The Mini-Cog, Clock Drawing Test, and the Mini-Mental State Examination in a German memory clinic: specificity of separation dementia from depression

A blood-based, metabolite and demographic characteristic markers panel for the diagnosis of Alzheimer's disease

Aims: This work was designed to provide early diagnosis strategies for Alzheimer's disease (AD) based on the identification of blood metabolic biomarkers. Patients & methods: A total of 90 subjects aged 60 years or older were included in this study; 45 patients were assigned to the case group and control group, respectively. A total of 31 target metabolites were quantitatively analyzed by parallel reaction monitoring between the two groups. Results & conclusion: Three metabolites were screened out, including cystine, serine and alanine/sarcosine. Logistic regression and random forest analysis were used to establish AD diagnosis models, and the model combining metabolic biomarkers and demographic variables had higher detection efficiency (area under the curve = 0.869). A combination diagnostic model to provide a scientific reference for early screening and diagnosis of AD was constructed.

Clock Drawing Test: Types of Errors and Accuracy in Early Cognitive Screening

BACKGROUND

Clock Drawing Test (CDT) is a commonly used screening tool for cognitive disorders, known for its ease of administration and scoring. Despite frequent use by clinicians, CDT is criticized for its poor predictive value in mild cases of impairment.

OBJECTIVE

To evaluate CDT as a screening tool for early stage of cognitive impairment in biomarker-verified Alzheimer's disease (AD) and depressive disorder (DD).

METHODS

We analyzed CDT of 172 patients with verified AD, 70 patients with DD, in whom neurodegenerative disorder was excluded using cerebrospinal fluid biomarkers, and 58 healthy older adults. CDT was scored using the semi-quantitative (Shulman) and itemized criteria (adapted from Mendez).

RESULTS

Logistic regression showed that for both DD and AD patients with high Mini-Mental State Examination (MMSE) scores (27 and above) the significant predicting variable is uneven number spacing. As MMSE deteriorates (24-26 points), an additional error of setting clock hands is predictive of the disease. In the low MMSE condition, CDT showed an acceptable discrimination for AD (AUC itemized 0.740, Shulman 0.741) and DD (AUC itemized 0.827, Shulman 0.739) using both scoring methods. In the high MMSE condition, discrimination rates were acceptable using itemized scoring but poor using Shulman scoring for both AD (AUC itemized 0.707, Shulman 0.677) and DD (AUC itemized 0.755, Shulman 0.667) groups.

CONCLUSION

Ideally, modern diagnostic process should take place before the cognitive performance drops beneath the healthy range. This makes CDT of little use when screening patients with very mild cognitive deficits.

Effects of cognitive impairment and depressive symptoms on health-related quality of life in community-dwelling older adults: The mediating role of disability in the activities of daily living and the instrumental activities of daily living

The objective of this study was to estimate the joint effects of cognitive impairment and depressive symptoms on health-related quality of life (HRQoL) and to explore the mediating role of disability among Chinese community-dwelling older adults. A cross-sectional study was conducted with 2525 community-dwelling older adults aged ≥60 years and living in Shanghai, China in 2019. Participants were divided into four groups: (1) non-depressed without dementia, (2) non-depressed with probable MCI, (3) depressed without dementia and (4) depressed with probable mild cognitive impairment (MCI). HRQoL was assessed using the 36-Item Short-Form Health Survey. Cognitive impairment and depressive symptoms were evaluated with the AD8 and the Geriatric Depression Scale respectively. Activities of daily living (ADL) and instrumental activities of daily living (IADL) disability and other sociodemographic variables were also assessed. The results of this study showed that controlling for sociodemographic characteristics, significant differences in a physical component score (PCS) and a mental component score (MCS) of HRQoL were found across the four groups. Compared to those who were non-depressed without dementia, older adults who were depressed with probable MCI reported the lowest level of PCS and MCS, followed by older adults who were depressed without dementia. Both ADL and IADL disabilities played mediating roles in the relationship between cognitive impairment and depressive symptoms and PCS. Based on this study, we suggest that the early detection and adequate management of depressive symptoms and cognitive status-as well as efforts to improve individuals' ability to manage their ADLs and IADLs-may help to maintain or improve their HRQoL.

