Brief cognitive screening instruments for early detection of Alzheimer's disease: a systematic review

Mapping cognitive function screening instruments for patients with heart failure: A scoping review

Background

Patients with heart failure (HF) often experience cognitive impairment, which negatively affects their quality of life. An effective screening tool is essential for nurses and healthcare professionals to assess cognitive function as part of HF management. Although many instruments exist, none are specifically designed for patients with HF.

Objective

This study aimed to map the instruments for screening cognitive function in patients with HF.

Design

A scoping review.

Data Sources

Articles published between 2019 and 2023 were searched in PubMed, ScienceDirect, and Google Scholar, with the last search conducted on 27 January 2024.

Review Methods

The review followed the scoping review framework by Arksey and O'Malley and adhered to PRISMA guidelines for scoping reviews.

Results

Of the 21 articles meeting inclusion criteria, six cognitive function screening instruments were used across various cognitive domains, effectively identifying cognitive impairment in both inpatient and outpatient HF settings. The Montreal Cognitive Assessment (MoCA) was the most frequently used tool, covering a broad range of cognitive domains. MoCA showed high efficacy with a kappa coefficient of 0.82, Cronbach's alpha reliability of 0.75, sensitivity of 90%, and specificity of 87%.

Conclusion

Instruments like MoCA, Mini-Cog, and TICS-m show promise for assessing cognitive function in patients with HF, each with specific strengths and limitations. MoCA is notable for its comprehensive coverage despite being time-consuming and having language barriers. Further research is needed to revalidate and improve the existing instruments. It is crucial for nurses and healthcare professionals to integrate these tools into regular patient management, highlighting the need for continued research in their application.

Why am I overwhelmed by bright lights? The behavioural mechanisms of post-stroke visual hypersensitivity

After stroke, patients can experience visual hypersensitivity, an increase in their sensitivity for visual stimuli as compared to their state prior to the stroke. Candidate behavioural mechanisms for these subjective symptoms are atypical bottom-up sensory processing and impaired selective attention, but empirical evidence is currently lacking. In the current study, we aimed to investigate the relationship between post-stroke visual hypersensitivity and sensory thresholds, sensory processing speed, and selective attention using computational modelling of behavioural data. During a whole/partial report task, participants (51 stroke patients, 76 orthopedic patients, and 77 neurotypical adults) had to correctly identify a single target letter that was presented alone (for 17-100 ms) or along a distractor (for 83ms). Performance on this task was used to estimate the sensory threshold, sensory processing speed, and selective attention abilities of each participant. In the stroke population, both on a group and individual level, there was evidence for impaired selective attention and -to a lesser extent- lower sensory thresholds in patients with post-stroke visual hypersensitivity as compared to neurotypical adults, orthopedic patients, or stroke patients without post-stroke sensory hypersensitivity. These results provide a significant advancement in our comprehension of post-stroke visual hypersensitivity and can serve as a catalyst for further investigations into the underlying mechanisms of sensory hypersensitivity after other types of acquired brain injury as well as post-injury hypersensitivity for other sensory modalities.

Diagnostic accuracy of cognitive screening tools validated for older adults in Iran: a systematic review and meta-analysis

BACKGROUND

This systematic review aims to comprehensively assess the diagnostic accuracy of cognitive screening tools validated for older adults in Iran, providing evidence-based recommendations for clinicians and researchers.

METHODS

A comprehensive search in March 2023 across Web of Science, PubMed, Scopus, ScienceDirect, SID, IranMedex, and IranDoc, enhanced by hand-searching references and Google Scholar, identified cross-sectional studies on cognitive screening in Iranian seniors. We assessed diagnostic accuracy, cognitive domains, and test strengths and weaknesses. A bivariate random-effects meta-analysis provided summary estimates and 95% confidence intervals, illustrated in forest plots.

RESULTS

Our review, derived from an initial screening of 38 articles, focused on 17 studies involving 14 cognitive screening tools and participant counts from 60 to 350, mostly from specialized clinics. The MMSE was the only tool examined in at least three studies, prompting a meta-analysis revealing its sensitivity at 0.89 and specificity at 0.77 for dementia detection, albeit amidst significant heterogeneity (I^2 > 80%). ACE-III demonstrated the highest diagnostic accuracy for MCI and dementia, while MoCA's performance was deemed adequate for MCI and excellent for dementia. High bias risk in studies limits interpretation.

CONCLUSION

This review identifies key cognitive tools for dementia and MCI in Iranian older adults, tailored to educational levels for use in primary and specialized care. It emphasizes the need for further validation to enhance diagnostic precision across diverse settings, within a concise framework prioritizing brevity and accuracy for clinical applicability.

Advancing Perioperative Neurocognitive Health: A Critical Review of Predictive Tools, Diagnostic Methods, and Interventional Strategies

Perioperative neurocognitive disorders (PNDs) affect a large percentage of people who undergo surgeries that need general anesthesia. There is an increased risk of death and a major disruption to postoperative self-care as a result of this. This study compiles all the relevant materials that the authors have found to investigate postnatal depression and its causes, as well as the methods used to determine the probability and severity of PNDs and how to reduce their risk before surgery. Postnatal depression can have many causes, and this text explores some of them. These include a history of alcohol or opiate use, immunological dysregulation, advanced age, educational background, infections, neurocognitive impairment, and pre-existing chronic inflammatory disorders. It also delves into various methods used to gauge the likelihood and severity of postpartum depression. The following assessment tools were covered: the Clock Drawing Test, Domain-Specific Tests, the Mini-Mental State Examination, and the Montreal Cognitive Assessment. In addition to biochemical markers, neuroimaging techniques play an important role in diagnosis. The Frailty Fried assessment, which measures inertia, sluggishness, lack of physical activity, fatigue, and unintentional weight loss, is a key prognostic sign that is highlighted. There is strong evidence that the index, which is derived from these five characteristics, may accurately predict the likelihood of PNDs. Risk mitigation strategies are also covered in this research. Preoperative brain plasticity-based therapies, such as physical exercise and intensive cognitive training, can significantly reduce the incidence and severity of postoperative neurocognitive disorders. A peripheral nerve block, monitoring cerebral oxygen saturation, dexmedetomidine, and a reduction in anesthesia depth are all ways to improve anesthetic procedures. Methods that lower blood pressure should be avoided, the body temperature should be kept down during surgery, or the time without liquids should be lengthened; all of these raise the risk of postoperative nausea and vomiting and make it worse. Potential approaches include a Mediterranean diet, physical activity, cognitive stimulation, smoking cessation, alcohol reduction, avoidance of anticholinergic medications, and non-steroidal anti-inflammatory drug stewardship, although there is no definitive evidence for successful postoperative neurocognitive rehabilitation procedures. More standardized diagnostic criteria, evaluation methods, and PND classification are urgently needed, according to this study. Different cases of PNDs are characterized by different combinations of tests, cutoff values, and methods because there is a broad variety of diagnostic tests used to make the diagnosis. Until now, PNDs and pre-existing neurocognitive disorders have been diagnosed using the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). With an aging population comes an increase in the occurrence and prevalence of PNDs, which calls for a specific way to classify and describe the condition.

Combining Mini-Mental State Examination and Montreal Cognitive Assessment for assessing the clinical efficacy of cholinesterase inhibitors in mild Alzheimer's disease: a pilot study

Current drugs for Alzheimer's Disease (AD), such as cholinesterase inhibitors (ChEIs), exert only symptomatic activity. Different psychometric tools are needed to assess cognitive and non-cognitive dimensions during pharmacological treatment. In this pilot study, we monitored 33 mild-AD patients treated with ChEIs. Specifically, we evaluated the effects of 6 months (Group 1 = 17 patients) and 9 months (Group 2 = 16 patients) of ChEIs administration on cognition with the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Frontal Assessment Battery (FAB), while depressive symptoms were measured with the Hamilton Depression Rating Scale (HDRS). After 6 months (Group 1), a significant decrease in MoCA performance was detected. After 9 months (Group 2), a significant decrease in MMSE, MoCA, and FAB performance was observed. ChEIs did not modify depressive symptoms. Overall, our data suggest MoCA is a potentially useful tool for evaluating the effectiveness of ChEIs.

