Screening For Cognitive Impairment Research Articles

Bipolar-ADHD comorbidity: screening for differences in neurocognition and virtual reality-based cognitive performance

Objectives Identification of comorbid attention-deficit/hyperactivity disorder (ADHD) in patients with bipolar disorder (BD) is complicated by overlapping cognitive symptoms and methodological challenges. This cross-sectional study investigated whether virtual reality (VR)-based cognitive assessment that mimics daily life cognitive challenges can aid in the detection of sustained attention impairment in BD individuals with comorbid ADHD (BD + ADHD). Methods Forty-nine fully or partially remitted outpatients with BD, of whom 14 (24%) had BD + ADHD, were assessed with the Cognition Assessment in Virtual Reality (CAVIR) test, including a sustained attention test that involves distractions, and the Screen for Cognitive Impairment in Psychiatry (SCIP). Patients were also rated for mood symptoms and functioning and completed questionnaires assessing subjective cognition and quality of life. Patients’ cognitive impairment on the SCIP was estimated with reference to n = 100 demographically comparable healthy control participants. Results BD + ADHD participants exhibited more pronounced performance deficits on the CAVIR sustained attention test (t(48) = 2.15, p = .037, d = .66). Notably, deficits on this test were proportional to self-reported daily life concentration difficulties in BD + ADHD individuals. Exploratory analyses revealed that BD + ADHD participants also displayed greater impairment on the SCIP working memory- and delayed verbal learning subtests and greater subjective cognitive complaints than BD patients without this comorbidity (p-levels < .001), but only the difference in subjective cognition survived correction for multiple comparisons (F(1,47) = 14.13, p = .005, np2 = 0.24). Conclusion Screening for deficits in sustained attention with an ecologically valid VR test involving distracting stimuli may be useful for identifying BD + ADHD individuals.

Gesture imitation performance in community-dwelling older people: assessment of a gesture imitation task in the screening and diagnosis of mild cognitive impairment and dementia.

Gesture imitation, a simple tool for assessing visuospatial/visuoconstructive functions, is reportedly useful for screening and diagnosing dementia. However, gesture imitation performance in healthy older adults is largely unknown, as are the factors associated with lower performance. To address these unknowns, we examined the gesture imitation performance of a large number of community-dwelling older adults aged ≥65 years in Arao City, Kumamoto Prefecture (southern Japan). The examiner presented the participants with eight gesture patterns and considered it a success if they could imitate them within 10 s. The success rate of each gesture imitation was calculated for three diagnostic groups: cognitively normal (CN) (n = 1184), mild cognitive impairment (MCI) (n = 237), and dementia (n = 47). Next, we reorganised the original gesture imitation battery by combining six selected gestures with the following scoring method: if the participants successfully imitated the gestures, immediately or within 5 s, two points were assigned. If they succeeded within 5-10 s, one point was assigned. The sensitivity and specificity of the battery were investigated to detect the dementia and MCI groups. Factors associated with gesture imitation battery scores were examined. Except one complex gesture, the success rate of imitation in the CN group was high, approximately 90%. The sensitivity and specificity of the gesture imitation battery for discriminating between the dementia and CN groups and between the MCI and CN groups were 70%/88%, and 45%/75%, respectively. Ageing, male sex, and a diagnosis of dementia or MCI were associated with lower scores on the gesture imitation battery. Gesture imitation tasks alone may not be sufficient to detect MCI. However, by combining gestures with set time limits, gesture imitation tasks can be a low-burden and effective method for detecting dementia, even in community medicine, such as during health check-ups.