Cognitive Assessment Tools Recommended in Geriatric Oncology Guidelines: A Rapid Review

Cognitive assessment is a cornerstone of geriatric care. Cognitive impairment has the potential to significantly impact multiple phases of a person's cancer care experience. Accurately identifying this vulnerability is a challenge for many cancer care clinicians, thus the use of validated cognitive assessment tools are recommended. As international cancer guidelines for older adults recommend Geriatric Assessment (GA) which includes an evaluation of cognition, clinicians need to be familiar with the overall interpretation of the commonly used cognitive assessment tools. This rapid review investigated the cognitive assessment tools that were most frequently recommended by Geriatric Oncology guidelines: Blessed Orientation-Memory-Concentration test (BOMC), Clock Drawing Test (CDT), Mini-Cog, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Short Portable Mental Status Questionnaire (SPMSQ). A detailed appraisal of the strengths and limitations of each tool was conducted, with a focus on practical aspects of implementing cognitive assessment tools into real-world clinical settings. Finally, recommendations on choosing an assessment tool and the additional considerations beyond screening are discussed.

Mini-Cog for the detection of dementia within a secondary care setting

BACKGROUND

The diagnosis of Alzheimer's disease dementia and other dementias relies on clinical assessment. There is a high prevalence of cognitive disorders, including undiagnosed dementia in secondary care settings. Short cognitive tests can be helpful in identifying those who require further specialist diagnostic assessment; however, there is a lack of consensus around the optimal tools to use in clinical practice. The Mini-Cog is a short cognitive test comprising three-item recall and a clock-drawing test that is used in secondary care settings.

OBJECTIVES

The primary objective was to determine the accuracy of the Mini-Cog for detecting dementia in a secondary care setting. The secondary objectives were to investigate the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity will include the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality.

SEARCH METHODS

We searched the following sources in September 2012, with an update to 12 March 2019: Cochrane Dementia Group Register of Diagnostic Test Accuracy Studies, MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Web of Knowledge), Science Citation Index (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We made no exclusions with regard to language of Mini-Cog administration or language of publication, using translation services where necessary.

SELECTION CRITERIA

We included cross-sectional studies and excluded case-control designs, due to the risk of bias. We selected those studies that included the Mini-Cog as an index test to diagnose dementia where dementia diagnosis was confirmed with reference standard clinical assessment using standardised dementia diagnostic criteria. We only included studies in secondary care settings (including inpatient and outpatient hospital participants).

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts generated by the electronic database searches. Two review authors independently checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool. We extracted data into two-by-two tables to allow calculation of accuracy metrics for individual studies, reporting the sensitivity, specificity, and 95% confidence intervals of these measures, summarising them graphically using forest plots.

MAIN RESULTS

Three studies with a total of 2560 participants fulfilled the inclusion criteria, set in neuropsychology outpatient referrals, outpatients attending a general medicine clinic, and referrals to a memory clinic. Only n = 1415 (55.3%) of participants were included in the analysis to inform evaluation of Mini-Cog test accuracy, due to the selective use of available data by study authors. There were concerns related to high risk of bias with respect to patient selection, and unclear risk of bias and high concerns related to index test conduct and applicability. In all studies, the Mini-Cog was retrospectively derived from historic data sets. No studies included acute general hospital inpatients. The prevalence of dementia ranged from 32.2% to 87.3%. The sensitivities of the Mini-Cog in the individual studies were reported as 0.67 (95% confidence interval (CI) 0.63 to 0.71), 0.60 (95% CI 0.48 to 0.72), and 0.87 (95% CI 0.83 to 0.90). The specificity of the Mini-Cog for each individual study was 0.87 (95% CI 0.81 to 0.92), 0.65 (95% CI 0.57 to 0.73), and 1.00 (95% CI 0.94 to 1.00). We did not perform meta-analysis due to concerns related to risk of bias and heterogeneity.

AUTHORS' CONCLUSIONS

This review identified only a limited number of diagnostic test accuracy studies using Mini-Cog in secondary care settings. Those identified were at high risk of bias related to patient selection and high concerns related to index test conduct and applicability. The evidence was indirect, as all studies evaluated Mini-Cog differently from the review question, where it was anticipated that studies would conduct Mini-Cog and independently but contemporaneously perform a reference standard assessment to diagnose dementia. The pattern of test accuracy varied across the three studies. Future research should evaluate Mini-Cog as a test in itself, rather than derived from other neuropsychological assessments. There is also a need for evaluation of the feasibility of the Mini-Cog for the detection of dementia to help adequately determine its role in the clinical pathway.