Reliability and validity of the Montreal Cognitive Assessment's auditory items (MoCA-22)

Objective: To evaluate the latent structure, internal consistency, convergent and discriminant validity, diagnostic accuracy, and criterion validity of the Montreal Cognitive Assessment's auditory items (MoCA-22), which has previously been evaluated in small samples if at all. Methods: 11,284 participants completed the MoCA over 1-2 visits to an Alzheimer Disease Research Center (Mage = 69.2, Meducation = 15.9, 57.6% women, 92.4% non-Hispanic white). MoCA-22 items were probed with alpha, omega, confirmatory factor analysis, and test-retest correlations. Scores were related to measures of neurocognition, daily functioning, behavioral-psychological symptoms (BPS), and vision performance for convergent-discriminant and criterion validity. Dementia stage was used to calculate area under the receiver operating characteristic (AUC-ROC) curves and cutoffs for mild cognitive impairment (MCI) and dementia. Results: A single-factor had good fit (CFI = .961; TLI = .945; RMSEA = .061; SRMR = .031), with good internal consistency (Omega total = .83) and test-retest consistency (ICC = .92 at 2.7 years). The strongest convergent correlations were with general cognition and executive functioning, while discriminant validity was demonstrated with its weakest and negative correlations being with BPS. There was strong classification accuracy in distinguishing MCI from normal cognition (AUC = .79; optimal cutoff point < 18), and mild-to-moderate dementia from MCI (AUC = .85; optimal cutoff point < 13). Furthermore, the MoCA-22 had negligible-to-small differences among those with and without vision limitations. Conclusions: These findings add to the evidence of the MoCA-22's utility and it serves as a useful cognitive screening tool with sound reliability and validity.

The Memory Assessment Scale: A Population-based Cognitive Impairment Screening Instrument

This study re-examined the Memory Assessment Scale (MAS), a brief memory test developed in Hawai'i in 1987, to assess whether it remains a valid and reliable cognitive impairment screening tool in Hawai'i. Patients suspected of having neurocognitive dysfunction were divided into 2 groups (those with and without mild cognitive impairment) based on their results on a battery of neuropsychological tests. No differences in MAS scores were found between patients with and without mild cognitive impairment. Further research with the MAS comparing patients with mild cognitive disorder to healthy controls is indicated to further examine the efficacy of this population-based test.

Validation of a web-based self-administered test for cognitive assessment in a Swedish geriatric setting

Computerized cognitive tests have the potential to cost-effectively detect and monitor cognitive impairments and thereby facilitate treatment for these conditions. However, relatively few of these tests have been validated in a variety of populations. Brain on Track, a self-administered web-based test, has previously been shown to have a good ability to differentiate between healthy individuals and patients with cognitive impairment in Portuguese populations. The objective of this study was to validate the differential ability and evaluate the usability of Brain on Track in a Swedish memory clinic setting. Brain on Track was administered to 30 patients with mild cognitive impairment/mild dementia and 30 healthy controls, all scheduled to perform the test from home after one week and after three months. To evaluate the usability, the patient group was interviewed after completion of the testing phase. Patients scored lower than healthy controls at both the first (median score 42.4 vs 54.1, p<0.001) and the second test (median score 42.3 vs 55.0, p<0.001). The test-retest intra-class correlation was 0.87. A multiple logistic regression model accounting for effects of age, gender and education rendered an ability of Brain on Track to differentiate between the groups with an area under the receiver operation characteristics curve of 0.90 for the first and 0.88 for the second test. In the subjective evaluation, nine patients left positive comments, nine were negative whereas five left mixed comments regarding the test experience. Sixty percent of patients had received help from relatives to log on to the platform. In conclusion, Brain on Track performed well in differentiating healthy controls from patients with cognitive impairment and showed a high test-retest reliability, on par with results from previous studies. However, the substantial proportion of patients needing help to log in could to some extent limit an independent use of the platform.

Predicting the incidence of mild cognitive impairment with a computer-based cognitive assessment tool in community-dwelling older adults: The Otassha study

This study examined the ability of a computer-based cognitive assessment tool (CompBased-CAT) to predict mild cognitive impairment (MCI) in community-dwelling older adults. A two-year longitudinal study was conducted using data from 2016 to 2018 from the Otassha study cohort of community-dwelling older adults. MCI was defined as a Mini-Mental Status Examination (MMSE) score of <27. The CompBased-CAT was used at baseline, with each subtest score converted into a Z-score. Subsequently, the total Z-scores were calculated. Participants were divided into robust and MCI groups, and all variables were compared using the t-test or χ2 test. Receiver operating characteristic (ROC) curves and logistic regression analyses were conducted, with MCI and total Z-scores as dependent and independent variables, respectively. Among the 455 participants (median age, 72 years; range, 65-89 years; 282 women and 173 men), 32 developed MCI after two years. The participants in the MCI group were significantly older. They had lower maximal gait speed, baseline MMSE scores, subtest Z-scores, and total Z-scores than those in the robust group. The area under the ROC curve was 0.79 (95% confidence interval: 0.70-0.87; P <0.01). The sensitivity was 0.76, and the specificity was 0.75. The logistic regression analysis showed an odds ratio of 1.34 (95% confidence interval: 1.18-1.52; P <0.01). This study showed that CompBased-CAT can detect MCI, which is an early stage of dementia. Thus, CompBased-CAT can be used in future community health checkups and events for older adults.

Cognitive Screening for Mild Cognitive Impairment: Clinician Perspectives on Current Practices and Future Directions

 This study surveyed 51 specialist clinicians for their views on existing cognitive screening tests for mild cognitive impairment and their opinions about a hypothetical remote screener driven by artificial intelligence (AI). Responses revealed significant concerns regarding the sensitivity, specificity, and time taken to administer current tests, along with a general willingness to consider adopting telephone-based screening driven by AI. Findings highlight the need to design screeners that address the challenges of recognizing the earliest stages of cognitive decline and that prioritize not only accuracy but also stakeholder input.

Preventing Dementia-A Cross-Sectional Study of Outpatients in a Tertiary Internal Medicine Department

Dementia is a significant health problem worldwide, being the seventh leading cause of death (2,382,000 deaths worldwide in 2016). Recent data suggest there are several modifiable risk factors that, if addressed, can decrease dementia risk. Several national dementia screening programs exist; however, limited-income countries do not have the means to implement such measures. We performed a prospective cross-sectional study in an outpatient department to identify individuals at risk for dementia. Patients with no known cognitive dysfunction seeking a medical consult were screened for dementia risk by means of the cardiovascular risk factors, ageing, and dementia (CAIDE) and modified CAIDE tests. Additionally, we collected demographic and clinical data and assessed each participant for depression, mental state, and ability to perform daily activities. Of the 169 patients enrolled, 63.3% were identified as being in the intermediate-risk or high-risk group, scoring more than seven points on the mCAIDE test. Over 40% of the elderly individuals in the study were assessed as "somewhat depressed" or "depressed" on the geriatric depression scale. Almost 10% of the study population was diagnosed de novo with cognitive dysfunction. In conclusion, using a simple questionnaire such as the mCAIDE in a predefined high-risk population is easy and does not represent a major financial burden. At-risk individuals can subsequently benefit from personalized interventions that are more likely to be successful. Limited-resource countries can implement such screening tools in outpatient clinics.

Structural and Functional Retinal Changes in Patients with Mild Cognitive Impairment with and without Diabetes

Our objective is to analyze retinal changes using optical coherence tomography angiography (OCT-A) in patients with mild cognitive impairment (MCI) to characterize structural and vascular alterations. This cross-sectional study involved 117 eyes: 39 eyes from patients with MCI plus diabetes (DM-MCI), 39 eyes from patients with MCI but no diabetes (MCI); and 39 healthy control eyes (C). All patients underwent a visual acuity measurement, a structural OCT, an OCT-A, and a neuropsychological examination. Our study showed a thinning of retinal nerve fiber layer thickness (RNFL) and a decrease in macular thickness when comparing the MCI-DM group to the C group (p = 0.008 and p = 0.016, respectively). In addition, an increase in arteriolar thickness (p = 0.016), a reduction in superficial capillary plexus density (p = 0.002), and a decrease in ganglion cell thickness (p = 0.027) were found when comparing the MCI-DM group with the MCI group. Diabetes may exacerbate retinal vascular changes when combined with mild cognitive impairment.