Investigating the relevance of the advanced activities of daily living tool for the screening and diagnosis of mild cognitive impairment and dementia to the Sub-Saharan African migrant population in Belgium: A qualitative focus group study

Introduction: Early diagnosis of dementia is partly based on the evaluation of the basic (b-), instrumental (i-) and advanced (a-) activities of daily living (ADL). Adapting the item content of assessment tools to maintain relevance, understanding, and equivalence of the items and scales across other groups is pertinent. However, there are limited assessment tools developed on or adapted for use on the growing older Sub-Saharan African (SSA) migrant population in Europe. Focusing on the item content, we evaluated the relevance of the advanced activities of daily living (a-ADL) tool to the older SSA migrant population in Belgium. Method: Two focus group discussions were organized with participants from the SSA community in Gent, Belgium. Relevant, irrelevant, unclear, and new items were identified. The data was analyzed through the inductive method while consensus agreements were used to arrive at refined themes. Results: Out of the 49 items on the tool, both groups unanimously agreed that 15 items were relevant and 23 irrelevant. Thirteen new items were identified, whereas 15 items were considered unclear. Conclusion: Participants agreed the tool was relevant but should be adapted. Verification and validation of these results in a larger SSA older migrant population in Belgium is strongly recommended.

Cross-Cultural Adaptation of Gujarati Version of Rowland Universal Dementia Assessment Scale for Assessing Cognition in Elderly Population

Background: The Rowland Universal Dementia Assessment Scale (RUDAS) has less educational bias when compared to other cognitive assessment scales like MMSE and MoCA. But its performance has not been adequately addressed in Indian population. Moreover, there are very less scales for cognition which are available in Guajarati language which can be taken in elderly population. Therefore, the reliability and validity of Gujarati-RUDAS in elderly population needs to be tested. Purpose: To determine the reliability and validity of the translated Gujarati version of Rowland Universal Dementia Assessment Scale (RUDAS) for assessing cognition in elderly population. Methodology: A total of 60 subjects were included in this study according to the inclusion criteria. After gaining cross-cultural adaptations, reliability was assessed with intra-rater and inter-rater reliability, analyzed by intraclass correlation coefficient (ICC). Validity was assessed with content validity, analyzed by content validity index (CVI), Result: Intra-rater reliability was having good reliability with ICC value of 0.757 and inter-rater reliability was found to be moderately reliable with ICC value of 0.700. Content validity was found to be good with CVI of 1. Conclusion: The Gujarati version of RUDAS (G-RUDAS) is a reliable and valid tool for the screening of cognitive impairment among elderly population. Keywords: Cognition, Validation, Rowland Universal Dementia Assessment Scale (RUDAS), Gujarati version, Geriatrics, Psychometric properties, cross-cultural adaptation.

Deep Learning Models for the Screening of Cognitive Impairment Using Multimodal Fundus Images

ObjectiveWe aimed to develop a deep learning system capable of identifying subjects with cognitive impairment quickly and easily based on multimodal ocular images. DesignCross-sectional study SubjectsParticipants of Beijing Eye Study 2011 and patients attending Beijing Tongren Eye Center and Beijing Tongren Hospital Physical Examination Center. MethodsWe trained and validated a deep learning algorithm to assess cognitive impairment using retrospectively collected data from the Beijing Eye Study 2011. Cognitive impairment was defined as a Mini–Mental State Examination (MMSE) score <24. Based on fundus photographs and optical coherence tomography (OCT) images, we developed five models based on the following sets of images: macula-centered fundus photographs, optic disc-centered fundus photographs, fundus photographs of both fields, optical coherence tomography (OCT) images, and fundus photographs of both fields with OCT (multi-modal). The performance of the models was evaluated and compared in an external validation dataset, which was collected from patients attending Beijing Tongren Eye Center and Beijing Tongren Hospital Physical Examination Center. Main Outcome MeasuresArea under the curve (AUC). ResultsA total of 9,424 retinal photographs and 4,712 OCT images were used to develop the model. The external validation sets from each center included 1,180 fundus photographs and 590 OCT images. Model comparison revealed that the multi-modal performed best, achieving an AUC of 0.820 in the internal validation set, 0.786 in external validation set 1 and 0.784 in external validation set 2. We evaluated the performance of the multi-model in different sexes and different age groups; there were no significant differences. The heatmap analysis showed that signals around the optic disc in fundus photographs and the retina and choroid around the macular and optic disc regions in OCT images were used by the multi-modal to identify participants with cognitive impairment. ConclusionsFundus photographs and OCT can provide valuable information on cognitive function. Multi-modal models provide richer information compared to single-mode models. Deep learning algorithms based on multimodal retinal images may be capable of screening cognitive impairment. This technique has potential value for broader implementation in community-based screening or clinic settings.