Mini-Cog for the detection of dementia within a primary care setting

BACKGROUND

Alzheimer's disease and other forms of dementia are becoming increasingly common with the aging of most populations. The majority of individuals with dementia will first present for care and assessment in primary care settings. There is a need for brief dementia screening instruments that can accurately detect dementia in primary care settings. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings.

OBJECTIVES

To determine the accuracy of the Mini-Cog for detecting dementia in a primary care setting.

SEARCH METHODS

We searched the Cochrane Dementia and Cognitive Improvement Register of Diagnostic Test Accuracy Studies, MEDLINE, Embase and four other databases, initially to September 2012. Since then, four updates to the search were performed using the same search methods, and the most recent was January 2017. We used citation tracking (using the databases' 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data.

SELECTION CRITERIA

We only included studies that evaluated the Mini-Cog as an index test for the diagnosis of Alzheimer's disease dementia or related forms of dementia when compared to a reference standard using validated criteria for dementia. We only included studies that were conducted in primary care populations.

DATA COLLECTION AND ANALYSIS

We extracted and described information on the characteristics of the study participants and study setting. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria we evaluated the quality of studies, and we assessed risk of bias and applicability of each study for each domain in QUADAS-2. Two review authors independently extracted information on the true positives, true negatives, false positives, and false negatives and entered the data into Review Manager 5 (RevMan 5). We then used RevMan 5 to determine the sensitivity, specificity, and 95% confidence intervals. We summarized the sensitivity and specificity of the Mini-Cog in the individual studies in forest plots and also plotted them in a receiver operating characteristic plot. We also created a 'Risk of bias' and applicability concerns graph to summarize information related to the quality of included studies.

MAIN RESULTS

There were a total of four studies that met our inclusion criteria, including a total of 1517 total participants. The sensitivity of the Mini-Cog varied between 0.76 to 1.00 in studies while the specificity varied between 0.27 to 0.85. The included studies displayed significant heterogeneity in both methodologies and clinical populations, which did not allow for a meta-analysis to be completed. Only one study (Holsinger 2012) was found to be at low risk of bias on all methodological domains. The results of this study reported that the sensitivity of the Mini-Cog was 0.76 and the specificity was 0.73. We found the quality of all other included studies to be low due to a high risk of bias with methodological limitations primarily in their selection of participants.

AUTHORS' CONCLUSIONS

There is a limited number of studies evaluating the accuracy of the Mini-Cog for the diagnosis of dementia in primary care settings. Given the small number of studies, the wide range in estimates of the accuracy of the Mini-Cog, and methodological limitations identified in most of the studies, at the present time there is insufficient evidence to recommend that the Mini-Cog be used as a screening test for dementia in primary care. Further studies are required to determine the accuracy of Mini-Cog in primary care and whether this tool has sufficient diagnostic test accuracy to be useful as a screening test in this setting.

Mini-Cog for the diagnosis of Alzheimer's disease dementia and other dementias within a secondary care setting

BACKGROUND

The diagnosis of Alzheimer's disease dementia and other dementias relies on clinical assessment. There is a high prevalence of cognitive disorders, including undiagnosed dementia in secondary care settings. Short cognitive tests can be helpful in identifying those who require further specialist diagnostic assessment; however, there is a lack of consensus around the optimal tools to use in clinical practice. The Mini-Cog is a short cognitive test comprising three-item recall and a clock-drawing test that is used in secondary care settings.

OBJECTIVES

The primary objective was to determine the diagnostic accuracy of the Mini-Cog for detecting Alzheimer's disease dementia and other dementias in a secondary care setting. The secondary objectives were to investigate the heterogeneity of test accuracy in the included studies and potential sources of heterogeneity. These potential sources of heterogeneity will include the baseline prevalence of dementia in study samples, thresholds used to determine positive test results, the type of dementia (Alzheimer's disease dementia or all causes of dementia), and aspects of study design related to study quality.

SEARCH METHODS

We searched the following sources in September 2012, with an update to 12 March 2019: Cochrane Dementia Group Register of Diagnostic Test Accuracy Studies, MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (Web of Knowledge), Science Citation Index (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We made no exclusions with regard to language of Mini-Cog administration or language of publication, using translation services where necessary.

SELECTION CRITERIA

We included cross-sectional studies and excluded case-control designs, due to the risk of bias. We selected those studies that included the Mini-Cog as an index test to diagnose dementia where dementia diagnosis was confirmed with reference standard clinical assessment using standardised dementia diagnostic criteria. We only included studies in secondary care settings (including inpatient and outpatient hospital participants).