Documentation of cognitive impairment screening amongst older hospitalised Australians: a prospective clinical record audit

BACKGROUND

Failure to detect cognitive impairment (CI) in hospitalised older inpatients has serious medical and legal implications, including for the implementation of care planning. This mixed methods study aimed to determine amongst hospital in-patients aged ≥ 65 years: (1) Rates of documentation of screening for CI, including the factors associated with completion of screening; (2) Rates of undocumented CI amongst patients who had not received screening during their admission; (3) Healthcare provider practices and barriers related to CI screening.

METHODS

A mixed methods study incorporating a clinical audit and interviews with healthcare providers was conducted at one Australian public hospital. Patients were eligible for inclusion if they were aged 65 years and older and were admitted to a participating ward for a minimum of 48 h. Patient characteristics, whether CI screening had been documented, were extracted using a template. Patients who had not been screened for CI completed the Montreal Cognitive Assessment (MoCA) to determine cognitive status. Interviews were conducted with healthcare providers to understand practices and barriers to screening for CI.

RESULTS

Of the 165 patients included, 34.5% (n = 57) had screening for CI documented for their current admission. Patients aged > 85 years and those with two or more admissions had greater odds of having CI screening documented. Among patients without CI screening documented, 72% (n = 78) were identified as cognitively impaired. While healthcare providers agreed CI screening was beneficial, they identified lack of time and poor knowledge as barriers to undertaking screening.

CONCLUSIONS

CI is frequently unrecognised in the hospital setting which is a missed opportunity for the provision of appropriate care. Future research should identify feasible and effective strategies to increase implementation of CI screening in hospitals.

A systematic review of predictive accuracy via c-statistic of preoperative frailty tests for extended length of stay, post-operative complications, and mortality

Frailty, as an age-related syndrome of reduced physiological reserve, contributes significantly to post-operative outcomes. With the aging population, frailty poses a significant threat to patients and health systems. Since 2012, preoperative frailty assessment has been recommended, yet its implementation has been inhibited by the vast number of frailty tests and lack of consensus. Since the anesthesiologist is the best placed for perioperative care, an anesthesia-tailored preoperative frailty test must be simple, quick, universally applicable to all surgeries, accurate, and ideally available in an app or online form. This systematic review attempted to rank frailty tests by predictive accuracy using the c-statistic in the outcomes of extended length of stay, 3-month post-operative complications, and 3-month mortality, as well as feasibility outcomes including time to completion, equipment and training requirements, cost, and database compatibility. Presenting findings of all frailty tests as a future reference for anesthesiologists, Clinical Frailty Scale was found to have the best combination of accuracy and feasibility for mortality with speed of completion and phone app availability; Edmonton Frailty Scale had the best accuracy for post-operative complications with opportunity for self-reporting. Finally, extended length of stay had too little data for recommendation of a frailty test. This review also demonstrated the need for changing research emphasis from odds ratios to metrics that measure the accuracy of a test itself, such as the c-statistic.

Deep Learning of Speech Data for Early Detection of Alzheimer's Disease in the Elderly

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia, which makes the lives of patients and their families difficult for various reasons. Therefore, early detection of AD is crucial to alleviating the symptoms through medication and treatment.

OBJECTIVE

Given that AD strongly induces language disorders, this study aims to detect AD rapidly by analyzing the language characteristics.

MATERIALS AND METHODS

The mini-mental state examination for dementia screening (MMSE-DS), which is most commonly used in South Korean public health centers, is used to obtain negative answers based on the questionnaire. Among the acquired voices, significant questionnaires and answers are selected and converted into mel-frequency cepstral coefficient (MFCC)-based spectrogram images. After accumulating the significant answers, validated data augmentation was achieved using the Densenet121 model. Five deep learning models, Inception v3, VGG19, Xception, Resnet50, and Densenet121, were used to train and confirm the results.

RESULTS

Considering the amount of data, the results of the five-fold cross-validation are more significant than those of the hold-out method. Densenet121 exhibits a sensitivity of 0.9550, a specificity of 0.8333, and an accuracy of 0.9000 in a five-fold cross-validation to separate AD patients from the control group.

CONCLUSIONS

The potential for remote health care can be increased by simplifying the AD screening process. Furthermore, by facilitating remote health care, the proposed method can enhance the accessibility of AD screening and increase the rate of early AD detection.

Research on digital tool in cognitive assessment: a bibliometric analysis

Objective

The number of research into new cognitive assessment tools has increased rapidly in recent years, sparking great interest among professionals. However, there is still little literature revealing the current status and future trends of digital technology use in cognitive assessment. The aim of this study was to summarize the development of digital cognitive assessment tools through the bibliometric method.

Methods

We carried out a comprehensive search in the Web of Science Core Collection to identify relevant papers published in English between January 1, 2003, and April 3, 2023. We used the subjects such as "digital," "computer," and "cognitive," and finally 13,244 related publications were collected. Then we conducted the bibliometric analysis by Bibliometrix" R-package, VOSviewer and CiteSpace software, revealing the prominent countries, authors, institutions, and journals.

Results

11,045 articles and 2,199 reviews were included in our analyzes. The number of annual publications in this field was rising rapidly. The results showed that the most productive countries, authors and institutions were primarily located in economically developed regions, especially the North American, European, and Australian countries. Research cooperation tended to occur in these areas as well. The application of digital technology in cognitive assessment appealed to growing attention during the outbreak of the COVID-19 epidemic.

Conclusion

Digital technology uses have had a great impact on cognitive assessment and health care. There have been substantial papers published in these areas in recent years. The findings of the study indicate the great potential of digital technology in cognitive assessment.

Molecular and environmental contributors to neurological complications in sickle cell disease

Sickle cell disease (SCD) is an inherited hemoglobinopathy in which affected hemoglobin polymerizes under hypoxic conditions resulting in red cell distortion and chronic hemolytic anemia. SCD affects millions of people worldwide, primarily in Sub-Saharan Africa and the Indian subcontinent. Due to vaso-occlusion of sickled red cells within the microvasculature, SCD affects virtually every organ system and causes significant morbidity and early mortality. The neurological complications of SCD are particularly devastating and diverse, ranging from overt stroke to covert cerebral injury, including silent cerebral infarctions and blood vessel tortuosity. However, even individuals without evidence of neuroanatomical changes in brain imaging have evidence of cognitive deficits compared to matched healthy controls likely due to chronic cerebral hypoxemia and neuroinflammation. In this review, we first examined the biological contributors to SCD-related neurological complications and then discussed the equally important socioenvironmental contributors. We then discuss the evidence for neuroprotection from the two primary disease-modifying therapies, chronic monthly blood transfusions and hydroxyurea, and end with several experimental therapies designed to specifically target these complications.

Clinical Tests Predicting On-Road Performance in Older Drivers with Cognitive Impairment

Background. The Trail Making Test Part B (Trails B) and Useful Field of View® (UFOV) can predict on-road outcomes in drivers with cognitive impairment (CI); however, studies have not included drivers referred for comprehensive driving evaluations (CDEs), who typically have more severe CI. Purpose. We determined the predictive ability of Trails B and UFOV on pass/fail on-road outcomes in drivers with CI (Montreal Cognitive Assessment <26) referred for CDEs. Method. Retrospective data collection from two driving assessments centers (N  =  100, mean age  =  76.2  ±  8.8 years). Findings. The Trails B (area under the curve [AUC]  =  .70) and UFOV subtests 2 (AUC  =  .73) and 3 (AUC  =  .76) predicted pass/fail outcomes. A cut-point ≥467 ms on UFOV subtest 3 better-predicted pass/fail outcomes with 78.9% sensitivity and 73.5% specificity. In comparison, a cut-point ≥3.58 min on Trails B had lower sensitivity (73.7%) and specificity (61.8%). Implications. The UFOV subtest 3 may be more useful than the Trails B for predicting pass/fail outcomes in drivers with more severe CI referred for CDEs.