Linear brain measurement: a new screening method for cognitive impairment in elderly patients with cerebral small vessel disease.

The old adults have high incidence of cognitive impairment, especially in patients with cerebral small vessel disease (CSVD). Cognitive impairment is not easy to be detected in such populations. We aimed to develop clinical prediction models for different degrees of cognitive impairments in elderly CSVD patients based on conventional imaging and clinical data to determine the better indicators for assessing cognitive function in the CSVD elderly. 210 CSVD patients were screened out by the evaluation of Magnetic Resonance Imaging (MRI). Then, participants were divided into the following three groups according to the cognitive assessment results: control, mild cognitive impairment (MCI), and dementia groups. Clinical data were collected from all patients, including demographic data, biochemical indicators, carotid ultrasound, transcranial Doppler (TCD) indicators, and linear measurement parameters based on MRI. Our results showed that the brain atrophy and vascular lesions developed progressive worsening with increased degree of cognitive impairment. Crouse score and Interuncal distance/Bitemporal distance (IUD/BTD) were independent risk factors for MCI in CSVD patients, and independent risk factors for dementia in CSVD were Crouse Score, the pulsatility index of the middle cerebral artery (MCAPI), IUD/BTD, and Sylvian fissure ratio (SFR). Overall, the parameters with high performance were the IUD/BTD (OR 2.28; 95% CI 1.26-4.10) and SFR (OR 3.28; 95% CI 1.54-6.91), and the AUC (area under the curve) in distinguishing between CSVD older adults with MCI and with dementia was 0.675 and 0.724, respectively. Linear brain measurement parameters had larger observed effect than other indexes to identify cognitive impairments in CSVD patients. This study shows that IUD/BTD and SFR are good predictors of cognitive impairments in CSVD elderly. Linear brain measurement showed a good predictive power for identifying MCI and dementia in elderly subjects with CSVD. Linear brain measurement could be a more suitable and novel method for screening cognitive impairment in aged CSVD patients in primary healthcare facilities, and worth further promotion among the rural population.

Differences in clinical presentation between newly diagnosed bipolar I and II disorders: A naturalistic study

AimThis naturalistic clinical study aims to investigate differences between newly diagnosed patients with bipolar type I (BDI) and bipolar type II (BDII) disorders in socio-demographic and clinical characteristics, affective symptoms, cognition, functioning and comorbidity with personality disorders. MethodsThe BD diagnosis and type were confirmed using the Schedules for Clinical Assessment in Neuropsychiatry. Affective symptoms were assessed with the Young Mania Rating Scale, the Hamilton Depression Rating Scale, the Major Depressive Index, and the Altman Self-Rating Mania Scale. Functional impairment was assessed with the Functional Assessment Short Test. Cognitive impairment was evaluated by the Screen for Cognitive Impairment in Psychiatry and the Cognitive Complaints in Bipolar Disorder Rating Assessment. Finally, comorbid personality disorders were assessed with the Standardized Assessment of Personality-Abbreviated Scale and structured interview Structured Clinical Interview for DSM-disorders. Results383 newly diagnosed patients were included (BDI: n = 125; BDII: n = 258). Against expectations, we found no more depressive symptoms in BDII compared with BDI nor any differences in cognitive, childhood trauma or overall functional impairment. The only difference was lower occupational impairment in the BDII group. LimitationsThe self-reported measures of cognitive difficulties and childhood trauma involved potential bias (recall or other). Despite BD being newly diagnosed a diagnostic delay was observed. ConclusionPatients newly diagnosed with BDII and BDI had similar burdens of depressive symptoms and cognitive and overall functional impairment, however patients with BDI had lower occupational functioning. No statistically significant difference was found in prevalence of comorbid personality disorders between patients with BDI and BDII.

