acquired in vivo. Three groups were studied: autopsy-confirmed AD, control and mild cognitive impairment (MCI). A feature selection approach using the first derivative of the intensity normalized spectra was used to discover spectral regions that best distinguished "AD-alone" (i.e., without other significant neuropathology) from controls. The approach was then applied to other autopsy-confirmed AD cases and to clinically diagnosed MCI cases.Results: Two regions about 860 and 895 nm completely separate AD patients from controls and differentiate MCI subjects according to the degree of impairment. The 895 nm feature is more important in separating MCI subjects from controls (ratio-of-weights: 1.3); the 860 nm feature is more important for distinguishing MCI from AD (ratio-of-weights: 8.2).Conclusion: These results form a proof of the concept that near-infrared spectroscopy can detect and classify diseased and normal human brain in vivo. A clinical trial is needed to determine whether the two features can track disease progression and monitor potential therapeutic interventions. [ABSTRACT FROM AUTHOR]

The informant AD8 has excellent discriminant ability for dementia case finding in tertiary healthcare settings. However, its clinical utility for dementia case finding at the forefront of dementia management, primary healthcare, is unknown. Therefore, we recruited participants from two primary healthcare centers in Singapore and measured their performance on the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Clinical Dementia Rating (CDR), and a local formal neuropsychological battery, in addition to the AD8. Logistic regression was conducted to examine the associations between demographic factors and dementia. Area under the receiver operating characteristics (ROC) curve analysis was used to establish the optimal cut-off points for dementia case finding. Of the 309 participants recruited, 243 (78.7%) had CDR = 0, 22 (7.1%) CDR = 0.5, and 44 (14.2%) CDR ≥1. Age was strongly associated with dementia, and the optimal age for dementia case finding in primary healthcare settings was ≥75 years. In this age group, the AD8 has excellent dementia case finding capability and was superior to the MMSE and equivalent to the MoCA [AD8 AUC (95% CI): 0.95 (0.91-0.99), cut-off: ≥3, sensitivity: 0.90, specificity: 0.88, PPV: 0.79 and NPV: 0.94; MMSE AUC (95% CI): 0.87 (0.79-0.94), p = 0.04; MoCA AUC (95% CI): 0.88 (0.82-0.95), p = 0.06]. In conclusion, the AD8 is well suited for dementia case finding in primary healthcare settings. [ABSTRACT FROM AUTHOR]

Many cognitive screening instruments have been developed during the last decades to detect mild cognitive dysfunction and dementia, and there is an ongoing discussion as to which tool should be used in which setting and which challenges have to be considered. Among other aspects, dependence on age is a recognized problem in screening tools which still has not found its way into common scoring procedures. Another aspect which has been handled very heterogeneously is which domain is represented in which proportion in the total score. Furthermore, screening ethnic minority patients has been identified as an important but so far widely unresolved matter. In this review, four cognitive screening tools that all follow a common, stringent concept and pay regard to some critical aspects are described: the DemTect, a 'generic' tool; the PANDA for Parkinson's disease patients; the EASY, a non-verbal, culture-fair screening test for patients with migration background; and the MUSIC for patients with multiple sclerosis. All of these screening instruments have an age-correction, provide a total score in which the different subtests are weighted according to their individual sensitivity and specificity, and include tasks that are specifically aligned to the cognitive profile of the target group, including the EASY with non-verbal, culture-fair tasks to overcome language and cultural barriers. The development, main characteristics, data, and limitations of these tools are presented and discussed against the background of the current landscape of cognitive screening tools. [ABSTRACT FROM AUTHOR]

Mild cognitive impairment (MCI) often presages development of Alzheimer's disease (AD). We recently completed a cross-sectional study to test the hypothesis that a combination of a brief cognitive screening instrument (Mini-Cog) with a functional scale (Functional Activities Questionnaire; FAQ) would accurately identify individuals with MCI and undiagnosed dementia. The Mini-Cog consists of a clock drawing task and 3-item recall, and takes less than 5 minutes to administer. The FAQ is a 30-item questionnaire completed by an informant. In addition to the Mini-Cog and FAQ, a traditional cognitive test battery was administered, and two neurologists and a neuropsychologist determined a consensus diagnosis of Normal, MCI, or Dementia. A classification tree algorithm was used to pick optimal cutpoints, and, using these cutpoints, the combined Mini-Cog and FAQ (MC-FAQ) predicted the consensus diagnosis with an accuracy of 83% and a weighted kappa of 0.81. When the population was divided into Normal and Abnormal, the sensitivity, specificity and positive predictive value were 89%, 90%, and 95%, respectively. The MC-FAQ discriminates individuals with MCI from cognitively normal individuals and those with dementia, and its ease of administration makes it an attractive screening instrument to aid detection of cognitive impairment in the elderly. [ABSTRACT FROM AUTHOR]

Early detection of Alzheimer's disease and related disorders (ADRD) is important, especially in primary care settings. We compared performances of two common screening tests, the Mini-Mental State Exam (MMSE) and Clock Drawing Test (CDT), with that of the MCI Screen ({MCIS}) in 254 patients over 65. None had previous diagnosis of ADRD, and 81% were asymptomatic by Functional Assessment Staging Test ({FAST}) (FAST=1). 215 patients completed all screening tests - 141 had >or= 1 abnormal result, 121/141 completed standardized diagnostic assessment, and the remaining 74/215 (34%) screened entirely normally and weren't further evaluated. Potential bias due to unevaluated cases was statistically adjusted. Among diagnosed cases: AD=43%, cerebrovascular disease=36%, other causes=21%. Bias-adjusted MCI prevalence for FAST stages 1 and 1-3 were 13.9-20.3% and 23.0-28.3%. Bias-adjusted results for the CDT, MMSE and MCIS were: clinical diagnosis validity (kappa statistic)={-0.02 (p=0.61), 0.06 (p=0.23), 0.92 (p< 0.0001)}; sensitivity={59%, 71%, 94%}; specificity={39%, 36%, 97%}; overall accuracy={54%, 62%, 96%}; positive predictive value={16%, 17%, 86%}; and negative predictive value={83%, 87%, 96%}. The MMSE and CDT were not valid for early detection, while the MCIS had high validity and accuracy in the primary care cohort. [ABSTRACT FROM AUTHOR]