The feasibility of a stepping exergame prototype for older adults with major neurocognitive disorder residing in a long-term care facility: a mixed methods pilot study

PURPOSE

To explore the feasibility of an exergame prototype in residential individuals with major neurocognitive disorder (MNCD).

MATERIALS AND METHODS

Participants were randomly assigned to a 12-week stepping exergame training or traditional exercise (active control group). Semi-structured interviews were conducted after six and 12 weeks of exergaming. Qualitative data were thematically analysed using NVivo 12. The Short Physical Performance Battery, one minute sit-to-stand test, Mini-Mental State Examination (MMSE), Neuropsychiatric Inventory, Cornell Scale for Depression in Dementia, and Dementia Quality of Life were assessed at baseline and post intervention using a Quade's ANCOVA.

RESULTS

Seven older adults with MNCD in the exergame and 11 in the active control group completed the study [mean age = 83.2 ± 6.5 years; 94.4% female; SPPB score = 7.3 ± 2.4]. Results indicated that the VITAAL exergame prototype was experienced as enjoyable and beneficial. The post-MMSE score was higher (η2=.02, p = 0.01, F = 8.1) following exergaming versus traditional exercise.

CONCLUSIONS

The findings suggest that the exergame prototype is accepted by individuals with MNCD residing in a long-term care facility when they are able to participate and under the condition that they are extensively guided. The preliminary efficacy results revealed higher post-MMSE scores after exergaming versus traditional exercise. Future trials should confirm or refute these findings.

TRIAL REGISTRATION

The trial was registered in ClinicalTrials.gov (Identifier: NCT04436315)Implications for rehabilitationThe VITAAL exergame prototype is accepted by individuals with MNCD residing in a long-term care facility who are able to participate.Supervision of exergaming by health professionals is essential for successful implementation.The VITAAL exergame prototype might maintain cognitive levels in major neurocognitive disorder longer than walking combined with standardised squatting and stepping exercises.

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

Humans are a vision-dominated species; what we perceive depends on where we look. Therefore, eye movements (EMs) are essential to our interactions with the environment, and experimental findings show EMs are affected in neurodegenerative disorders (ND). This could be a reason for some cognitive and movement disorders in ND. Therefore, we aim to establish whether changes in EM-evoked responses can tell us about the progression of ND, such as Alzheimer's (AD) and Parkinson's diseases (PD), in different stages. In the present review, we have analyzed the results of psychological, neurological, and EM (saccades, antisaccades, pursuit) tests to predict disease progression with machine learning (ML) methods. Thanks to ML algorithms, from the high-dimensional parameter space, we were able to find significant EM changes related to ND symptoms that gave us insights into ND mechanisms. The predictive algorithms described use various approaches, including granular computing, Naive Bayes, Decision Trees/Tables, logistic regression, C-/Linear SVC, KNC, and Random Forest. We demonstrated that EM is a robust biomarker for assessing symptom progression in PD and AD. There are navigation problems in 3D space in both diseases. Consequently, we investigated EM experiments in the virtual space and how they may help find neurodegeneration-related brain changes, e.g., related to place or/and orientation problems. In conclusion, EM parameters with clinical symptoms are powerful precision instruments that, in addition to their potential for predictions of ND progression with the help of ML, could be used to indicate the different preclinical stages of both diseases.

Olfactory function changes and the predictive performance of the Chinese Smell Identification Test in patients with mild cognitive impairment and Alzheimer's disease

Objectives

Olfactory disorder is one of the sensory features that reflects a decline in cognitive function. However, olfactory changes and the discernibility of smell testing in the aging population have yet to be fully elucidated. Therefore, this study aimed to examine the effectiveness of the Chinese Smell Identification Test (CSIT) in distinguishing individuals with cognitive decline from those with normal aging and to determine whether the patients with MCI and AD show changes in their olfactory identification abilities.

Methods

This cross-sectional study included eligible participants aged over 50 years between October 2019 and December 2021. The participants were divided into three groups: individuals with mild cognitive impairment (MCI), individuals with Alzheimer's disease (AD), and cognitively normal controls (NCs). All participants were assessed using neuropsychiatric scales, the Activity of Daily Living scale, and the 16-odor cognitive state test (CSIT) test. The test scores and the severity of olfactory impairment were also recorded for each participant.

Results

In total, 366 eligible participants were recruited, including 188 participants with MCI, 42 patients with AD, and 136 NCs. Patients with MCI achieved a mean CSIT score of 13.06 ± 2.05, while patients with AD achieved a mean score of 11.38 ± 3.25. These scores were significantly lower than those of the NC group (14.6 ± 1.57; P < 0.001). An analysis showed that 19.9% of NCs exhibited mild olfactory impairment, while 52.7% of patients with MCI and 69% of patients with AD exhibited mild to severe olfactory impairment. The CSIT score was positively correlated with the MoCA and MMSE scores. The CIST score and the severity of olfactory impairment were identified as robust indicators for MCI and AD, even after adjusting for age, gender, and level of education. Age and educational level were identified as two important confounding factors that influence cognitive function. However, no significant interactive effects were observed between these confounders and CIST scores in determining the risk of MCI. The area under the ROC curve (AUC) generated from the ROC analysis was 0.738 and 0.813 in distinguishing patients with MCI and patients with AD from NCs based on the CIST scores, respectively. The optimal cutoff for distinguishing MCI from NCs was 13, and for distinguishing AD from NCs was 11. The AUC for distinguishing AD from MCI was 0.62.

Conclusions

The olfactory identification function is frequently affected in patients with MCI and patients with AD. CSIT is a beneficial tool for the early screening of cognitive impairment among elderly patients with cognitive or memory issues.

Newly self-administered two-step tool for screening cognitive function in an ageing Chinese population: an exploratory cross-sectional study

Background

Early screening of cognitive function is critical to dementia treatment and care. However, traditional tests require face-to-face administration and are often limited by implementation costs and biases.

Aims

This study aimed to assess whether the Thoven Cognitive Self-Assessment (TCSA), a novel, innovative two-step touchscreen-based cognition assessment tool, could identify early cognitive impairment due to dementia in older adults.

Methods

The TCSA was administered to 61 healthy controls (HCs), 46 participants with mild cognitive impairment (MCI) and 44 participants diagnosed with dementia recruited from Shanghai. Two outcome measures were generated from the TCSA test: the TCSA_{primary task} score and the TCSA_{secondary task} score.

Results

The total average scores in the control group for the TCSA_{primary task} and TCSA_{secondary task} were significantly higher than those in the MCI and dementia groups (TCSA_{primary task}: HCs vs MCI group vs dementia group, 8.58±1.76 vs 5.40±2.67 vs 2.74±2.11, F=75.40, p<0.001; TCSA_{secondary task}: HCs vs MCI group vs dementia group, 23.02±3.31 vs 17.95±4.93 vs 11.93±5.50, F=76.46, p<0.001). Moreover, receiver operating characteristic analysis showed that a score below 7.5 for the TCSA_{primary task} and a score below 22.5 for the TCSA_{secondary task} were indicators of MCI.

Conclusions

The TCSA appears to be efficacious for the detection of cognitive impairment in older adults. It demonstrates the potential for large-scale cognition screening in community service settings.

A Novel Digital Digit-Symbol Substitution Test Measuring Processing Speed in Adults At Risk for Alzheimer Disease: Validation Study

BACKGROUND

Assessing cognitive constructs affected by Alzheimer disease, such as processing speed (PS), is important to screen for potential disease and allow for early detection. Digital PS assessments have been developed to provide widespread, efficient cognitive testing, but all have been validated only based on the correlation between test scores. Best statistical practices dictate that concurrent validity should be assessed for agreement or equivalence rather than using correlation alone.

OBJECTIVE

This study aimed to assess the concurrent validity of a novel digital PS assessment against a gold-standard measure of PS.