The plasma derived exosomal miRNA-483-5p/502-5p serve as potential MCI biomarkers in aging

Alzheimer's disease (AD) is the leading cause of dementia and is rapidly becoming one of the most costly, fatal diseases, which is typically discovered in the late stage of molecular pathology, at which point medication intervention is irreversible. As a result, there is an urgent need for a low-cost, least-invasive way of screening cognitive impairment, with the goal of identifying persons at risk of AD. Mild cognitive impairment (MCI) has been described as a transitional state between normal cognitive aging and AD. Early detection and timely tracking of MCI can to some extent prevent the progression towards AD. We found a population in Northwestern China has a comparatively high prevalence of MCI. Continued education, consistent exercise, and a secure financial situation can all help older people maintain cognitive function. Due to the critical role of circulating microRNAs in intercellular signaling and the perturbations thereof, their investigation has assumed paramount significance in elucidating various pathological conditions. Numerous investigations have substantiated the significance of circulating miRNAs specifically in MCI. Here, we evaluated miR-483-5p (Area Under the Curve (AUC) is 0.901, sensitivity 79.2 % and specificity 100 %) and miR-502-5p (AUC is 0.872, sensitivity 79.2 % and specificity 83.3 %), which were derived from plasma exosomes and maintained at high levels in elderly people with MCI, could be employed as promising noninvasive biomarkers.

Robotic assessment of sensorimotor and cognitive deficits in patients with temporal lobe epilepsy

ObjectiveIndividuals with temporal lobe epilepsy (TLE) frequently demonstrate impairments in executive function, working memory, and/or declarative memory. It is recommended that screening for cognitive impairment is undertaken in all people newly diagnosed with epilepsy. However, standard neuropsychological assessments are a limited resource and thus not available to all. Our study investigated the use of robotic technology (the Kinarm robot) for cognitive screening. Methods27 participants with TLE (17 left) underwent both a brief neuropsychological screening and a robotic (Kinarm) assessment. The degree of impairments and correlations between standardized scores from both approaches to assessments were analysed across different neurocognitive domains. Performance was compared between people with left and right TLE to look for laterality effects. Finally, the association between the duration of epilepsy and performance was assessed. ResultsAcross the 6 neurocognitive domains (attention, executive function, language, memory, motor and visuospatial) assessed by our neuropsychological screening, all showed scores that significantly correlated with Kinarm tasks assessing the same cognitive domains except language and memory that were not adequately assessed with Kinarm. Participants with right TLE performed worse on most tasks than those with left TLE, including both visuospatial (typically considered right hemisphere), and verbal memory and language tasks (typically considered left hemisphere). No correlations were found between the duration of epilepsy and either the neuropsychological screening or Kinarm assessment. SignificanceOur findings suggest that Kinarm may be a useful tool in screening for neurocognitive impairment in people with TLE. Further development may facilitate an easier and more rapid screening of cognition in people with epilepsy and distinguishing patterns of cognitive impairment.

The Reliability and Clinical Validation of Automatically-Derived Verbal Memory Features of the Verbal Learning Test in Early Diagnostics of Cognitive Impairment.

Previous research has shown that verbal memory accurately measures cognitive decline in the early phases of neurocognitive impairment. Automatic speech recognition from the verbal learning task (VLT) can potentially be used to differentiate between people with and without cognitive impairment. Investigate whether automatic speech recognition (ASR) of the VLT is reliable and able to differentiate between subjective cognitive decline (SCD) and mild cognitive impairment (MCI). The VLT was recorded and processed via a mobile application. Following, verbal memory features were automatically extracted. The diagnostic performance of the automatically derived features was investigated by training machine learning classifiers to distinguish between participants with SCD versus MCI/dementia. The ICC for inter-rater reliability between the clinical and automatically derived features was 0.87 for the total immediate recall and 0.94 for the delayed recall. The full model including the total immediate recall, delayed recall, recognition count, and the novel verbal memory features had an AUC of 0.79 for distinguishing between participants with SCD versus MCI/dementia. The ten best differentiating VLT features correlated low to moderate with other cognitive tests such as logical memory tasks, semantic verbal fluency, and executive functioning. The VLT with automatically derived verbal memory features showed in general high agreement with the clinical scoring and distinguished well between SCD and MCI/dementia participants. This might be of added value in screening for cognitive impairment.