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts generated by the electronic database searches. Two review authors independently checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool. We extracted data into two-by-two tables to allow calculation of accuracy metrics for individual studies, reporting the sensitivity, specificity, and 95% confidence intervals of these measures, summarising them graphically using forest plots.

MAIN RESULTS

Three studies with a total of 2560 participants fulfilled the inclusion criteria, set in neuropsychology outpatient referrals, outpatients attending a general medicine clinic, and referrals to a memory clinic. Only n = 1415 (55.3%) of participants were included in the analysis to inform evaluation of Mini-Cog test accuracy, due to the selective use of available data by study authors. There were concerns related to high risk of bias with respect to patient selection, and unclear risk of bias and high concerns related to index test conduct and applicability. In all studies, the Mini-Cog was retrospectively derived from historic data sets. No studies included acute general hospital inpatients. The prevalence of dementia ranged from 32.2% to 87.3%. The sensitivities of the Mini-Cog in the individual studies were reported as 0.67 (95% confidence interval (CI) 0.63 to 0.71), 0.60 (95% CI 0.48 to 0.72), and 0.87 (95% CI 0.83 to 0.90). The specificity of the Mini-Cog for each individual study was 0.87 (95% CI 0.81 to 0.92), 0.65 (95% CI 0.57 to 0.73), and 1.00 (95% CI 0.94 to 1.00). We did not perform meta-analysis due to concerns related to risk of bias and heterogeneity.

AUTHORS' CONCLUSIONS

This review identified only a limited number of diagnostic test accuracy studies using Mini-Cog in secondary care settings. Those identified were at high risk of bias related to patient selection and high concerns related to index test conduct and applicability. The evidence was indirect, as all studies evaluated Mini-Cog differently from the review question, where it was anticipated that studies would conduct Mini-Cog and independently but contemporaneously perform a reference standard assessment to diagnose dementia. The pattern of test accuracy varied across the three studies. Future research should evaluate Mini-Cog as a test in itself, rather than derived from other neuropsychological assessments. There is also a need for evaluation of the feasibility of the Mini-Cog for the diagnosis of dementia to help adequately determine its role in the clinical pathway.

Estimation of diagnostic performance of dementia screening tests: Mini-Mental State Examination, Mini-Cog, Clock Drawing test and Ascertain Dementia 8 questionnaire

OBJECTIVE

Dementia is one of the leading causes of dependence in the elderly. This study was conducted to estimate diagnostic performance of dementia screening tests including Mini-Mental State Examination (MMSE), Mini-Cog, Clock Drawing Test (CDT) and Ascertain Dementia 8 questionnaire (AD8) by Bayesian models.

METHOD

A total of 2015 participants aged 65 years or more in eastern China were enrolled. The four screening tests were administered and scored by specifically trained psychiatrists. The prior information of sensitivity and specificity of every screening test was updated via Bayes' theorem to a posterior distribution. Then the results were compared with the estimation based on National Institute of Aging-Alzheimer's Association criteria (NIA-AA).

RESULTS

The diagnostic characteristics of Mini-Cog, including sensitivity, specificity, PPV, NPV, especially the Youden index, performed well, even better than the combinations of several screening tests.

CONCLUSION

The Mini-Cog with excellent screening characteristics, spending less time, could be considered to be used as a screening test to help to screen patients with cognitive impairment or dementia early. And Bayesian method was shown to be a suitable tool for evaluating dementia screening tests.

CONCLUSION

The Mini-Cog with excellent screening characteristics, spending less time, could be considered to be used as a screening test to help to screen patients with cognitive impairment or dementia early. And Bayesian method was shown to be a suitable tool for evaluating dementia screening tests.

Comparison of the value of Mini-Cog and MMSE screening in the rapid identification of Chinese outpatients with mild cognitive impairment