METHODS

Adults aged 45-75 years (n=191) participated in this study. Participants completed the novel digital digit-symbol substitution test (DDSST) and the Repeatable Battery for the Assessment of Neuropsychological Status coding test (RBANS-C). The correlation between the test scores was determined using a Pearson product-moment correlation, and a difference in mean test scores between tests was checked for using a 2-tailed dependent samples t test. Data were analyzed for agreement between the 2 tests using Bland-Altman limits of agreement and equivalency using a two one-sided t tests (TOST) approach.

RESULTS

A significant moderate, positive correlation was found between DDSST and RBANS-C scores (r=.577; P<.001), and no difference in mean scores was detected between the tests (P=.93). Bias was nearly zero (0.04). Scores between the tests were found to display adequate agreement with 90% of score differences falling between -22.66 and 22.75 (90% limits of agreement=-22.91 to 22.99), and the scores were equivalent (P=.049).

CONCLUSIONS

Analyses indicate that the DDSST is a valid digital assessment of PS. The DDSST appears to be a suitable option for widespread, immediate, and efficient PS testing.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04559789; https://clinicaltrials.gov/ct2/show/NCT04559789.

Multi-Disease Validation of the RUDAS for Cognitive Screening in Alzheimer's Disease, Parkinson's Disease, and Multiple Sclerosis

BACKGROUND

The Rowland Universal Dementia Assessment Scale (RUDAS) is a cognitive test with favorable diagnostic properties for detecting dementia and a low influence of education and cultural biases.

OBJECTIVE

We aimed to validate the RUDAS in people with Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS).

METHODS

We enrolled one hundred and fifty participants (60 with AD, 30 with PD, 60 with MS, and 120 healthy controls (HC)). All clinical groups completed a comprehensive neuropsychological battery, RUDAS, and standard cognitive tests of each disorder: MMSE, SCOPA-COG, and Symbol Digit Modalities Test. Intergroup comparisons between clinical groups and HC and ROC curves were estimated. Random Forest algorithms were trained and validated to detect cognitive impairment using RUDAS and rank the most relevant scores.

RESULTS

The RUDAS scores were lower in patients with AD, and patients with PD and MS showed cognitive impairment compared to healthy controls. Effect sizes were generally large. The total score was the most discriminative, followed by the memory score. Correlations with standardized neuropsychological tests were moderate to high. Random Forest algorithms obtained accuracies over 80-90% using the RUDAS for diagnosing AD and cognitive impairment associated with PD and MS.

CONCLUSION

Our results suggest the RUDAS is a valid test candidate for multi-disease cognitive screening tool in AD, PD, and MS.

Should Cognitive Screening Tests Be Corrected for Age and Education? Insights From a Causal Perspective

Cognitive screening tests such as the Mini-Mental State Examination are widely used in clinical routine to predict cognitive impairment. The raw test scores are often corrected for age and education, although documented poorer discrimination performance of corrected scores has challenged this practice. Nonetheless, test correction persists, perhaps due to the seemingly counterintuitive nature of the underlying problem. We used a causal framework to inform the long-standing debate from a more intuitive angle. We illustrate and quantify the consequences of applying the age-education correction of cognitive tests on discrimination performance. In an effort to bridge theory and practical implementation, we computed differences in discrimination performance under plausible causal scenarios using Open Access Series of Imaging Studies (OASIS)-1 data. We show that when age and education are causal risk factors for cognitive impairment and independently also affect the test score, correcting test scores for age and education removes meaningful information, thereby diminishing discrimination performance.

Hierarchical Two-Stage Cost-Sensitive Clinical Decision Support System for Screening Prodromal Alzheimer's Disease and Related Dementias

BACKGROUND

The detection of subtle cognitive impairment in a clinical setting is difficult. Because time is a key factor in small clinics and research sites, the brief cognitive assessments that are relied upon often misclassify patients with very mild impairment as normal.

OBJECTIVE

In this study, we seek to identify a parsimonious screening tool in one stage, followed by additional assessments in an optional second stage if additional specificity is desired, tested using a machine learning algorithm capable of being integrated into a clinical decision support system.

METHODS

The best primary stage incorporated measures of short-term memory, executive and visuospatial functioning, and self-reported memory and daily living questions, with a total time of 5 minutes. The best secondary stage incorporated a measure of neurobiology as well as additional cognitive assessment and brief informant report questionnaires, totaling 30 minutes including delayed recall. Combined performance was evaluated using 25 sets of models, trained on 1,181 ADNI participants and tested on 127 patients from a memory clinic.

RESULTS

The 5-minute primary stage was highly sensitive (96.5%) but lacked specificity (34.1%), with an AUC of 87.5% and diagnostic odds ratio of 14.3. The optional secondary stage increased specificity to 58.6%, resulting in an overall AUC of 89.7% using the best model combination of logistic regression and gradient-boosted machine.

CONCLUSION

The primary stage is brief and effective at screening, with the optional two-stage technique further increasing specificity. The hierarchical two-stage technique exhibited similar accuracy but with reduced costs compared to the more common single-stage paradigm.

Study of cognitive function in patients with severe asymptomatic carotid artery stenosis by a computerized neuropsychological assessment device

Background

Carotid stenosis can lead to stroke and cognitive impairment. Moreover, the cognitive function was assessed mostly by paper and pencil cognitive tests. This study aimed to evaluate the impact of severe asymptomatic carotid artery stenosis (SACAS) on cognitive function by a computerized neuropsychological assessment device (CNAD). The diagnostic value of screening SACAS of the CNAD was analyzed.

Methods

There were 48 patients with ≥70% asymptomatic carotid stenosis and 52 controls without carotid stenosis. Duplex ultrasound defined the degree of stenosis. The differences of cognitive function were analyzed between patients and controls. The relationship of scores of cognitive tests and age were analyzed in the linear regression equation. The diagnostic value of CNAD was evaluated by the receiver operating characteristic (ROC) curve.

Results

Stenosis and control subjects had no statistically significant differences in baseline characteristics. Stenosis patients had worse scores for Stroop color-word test (p = 0.002), one back test (p = 0.013), and identification test (p = 0.006) corresponding to attention and executive ability. The analysis of linear regression equation indicated that cognitive scores of stenosis patients declined faster with age, especially for digit span test, Stroop color-word test, one back test and identification test. In analysis of ROC curve, the Stroop color-word test (p = 0.002), one back test (p = 0.013), and identification test (p = 0.006), and comprehensive index of the three tests (p = 0.001) had the diagnostic value.

Conclusion

The CNAD has evaluation value and screening value for patients with cognitive impairment and SACAS. But it is necessary to update the CNAD and conduct a study with a bigger sample.

The Future of Cognitive Screening in Neurodegenerative Diseases

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.

Radiomics for Alzheimer's Disease: Fundamental Principles and Clinical Applications

Alzheimer's disease is a neurodegenerative disease with a huge impact on people's quality of life, life expectancy, and morbidity. The ongoing prevalence of the disease, in conjunction with an increased financial burden to healthcare services, necessitates the development of new technologies to be employed in this field. Hence, advanced computational methods have been developed to facilitate early and accurate diagnosis of the disease and improve all health outcomes. Artificial intelligence is now deeply involved in the fight against this disease, with many clinical applications in the field of medical imaging. Deep learning approaches have been tested for use in this domain, while radiomics, an emerging quantitative method, are already being evaluated to be used in various medical imaging modalities. This chapter aims to provide an insight into the fundamental principles behind radiomics, discuss the most common techniques alongside their strengths and weaknesses, and suggest ways forward for future research standardization and reproducibility.

Development of a Gastrointestinal-Myoelectrical-Activity-Based Nomogram Model for Predicting the Risk of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is the prodromal stage and an important risk factor of Alzheimer's disease (AD). Interventions at the MCI stage are significant in reducing the occurrence of AD. However, there are still many obstacles to the screening of MCI, resulting in a large number of patients going undetected. Given the strong correlation between gastrointestinal function and neuropsychiatric disorders, the aim of this study is to develop a risk prediction model for MCI based on gastrointestinal myoelectrical activity. The Mini-Mental State Examination and electrogastroenterography were applied to 886 participants in western China. All participants were randomly assigned to the training and validation sets in a ratio of 7:3. In the training set, risk variables were screened using LASSO regression and logistic regression, and risk prediction models were built based on nomogram and decision curve analysis, then validation was performed. Eight predictors were selected in the training set, including four electrogastroenterography parameters (rhythm disturbance, dominant frequency and dominant power ratio of gastric channel after meal, and time difference of intestinal channel after meal). The area under the ROC curve for the prediction model was 0.74 in the training set and 0.75 in the validation set, both of which exhibited great prediction ability. Furthermore, decision curve analysis displayed that the net benefit was more desirable when the risk thresholds ranged from 15% to 35%, indicating that the nomogram was clinically usable. The model based on gastrointestinal myoelectrical activity has great significance in predicting the risk of MCI and is expected to be an alternative to scales assessment.