Is it time for Heart-Brain clinics? A clinical survey and proposition to improve current care for cognitive problems in heart failure.

Cognitive impairment is highly prevalent among patients with heart failure (HF). International guidelines on the management of HF recommend screening for cognitive impairment and tailored care for patients with cognitive impairment. However, practical guidance is lacking. In this study, we explore cardiologists'perspective on screening and care for cognitive impairment in patients with HF. We give an example of a multidisciplinary Heart-Brain care pathway that facilitates screening for cognitive impairment in patients with HF. We distributed an online survey to cardiologists from the Dutch working groups on Geriatric Cardiology and Heart Failure. It covered questions about current clinical practice, impact of cognitive impairment on clinical decision-making, and their knowledge and skills to recognize cognitive impairment. Thirty-six out of 55 invited cardiologists responded. Only 3% performed structured cognitive screening, while 83% stated that not enough attention is paid to cognitive impairment. More than half of the cardiologists desired more training in recognizing cognitive impairment and three-quarters indicated that knowing about cognitive impairment would change their treatment plan. Eighty percent agreed that systematic cognitive screening would benefit their patients and 74% wished to implement a Heart-Brain clinic. Time and expertise were addressed as the major barriers to screening for cognitive impairment. Although cardiologists are aware of the clinical relevance of screening for cognitive impairment in cardiology patients, such clinical conduct is not yet commonly practiced due to lack of time and expertise. The Heart-Brain care pathway could facilitate this screening, thus improving personalized care in cardiology.

Exploring cognitive characteristics and impairments in bipolar disorder: Insights from the BiDiLoS-Ng pilot study

Abstract Bipolar disorder (BD) is a leading cause of disability and is linked to cognitive and functional impairment, increased mortality from cardiometabolic disorders and bipolar disorder suicide. Few studies in sub-Saharan Africa have explored cognitive dysfunction in bipolar disorder. Our study explores the cognitive characteristics in a bipolar patient cohort in Nigeria and assesses its association with clinical and demographic variables. 40 participants from the Bipolar Disorder Longitudinal Study, at baseline, were included in the pilot study of the BiDiLos-Ng. Using a cross-sectional design, cognitive function was assessed using the Screen for Cognitive Impairment in Psychiatry. Multiple linear regression models were used to explore associations between dependent and independent variables. Cognitive impairment was present in 41% of the bipolar cohort, it was not associated with the frequency of mood episodes, and higher educational level was associated with higher verbal fluency test scores (p = 0.02). Being in employment (p = 0.03), younger age (p = 0.00), and lower YMRS score (p = 0.006) were associated with higher working memory test scores. The presence of mania symptoms during the euthymic phase of BD was associated with cognitive impairment. Executive function and working memory were linked to better academic and occupational attainment.

Construction and Validation of a Risk Prediction Model for Mild Cognitive Impairment in Non-Dialysis Chronic Kidney Disease Patient.