Validation of a novel computerized cognitive function test for the rapid detection of mild cognitive impairment

BACKGROUND

In the present study, we examined the distinguishing ability of a mild cognitive impairment (MCI) assessment tool for rapid screening using a computer (MARC) for Alzheimer's disease dementia (ADD), MCI, and non-demented controls (NDC) with no cognitive impairment, as well as its validity and reliability, as part of a preliminary trial for the development of the tool.

METHODS

A total of 64 participants (23 in the ADD group, 17 in the MCI group, and 24 in the NDC group) were analyzed. The participants were administered MARC and a pre-existing computerized Alzheimer's dementia screening test (MSP), and 31 participants (14 in the MCI group, 17 in the NDC group) were readministered MARC within 4 months from the first test.

RESULTS

The median (interquartile range) test time for MARC was 401 (350-453) s. Total MARC scores were significantly worse in the MCI and ADD groups than in the NDC group (p < 0.05 and p < 0.01, respectively). In the receiver operating characteristic (ROC) analysis, the area under the ROC curve (AUC) when comparing the NDC and MCI groups was 0.866 (95% CI, 0.759-0.974), when comparing the NDC and AD groups was 0.989 (95% CI, 0.970-1.000), and when comparing the MCI and AD groups was 0.889 (95% CI, 0.790-0.988). Furthermore, there was a significant correlation with the results of the existing test, MSP (r = 0.839, p < 0.001). In addition, the intraclass correlation coefficient (ICC) (1,1) when the first and second MARC scores were compared was 0.740 (95% CI, 0.529-0.865; p < 0.001).

CONCLUSIONS

MARC is considered capable of distinguishing MCI with high accuracy. The tool has good validity and reliability, and it can be administered in a short period of time without the need for a specialist.

Correctness and response time distributions in the MemTrax continuous recognition task: Analysis of strategies and a reverse-exponential model

A critical issue in addressing medical conditions is measurement. Memory measurement is difficult, especially episodic memory, which is disrupted by many conditions. On-line computer testing can precisely measure and assess several memory functions. This study analyzed memory performances from a large group of anonymous, on-line participants using a continuous recognition task (CRT) implemented at https://memtrax.com. These analyses estimated ranges of acceptable performance and average response time (RT). For 344,165 presumed unique individuals completing the CRT a total of 602,272 times, data were stored on a server, including each correct response (HIT), Correct Rejection, and RT to the thousandth of a second. Responses were analyzed, distributions and relationships of these parameters were ascertained, and mean RTs were determined for each participant across the population. From 322,996 valid first tests, analysis of correctness showed that 63% of these tests achieved at least 45 correct (90%), 92% scored at or above 40 correct (80%), and 3% scored 35 correct (70%) or less. The distribution of RTs was skewed with 1% faster than 0.62 s, a median at 0.890 s, and 1% slower than 1.57 s. The RT distribution was best explained by a novel model, the reverse-exponential (RevEx) function. Increased RT speed was most closely associated with increased HIT accuracy. The MemTrax on-line memory test readily provides valid and reliable metrics for assessing individual episodic memory function that could have practical clinical utility for precise assessment of memory dysfunction in many conditions, including improvement or deterioration over time.

Eligibility criteria in NIH-funded clinical trials: Can adults with intellectual disability get in?

BACKGROUND

Although scientific breakthroughs can promote health equity, there is concern that adults with intellectual disability, a health disparities population, may be excluded from clinical trials.

OBJECTIVE

To determine the extent to which adults with intellectual disability are subject to exclusion from National Institutes of Health (NIH)-funded clinical trials.

METHODS

We studied recent NIH-funded Phase 2/3, 3, and 4 clinical trials of United States-based working-age adults (>18 < 55 years of age) listed in ClinicalTrials.gov. We coded eligibility criteria for inclusion, direct exclusion, and indirect exclusion of adults with intellectual disability.

RESULTS

We rarely identified studies that directly include adults with intellectual disability. Most studies (74.6%) had eligibility criteria that directly and/or indirectly exclude adults with intellectual disability. Approximately one-third of studies had direct exclusion criteria based on cognitive impairment or diagnosis of intellectual disability. Nearly 65% of studies indirectly excluded adults with intellectual disability based on factors likely associated with intellectual disability (e.g., functional capacity, inability to read/write, and/or research staff discretion).

CONCLUSIONS

We found less exclusion based on diagnosis of intellectual disability than anticipated. Nonetheless, about three-fourths of studies had eligibility criteria which would likely lead to the direct and/or indirect exclusion of adults with intellectual disability. Our findings suggest substantial cause for concern that adults with intellectual disability experience widespread exclusion from NIH-funded clinical trials-exclusion that may lack appropriate justification and assessment. Consequently, this group is denied equal access to the potential benefits of scientific discovery. We provide recommendations for approaches to include adults with intellectual disability.

Study of Health in Primary Care of the Amazonas Population: Protocol for an Observational Study on Diabetes Management in Brazil

Background

Changes in the profiles of patients have significant impacts on the health care system. Diabetes mellitus type 2 (T2DM) prevention and management should be studied in different contexts.

Objective

The Study of Health in Primary Care for the Amazonas Population (SAPPA) primarily aims to describe T2DM prevention and management actions offered by primary health care settings in Brazil and whether the care delivered is consistent with the chronic care model (CCM). Second, the study aims to examine the impact of T2DM management actions on health and lifestyle, and third, to understand how sociodemographic characteristics, health, and subjective outcomes impact diabetes management.

Methods

As part of this observational study, managers and health professionals complete a questionnaire containing information about T2DM prevention and management actions and CCM dimensions. During in-home visits, patients are asked about their health, lifestyle, sociodemographics, diabetes care, and subjective variables.

Results

A total of 34 managers, 1560 professional health workers, and 955 patients will be recruited. The data collection will be completed in October 2022.

Conclusions

The SAPPA is an observational study that intends to understand the T2DM management process in primary health care, including planning, execution, reach, and impact on patient motivation and adherence.

International Registered Report Identifier (IRRID)

DERR1-10.2196/37572

Cognitive Decline Detection for Alzheimer's Disease Patients Through an Activity of Daily Living (ADL)

There are conventional screening instruments for the detection of cognitive impairment, but they have a reduced ecological validity and the information they present could be biased. This study aimed at evaluating the effectiveness and usefulness of a task based on an activity of daily living (ADL) for the detection of cognitive impairment for an Alzheimer's disease (AD) population. Twenty-four participants were included in the study. The AD group (ADG) included twelve older adults (12 female) with AD (81.75±7.8 years). The Healthy group (HG) included twelve older adults (5 males, 77.7 ± 6.4 years). Both groups received a ADL-based intervention at two time frames separated 3 weeks. Cognitive functions were assessed before the interventions by using the MEC-35. The test-retest method was used to evaluate the reliability of the task, as well as the Intraclass Correlation Coefficient (ICC). The analysis of the test-retest reliability of the scores in the task indicated an excellent clinical relevance for both groups. The hypothesis of equality of the means of the scores in the two applications of the task was accepted for both the ADG and HG, respectively. The task also showed a significant high degree of association with the MEC-35 test (rho = 0.710, p = 0.010) for the ADG. Our results showed that it is possible to use an ADL-based task to assess everyday memory intended for cognitive impairments detection. In the same way, the task could be used to promote cognitive function and prevent dementia.

Perspectives and challenges in patient stratification in Alzheimer’s disease

Background

Patient stratification is the division of a patient population into distinct subgroups based on the presence or absence of particular disease characteristics. As patient stratification can be used to account for the underlying pathology of a disease, it can help physicians to tailor therapeutic interventions to individuals and optimize their care management and treatment regime. Alzheimer’s disease, the most common form of dementia, is a heterogeneous disease and its management benefits from patient stratification in clinical trials, and the development of personalized care and treatment strategies for people living with the disease.

Main body

In this review, we discuss the importance of the stratification of people living with Alzheimer’s disease, the challenges associated with early diagnosis and patient stratification, and the evolution of patient stratification once disease-modifying therapies become widely available.

Conclusion

Patient stratification plays an important role in drug development in clinical trials and may play an even larger role in clinical practice. A timely diagnosis and stratification of people living with Alzheimer’s disease is paramount in determining people who are at risk of progressing from mild cognitive impairment to Alzheimer’s dementia. There are key issues associated with stratifying patients which include the heterogeneity and complex neurobiology behind Alzheimer’s disease, our inadequately prepared healthcare systems, and the cultural perceptions of Alzheimer’s disease. Stratifying people living with Alzheimer’s disease may be the key in establishing precision and personalized medicine in the field, optimizing disease prevention and pharmaceutical treatment to slow or stop cognitive decline, while minimizing adverse effects.

Clinical Staging of Alzheimer's Disease: Concordance of Subjective and Objective Assessments in the Veteran's Affairs Healthcare System

INTRODUCTION

Uncertainty surrounding the accurate assessment of the early-stage Alzheimer's disease (AD) may cause delayed care and inappropriate patient access to new AD therapies.

METHODS

To analyze clinical assessments of patients with AD in the Veteran's Affairs (VA) Healthcare System and evaluate concordance between subjective and objective assessments, we processed clinical notes extracted by text integration utilities between April 1, 2008 and October 14, 2021. Veterans who had mild, moderate, or severe AD with clinical notes documenting both clinician's judgement of AD severity and objective test scores from the Mini-Mental State Examination or the Montreal Cognitive Assessment were included. Using clinician-defined severity cohorts, we determined concordance between the clinician's (subjective) assessments and the test-derived (objective) assessments of AD severity. Concordance was assessed over time and by selected symptoms and comorbidities, as well as healthcare system factors.

RESULTS

A total of 8888 notes were initially extracted; the final analysis sample included 7514 notes corresponding to 4469 unique patients (mean [standard deviation] age of 78 [9] years; 96.5% male; 77.8% White). Subjective and objective assessments were concordant in approximately half (53%) of overall notes. In the mild Alzheimer's cohort, patients were assessed to have more severe disease by objective test scores in 40% of notes. Concordance varied about 21-73%, 47-58%, and 40-64% across symptoms/comorbidities, clinician types, and Veteran's Integrated Service Networks, respectively. The proportion of concordant notes was higher in visits to dementia (61%) instead of non-dementia clinics (53%).

CONCLUSIONS

We found higher concordance between clinician's assessment and test-based assessment of Alzheimer's disease severity in dementia specialty clinics. Discordance is especially high for the subjectively assessed mild AD cohort where objective assessments showed a higher severity level in 40% of notes. These data indicate a critical need for improved understanding of clinical assessments and decision-making to identify appropriate patients for anti-amyloid therapy.

Clinical utility of Phototest via teleneuropsychology in Chilean rural older adults

The COVID-19 pandemic has shown the need for neuropsychological care for older adults with memory complaints in different contexts, including rural areas or areas with difficult access.

Objective

This study aimed to analyze the clinical utility of the Phototest, through telemedicine, to identify mild cognitive impairment in rural older adults with memory complaints, during the COVID-19 pandemic.

Methods

We performed a cross-sectional, case-control, and clinical utility comparison of brief cognitive tests (BCTs). The sample included 111 rural elderly people with mild cognitive impairment (MCI) and 130 healthy controls from the Los Lagos region, Chile. The instruments adopted were modified Mini-Mental State Examination (MMSEm) and adapted version of the Phototest (PT) for Chile.

Results

To identify mild cognitive impairment, using a cutoff score of 27-28 points, the Phototest showed a sensitivity of 96.6% and a specificity of 81.8%; indicators superior to those of the MMSEm.

Conclusions

The Phototest is more accurate than the MMSEm in identifying cognitive alterations in rural older adults with cognitive memory complaints through telemedicine. Therefore, its use in primary care is recommended in order to perform early detection of preclinical cognitive alterations in mild cognitive impairment or neurodegenerative diseases.

Dementia and the aging population: cognitive screening within correctional health

PURPOSE

The purpose of this study was to examine the literature surrounding dementia in the aging correctional population and assess the role of cognitive screening related to dementia detection within corrections. The literature regarding the role of dementia within the justice continuum is scant. Furthermore, correctional health researchers have not reached a consensus on the best age to administer cognitive screening in older persons or prioritizes a screening tool for the early detection of dementia.

DESIGN/METHODOLOGY/APPROACH

A key search term list including dementia screening and was developed to review the literature surrounding dementia and the aging correctional population. PubMed, Criminal Justice Abstracts (Ebsco) and the National Criminal Justice Reference Service were used within the academic search. A gray literature search using these same search terms was conducted reviewing criminal justice federal agencies and organizations for additional information on the dementia experience within correctional settings. Snowballing was used to capture relevant theoretical and empirical knowledge.

FINDINGS

Shortages in aging specialized health-care staffing presents a barrier for the clinical interpretation of Montreal Cognitive Assessment (MoCA) results. Correctional officers are also identified as useful candidates within the administration of cognitive screening with proper training. The MoCA may be the optimal cognitive screening tool for dementia, until an original cognitive screening tool is created specific to the correctional population. An age of 55 years or older may serve as the best cutoff score for classifying incarcerated individuals as older persons, and screening should be prioritized for these individuals. Finally, new specialized programs related to dementia within correctional settings are identified.

RESEARCH LIMITATIONS/IMPLICATIONS

A limitation of this research is the conflicting opinions among researchers regarding the use of general cognitive screening tools within the correctional setting.

ORIGINALITY/VALUE

This research can inform correctional organizational policy and practices regarding the screening of older persons suspected of dementia. Most notably, this research proposes that correctional settings should incorporate the MoCA within initial screening of all individuals 55 years of age or older, enriching the job design of correctional officer's job positions to include cognitive testing, and for correctional settings to provide dementia and age-associated training for correctional officers. Finally, this paper informs future research in the development of a cognitive assessment tool specific to the correctional population.

Screening for Mild Cognitive Impairment in the Preoperative Setting: A Narrative Review

Cognitive impairment predisposes patients to the development of delirium and postoperative cognitive dysfunction. In particular, in older patients, the adverse sequelae of cognitive decline in the perioperative period may contribute to adverse outcomes after surgical procedures. Subtle signs of cognitive impairment are often not previously diagnosed. Therefore, the aim of this review is to describe the available cognitive screeners suitable for preoperative screening and their psychometric properties for identifying mild cognitive impairment, as preoperative workup may improve perioperative care for patients at risk for postoperative cognitive dysfunction. Electronic systematic and snowball searches of PubMed, PsycInfo, ClinicalKey, and ScienceDirect were conducted for the period 2015–2020. Major inclusion criteria for articles included those that discussed a screener that included the cognitive domain ‘memory’, that had a duration time of less than 15 min, and that reported sensitivity and specificity to detect mild cognitive impairment. Studies about informant-based screeners were excluded. We provided an overview of the characteristics of the cognitive screener, such as interrater and test-retest reliability correlations, sensitivity and specificity for mild cognitive impairment and cognitive impairment, and duration of the screener and cutoff points. Of the 4775 identified titles, 3222 were excluded from further analysis because they were published prior to 2015. One thousand four hundred and forty-eight titles did not fulfill the inclusion criteria. All abstracts of 52 studies on 45 screeners were examined of which 10 met the inclusion criteria. For these 10 screeners, a further snowball search was performed to obtain related studies, resulting in 20 articles. Screeners included in this review were the Mini-Cog, MoCA, O3DY, AD8, SAGE, SLUMS, TICS(-M), QMCI, MMSE2, and Mini-ACE. The sensitivity and specificity range to detect MCI in an older population is the highest for the MoCA, with a sensitivity range of 81–93% and a specificity range of 74–89%. The MoCA, with the highest combination of sensitivity and specificity, is a feasible and valid routine screening of pre-surgical cognitive function. This warrants further implementation and validation studies in surgical pathways with a large proportion of older patients.