The aims of this study are to explore the factors affecting mild cognitive impairment in patients with chronic kidney disease (CKD) who are not undergoing dialysis and to construct and validate a nomogram risk prediction model. Using a convenience sampling method, 383 non-dialysis CKD patients from two tertiary hospitals in Chengdu were selected between February 2023 and August 2023 to form the modeling group. The patients were divided into a mild cognitive impairment group (n = 192) and a non-mild cognitive impairment group (n = 191), and factors such as demographics, disease data, and sleep disorders were compared between the two groups. Univariate and multivariate binary logistic regression analyses were used to identify independent influencing factors, followed by collinearity testing, and construction of the regression model. The final risk prediction model was presented through a nomogram and an online calculator, with internal validation using Bootstrap sampling. For external validation, 137 non-dialysis CKD patients from another tertiary hospital in Chengdu were selected between October 2023 and December 2023. In the modeling group, 192 (50.1%) of the non-dialysis CKD patients developed mild cognitive impairment, and in the validation group, 56 (40.9%) patients developed mild cognitive impairment, totaling 248 (47.7%) of all sampled non-dialysis CKD patients. Age, educational level, Occupation status, Use of smartphone, sleep disorders, hemoglobin, and platelet count were independent factors influencing the occurrence of mild cognitive impairment in non-dialysis CKD patients (all p &lt; 0.05). The model evaluation showed an area under the ROC curve of 0.928, 95% CI (0.902, 0.953) in the modeling group, and 0.897, 95% CI (0.844, 0.950) in the validation group. The model's Youden index was 0.707, with an optimal cutoff value of 0.494, sensitivity of 0.853, and specificity of 0.854, indicating good predictive performance; calibration curves, Hosmer-Lemeshow test, and clinical decision curves indicated good calibration and clinical benefit. Internal validation results showed a consistency index (C-index) of 0.928, 95% CI (0.902, 0.953). The risk prediction model developed in this study shows excellent performance, demonstrating significant predictive potential for early screening of mild cognitive impairment in non-dialysis CKD patients. The application of this model will provide a reference for healthcare professionals, helping them formulate more targeted intervention strategies to optimize patient treatment and management outcomes.

A Comparison of Item Characteristics and Test Information Between the K-MMSE~2:SV and K-MMSE.

The Korean-Mini Mental State Examination, 2nd edition (K-MMSE~2) was recently released. This study aimed to determine whether the K-MMSE~2: Standard Version (K-MMSE~2:SV) had the same test characteristics as the K-MMSE. A total of 1,514 healthy community-based participants aged 19 to 90 years were administered the K-MMSE~2:SV Blue Form along with the language items from the K-MMSE. The item and test characteristics and test information for the K-MMSE~2:SV and K-MMSE were compared using Item Response Theory analysis. Item discriminations for the K-MMSE~2:SV and K-MMSE were above the moderate range for all items except Recall. Most of the items on the K-MMSE~2:SV and K-MMSE had item category difficulty in the very easy or easy range. The test information curve (TIC) showed that the K-MMSE~2:SV and K-MMSE provide almost the same amount of information (27.86 vs. 28.44), with both tests providing the most information at an ability level of -1.57. The generalizability (G) coefficient for the K-MMSE~2:SV and K-MMSE was 0.99. These results indicate that the K-MMSE~2:SV and K-MMSE are equally optimal tests for screening for mild cognitive impairment and early dementia. Given that the amount of test information provided by the two tests was almost identical, the shapes of the TICs were very similar, and the G coefficient was close to 1, we can conclude that the K-MMSE and K-MMSE~2:SV are equivalent tests.

An Ensemble Learning Algorithm for Cognitive Evaluation by an Immersive Virtual Reality Supermarket.

Early screening for Mild Cognitive Impairment (MCI) is crucial in delaying cognitive deterioration and treating dementia. Conventional neuropsychological tests, commonly used for MCI detection, often lack ecological validity due to their simplistic and quiet testing environments. To address this gap, our study developed an immersive VR supermarket cognitive assessment program (IVRSCAP), simulating daily cognitive activities to enhance the ecological validity of MCI detection. This program involved elderly participants from Chengdu Second People's Hospital and various communities, comprising both MCI patients (N=301) and healthy elderly individuals (N=1027). They engaged in the VR supermarket cognitive test, generating complex datasets including User Behavior Data, Tested Cognitive Dimension Game Data, Trajectory Data, and Regional Data. To analyze this data, we introduced an adaptive ensemble learning method for imbalanced samples. Our study's primary contribution is demonstrating the superior performance of this algorithm in classifying MCI and healthy groups based on their performance in IVRSCAP. Comparative analysis confirmed its efficacy over traditional imbalanced sample processing methods and classic ensemble learning voting algorithms, significantly outperforming in metrics such as recall, F1-score, AUC, and G-mean. Our findings advocate the combined use of IVRSCAP and our algorithm as a technologically advanced, ecologically valid approach for enhancing early MCI detection strategies. This aligns with our broader aim of integrating realistic simulations with advanced computational techniques to improve diagnostic accuracy and treatment efficacy in cognitive health assessments.