Automated Early Detection of Alzheimer's Disease by Capturing Impairments in Multiple Cognitive Domains with Multiple Drawing Tasks

BACKGROUND

Automatic analysis of the drawing process using a digital tablet and pen has been applied to successfully detect Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, most studies focused on analyzing individual drawing tasks separately, and the question of how a combination of drawing tasks could improve the detection performance thus remains unexplored.

OBJECTIVE

We aimed to investigate whether analysis of the drawing process in multiple drawing tasks could capture different, complementary aspects of cognitive impairments, with a view toward combining multiple tasks to effectively improve the detection capability.

METHODS

We collected drawing data from 144 community-dwelling older adults (27 AD, 65 MCI, and 52 cognitively normal, or CN) who performed five drawing tasks. We then extracted motion- and pause-related drawing features for each task and investigated the statistical associations of the features with the participants' diagnostic statuses and cognitive measures.

RESULTS

The drawing features showed gradual changes from CN to MCI and then to AD, and the changes in the features for each task were statistically associated with cognitive impairments in different domains. For classification into the three diagnostic categories, a machine learning model using the features from all five tasks achieved a classification accuracy of 75.2%, an improvement by 7.8% over that of the best single-task model.

CONCLUSION

Our results demonstrate that a common set of drawing features from multiple drawing tasks can capture different, complementary aspects of cognitive impairments, which may lead to a scalable way to improve the automated detection of AD and MCI.

Verbal fluency response times predict incident cognitive impairment

Introduction

In recent decades, researchers have defined novel methods for scoring verbal fluency tasks. In this work, we evaluate novel scores based on speed of word responses.

Methods

We transcribed verbal fluency recordings from 641 cases of incident cognitive impairment (ICI) and matched controls, all participants in a large national epidemiological study. Timing measurements of utterances were used to calculate a speed score for each recording. Traditional raw and speed scores were entered into Cox proportional hazards (CPH) regression models predicting time to ICI.

Results

Concordance of the CPH model with speed scores was 0.599, an improvement of 3.4% over a model with only raw scores and demographics. Scores with significant effects included animals raw and speed scores, and letter F speed score.

Discussion

Novel verbal fluency scores based on response times could enable use of remotely administered fluency tasks for early detection of cognitive decline.

Highlights

 The current work evaluates prognostication with verbal fluency speed scores. These speed scores improve survival models predicting cognitive decline. Cases with progressive decline have some characteristics suggestive of Alzheimer's disease. The subset of acute decliners is probably pathologically heterogeneous.

Automated Analysis of Drawing Process to Estimate Global Cognition in Older Adults: Preliminary International Validation on the US and Japan Data Sets

BACKGROUND

With the aging of populations worldwide, early detection of cognitive impairments has become a research and clinical priority, particularly to enable preventive intervention for dementia. Automated analysis of the drawing process has been studied as a promising means for lightweight, self-administered cognitive assessment. However, this approach has not been sufficiently tested for its applicability across populations.

OBJECTIVE

The aim of this study was to evaluate the applicability of automated analysis of the drawing process for estimating global cognition in community-dwelling older adults across populations in different nations.

METHODS

We collected drawing data with a digital tablet, along with Montreal Cognitive Assessment (MoCA) scores for assessment of global cognition, from 92 community-dwelling older adults in the United States and Japan. We automatically extracted 6 drawing features that characterize the drawing process in terms of the drawing speed, pauses between drawings, pen pressure, and pen inclinations. We then investigated the association between the drawing features and MoCA scores through correlation and machine learning-based regression analyses.

RESULTS

We found that, with low MoCA scores, there tended to be higher variability in the drawing speed, a higher pause:drawing duration ratio, and lower variability in the pen's horizontal inclination in both the US and Japan data sets. A machine learning model that used drawing features to estimate MoCA scores demonstrated its capability to generalize from the US dataset to the Japan dataset (R²=0.35; permutation test, P<.001).

CONCLUSIONS

This study presents initial empirical evidence of the capability of automated analysis of the drawing process as an estimator of global cognition that is applicable across populations. Our results suggest that such automated analysis may enable the development of a practical tool for international use in self-administered, automated cognitive assessment.

Diagnostic Accuracy of the Five-Word Test for Mild Cognitive Impairment Due to Alzheimer's Disease

New diagnostic methods have been developed for the early diagnosis of Alzheimer’s disease (AD) with the primary purpose of intercepting the transition-phase (mild cognitive impairment, MCI) between normal aging and dementia. We aimed to explore whether the five-word test (FWT) and the mini-mental state examination (MMSE) are predictive for the early diagnosis of MCI due to AD (AD-MCI). We computed ROC analyses to evaluate the sensitivity and specificity of MMSE and FWT in predicting abnormal CSF (t-Tau, p-Tau181, Aβ1−42) and amyloid-PET biomarkers. AD-MCI patients showed lower MMSE and FWT scores (all p < 0.001) than non-AD-MCI. The best predictor of amyloid plaques’ presence at amyloid-PET imaging was the encoding sub-score of the FWT (AUC = 0.84). Both FWT and MMSE had low/moderate accuracy for the detection of pathological CSF Aβ42, t-Tau and p-Tau181 values, with higher accuracy for the t-Tau/Aβ1−42 ratio. In conclusion, the FWT, as a single-domain cognitive screening test, seems to be prompt and moderately accurate tool for the identification of an underlying AD neuropathological process in patients with MCI, supporting the importance of associating biomarkers evaluation in the work-up of patients with dementing neurodegenerative disorders.

Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer's Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

BACKGROUND

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer's disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD.

OBJECTIVE

We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test.

METHODS

Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent.

RESULTS

A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260).

CONCLUSION

MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.

Perioperative Neurocognitive Screening Tools for At-Risk Surgical Patients

Purpose of Review

Perioperative neurocognitive disorders are common after surgery and have serious socioeconomic impacts. Despite this, these disorders remain under-recognized and underdiagnosed. To facilitate detection and direct patients toward appropriate preventative interventions, assessment of cognition during the perioperative period is of critical importance. However, there are considerable barriers to the widespread clinical implementation of cognitive assessments, including a lack of consensus regarding the optimal tool for use in specific clinical scenarios.

Recent Findings

We provide an overview of the most widely used and validated cognitive assessment tools, including those that permit telemedicine-enabled patient encounters.

Summary

No single tool is optimal for all contexts. This narrative review can help clinicians to identify the appropriate cognitive screening tool for their needs by describing the advantages and disadvantages of several available tools, thereby enabling the identification of patients at risk of cognitive decline and facilitating optimization of patient-focused perioperative care.

Validation of a Computerized Cognitive Test Battery for Detection of Dementia and Mild Cognitive Impairment (Preprint)

Background

Early detection of dementia is critical for intervention and care planning but remains difficult. Computerized cognitive testing provides an accessible and promising solution to address these current challenges.

Objective

The aim of this study was to evaluate a computerized cognitive testing battery (BrainCheck) for its diagnostic accuracy and ability to distinguish the severity of cognitive impairment.

Methods

A total of 99 participants diagnosed with dementia, mild cognitive impairment (MCI), or normal cognition (NC) completed the BrainCheck battery. Statistical analyses compared participant performances on BrainCheck based on their diagnostic group.

Results

BrainCheck battery performance showed significant differences between the NC, MCI, and dementia groups, achieving 88% or higher sensitivity and specificity (ie, true positive and true negative rates) for separating dementia from NC, and 77% or higher sensitivity and specificity in separating the MCI group from the NC and dementia groups. Three-group classification found true positive rates of 80% or higher for the NC and dementia groups and true positive rates of 64% or higher for the MCI group.

Conclusions

BrainCheck was able to distinguish between diagnoses of dementia, MCI, and NC, providing a potentially reliable tool for early detection of cognitive impairment.