Sensitivity of Clock Drawing Test Alone to Screen for Cognitive Impairment in Patients with Parkinson's Disease.

Cognitive impairment is a prevalent non-motor symptom of Parkinson's disease (PD), significantly impacting patient quality of life. The Clock Drawing Test (CDT) evaluates cognitive abilities, including planning, organization, and executive functions such as attention, memory, and visuospatial skills. This study aimed to determine the sensitivity of the CDT in diagnosing cognitive impairment in PD. We reviewed the records of 44 PD patients (16 female, 28 male) diagnosed with dementia (30 patients) or mild cognitive impairment (14 patients) between 2018 and 2022. These patients were compared to 106 visitors to the neurological outpatient clinic, serving as a control group. A separate researcher assessed the patients' CDT scores, maintaining confidentiality of all other patient data except age and education level. Among the 44 PD patients, two with mild cognitive impairment were rated as normal, while all PD dementia cases were identified solely through the CDT. In the healthy control group, 72 out of 106 individuals reported no cognitive complaints, whereas 34 individuals (32.1%) reported cognitive complaints as assessed by a blind investigator. The CDT demonstrated a positive predictive value of 55.3% and a negative predictive value of 97.3%. Sensitivity was calculated at 95.5%, and specificity was 67.9%. The findings suggest that the CDT is sensitive in detecting cognitive impairment in PD patients with cognitive deficits. While the CDT serves as an effective rapid screening tool, high scores indicate the absence of cognitive impairment, but low scores alone are insufficient for a definitive diagnosis of dementia. Comprehensive neurological evaluation and detailed cognitive assessment remain essential for confirming dementia diagnoses.

Associations between cognitive screening performance and motor symptoms in Parkinson's disease:a systematic review and meta-analysis.

Despite a body of research examining relationships between motor symptoms and cognitive dysfunction in PD, no prior study has undertaken a systematic review of the magnitude of the relationship between motor symptoms and cognitive screening performance in PD. This study was a systematic review and meta-analysis of the relationship between cognitive screening performance, as assessed by the Montreal Cognitive Assessment (MoCA), and motor symptoms of PD. After the systematic screening, 20 studies were included, and meta-regressions using mixed-effects models were conducted. Motor symptoms across included studies were relatively mild, but average MoCA scores were at the established cutoff for risk of dementia in PD. The average disease duration was 5 years. Consistent with hypotheses, more severe motor symptoms were associated with lower MoCA scores (r=-0.22 (95%CI -0.29 to -0.16), p<0.001), indicating worse cognitive functioning. The results indicate a significant negative correlation between MoCA performance and motor symptoms of PD. Average MoCA scores captured early disease-stage cognitive impairment when motor symptoms remained relatively mild. Serial screening for cognitive impairment beginning early in the disease course may be of benefit to ensure that cognitive dysfunction is detected as it arises.

Factors influencing olfactory function in an adult general population sample: the CHRIS study.

The sense of smell allows for the assessment of the chemical composition of volatiles in our environment. Different factors are associated with reduced olfactory function, including age, sex, as well as health and lifestyle conditions. However, most studies that aimed at identifying the variables that drive olfactory function in the population suffered from methodological weaknesses in study designs and participant selection, such as the inclusion of convenience sample or only of certain age groups, or recruitment biases. We aimed to overcome these issues by investigating the Cooperative Health Research in South Tyrol (CHRIS) cohort, a population-based cohort, by using a validated odor identification test. Specifically, we hypothesized that a series of medical, demographic and lifestyle variables is associated with odor identification abilities. In addition, our goal was to provide clinicians and researchers with normative values for the Sniffin' Sticks identification set, after exclusion of individuals with impaired nasal patency. We included 6,944 participants without acute nasal obstruction and assessed several biological, social, and medical parameters. A basic model determined that age, sex, years of education, and smoking status together explained roughly 13% of the total variance in the data. We further observed that variables related to medical (positive screening for cognitive impairment and for Parkinson's disease, history of skull fracture, stage 2 hypertension) and lifestyle (alcohol abstinence) conditions had a negative effect on odor identification scores. Finally, we provide clinicians with normative values for both versions of the Sniffin' Sticks odor identification test, i.e. with 16 items and with 12 items.

Effect of Anti-Aging Standard Forest Healing Program With Multiple Visits to a Forest Facility on Cognition in Older Age Patients.

The anti-aging standard forest healing program (ASFHP), which uses forest therapy, was reported to be effective in improving psychological, physical, and cognitive functions. However, there are several challenges to directly visiting the forest. This study aimed to investigate the impact of multi-session ASFHP with forest visit on the mental and physical health of the older people with visits to forest facilities and compared them with those of the same program conducted indoors. Individuals aged over 70 years with concerns about cognitive decline were recruited at dementia relief centers and divided into control and experimental groups. A total of 33 people were administered ASFHP under the supervision of a forest therapy instructor. The control group stayed indoors, while the experimental group visited a forest healing center and repeated the program 20 weeks. The multiple-session ASFHP positively affected cognitive impairment screening test (CIST) total scores (p=0.002), memory (p=0.014), Korean version of the Repeatable Battery for the Assessment of Neuropsychological Status total scores (p<0.001), immediate recall (p=0.001), visuospatial/construction (p<0.001), language (p<0.001), forest healing standard questionnaire total scores (p=0.002), and cognitive function (p=0.019), regardless of location. The forest visits during the ASFHP showed positive effects on orientation (p=0.035), delayed recall (p=0.042), emotional stability (p=0.032), physical activity (p=0.005), and health (p=0.022). The CIST scores of the memory domain were the strongest indicator of the multiple-session ASFHP effects. The 20-week multi-session ASFHP with forest visit showed effects on cognitive improvement and physical and emotional stability compared to indoor education.

Text Dialogue Analysis for Primary Screening of Mild Cognitive Impairment: Development and Validation Study.

Artificial intelligence models tailored to diagnose cognitive impairment have shown excellent results. However, it is unclear whether large linguistic models can rival specialized models by text alone. In this study, we explored the performance of ChatGPT for primary screening of mild cognitive impairment (MCI) and standardized the design steps and components of the prompts. We gathered a total of 174 participants from the DementiaBank screening and classified 70% of them into the training set and 30% of them into the test set. Only text dialogues were kept. Sentences were cleaned using a macro code, followed by a manual check. The prompt consisted of 5 main parts, including character setting, scoring system setting, indicator setting, output setting, and explanatory information setting. Three dimensions of variables from published studies were included: vocabulary (ie, word frequency and word ratio, phrase frequency and phrase ratio, and lexical complexity), syntax and grammar (ie, syntactic complexity and grammatical components), and semantics (ie, semantic density and semantic coherence). We used R 4.3.0. for the analysis of variables and diagnostic indicators. Three additional indicators related to the severity of MCI were incorporated into the final prompt for the model. These indicators were effective in discriminating between MCI and cognitively normal participants: tip-of-the-tongue phenomenon (P<.001), difficulty with complex ideas (P<.001), and memory issues (P<.001). The final GPT-4 model achieved a sensitivity of 0.8636, a specificity of 0.9487, and an area under the curve of 0.9062 on the training set; on the test set, the sensitivity, specificity, and area under the curve reached 0.7727, 0.8333, and 0.8030, respectively. ChatGPT was effective in the primary screening of participants with possible MCI. Improved standardization of prompts by clinicians would also improve the performance of the model. It is important to note that ChatGPT is not a substitute for a clinician making a diagnosis.