Patients with mild cognitive impairment (MCI) are at high risk of dementia, but early identification and active intervention can reduce its morbidity and the incidence of dementia. There is currently no suitable neuropsychological assessment scale to effectively identify MCI in neurological outpatient departments in China. The Mini-Mental State Examination (MMSE) is often used to screen for MCI in outpatient departments in China.To compare the value of Mini-Cog and MMSE in screening patients for MCI in a neurological outpatient department, and determine differences in the value of Mini-Cog for different ages and educational levels.This was a retrospective study of 229 patients with suspected MCI who visited the Cangzhou Central Hospital between March 2012 and April 2016. The MCI group included 119 patients diagnosed with MCI and 110 cases without MCI (non-MCI group). The MCI patients were subgrouped as 40 to 60 years of age, 61 to 80 years, and >80 years; and as without education, ≤6 years education, and >6 years education. All subjects were assessed using the Mini-Cog and MMSE.There were significant differences in Mini-Cog (P < .05) and MMSE (P < .05) between the MCI and non-MCI groups. The sensitivity, specificity, positive predictive value, negative predictive value, and Youden index (85.71%, 79.41%, 0.8108, 0.8438, and 0.6550) of Mini-Cog were all higher than those of MMSE (64.76%, 71.57%, 0.7010, 0.6364, and 0.3370) in identifying MCI, but there was no significant difference in specificity (P > .05). Mini-Cog was better than MMSE (P < .05) for MCI patients with different ages and education levels.These results showed that the Mini-Cog was superior to MMSE in identifying MCI patients. Mini-Cog was less affected by age and education level than MMSE. The Mini-Cog assessment was short (3-4 minutes) and easily accepted by the patients. Mini-Cog could be more suitable for application in outpatient department in primary hospitals.

Mini-Cog for the diagnosis of Alzheimer's disease dementia and other dementias within a primary care setting

BACKGROUND

Alzheimer's disease and other forms of dementia are becoming increasingly common with the aging of most populations. The majority of individuals with dementia will first present for care and assessment in primary care settings. There is a need for brief dementia screening instruments that can accurately diagnose dementia in primary care settings. The Mini-Cog is a brief, cognitive screening test that is frequently used to evaluate cognition in older adults in various settings.

OBJECTIVES

To determine the diagnostic accuracy of the Mini-Cog for diagnosing Alzheimer's disease dementia and related dementias in a primary care setting.

SEARCH METHODS

We searched the Cochrane Dementia and Cognitive Improvement Register of Diagnostic Test Accuracy Studies, MEDLINE, Embase and four other databases, initially to September 2012. Since then, four updates to the search were performed using the same search methods, and the most recent was January 2017. We used citation tracking (using the databases' 'related articles' feature, where available) as an additional search method and contacted authors of eligible studies for unpublished data.

SELECTION CRITERIA

We only included studies that evaluated the Mini-Cog as an index test for the diagnosis of Alzheimer's disease dementia or related forms of dementia when compared to a reference standard using validated criteria for dementia. We only included studies that were conducted in primary care populations.

DATA COLLECTION AND ANALYSIS

We extracted and described information on the characteristics of the study participants and study setting. Using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria we evaluated the quality of studies, and we assessed risk of bias and applicability of each study for each domain in QUADAS-2. Two review authors independently extracted information on the true positives, true negatives, false positives, and false negatives and entered the data into Review Manager 5 (RevMan 5). We then used RevMan 5 to determine the sensitivity, specificity, and 95% confidence intervals. We summarized the sensitivity and specificity of the Mini-Cog in the individual studies in forest plots and also plotted them in a receiver operating characteristic plot. We also created a 'Risk of bias' and applicability concerns graph to summarize information related to the quality of included studies.

MAIN RESULTS

There were a total of four studies that met our inclusion criteria, including a total of 1517 total participants. The sensitivity of the Mini-Cog varied between 0.76 to 1.00 in studies while the specificity varied between 0.27 to 0.85. The included studies displayed significant heterogeneity in both methodologies and clinical populations, which did not allow for a meta-analysis to be completed. Only one study (Holsinger 2012) was found to be at low risk of bias on all methodological domains. The results of this study reported that the sensitivity of the Mini-Cog was 0.76 and the specificity was 0.73. We found the quality of all other included studies to be low due to a high risk of bias with methodological limitations primarily in their selection of participants.

AUTHORS' CONCLUSIONS

There is a limited number of studies evaluating the accuracy of the Mini-Cog for the diagnosis of dementia in primary care settings. Given the small number of studies, the wide range in estimates of the accuracy of the Mini-Cog, and methodological limitations identified in most of the studies, at the present time there is insufficient evidence to recommend that the Mini-Cog be used as a screening test for dementia in primary care. Further studies are required to determine the accuracy of Mini-Cog in primary care and whether this tool has sufficient diagnostic test accuracy to be useful as a screening test in this setting.

Psychometric Properties of the Persian Adaptation of Mini-Cog Test in Iranian Older Adults

The aim of this study was to assess the psychometric properties of the Mini-Cog in Iranian older adults. It was a cross-sectional study; 50 older people with dementia and 50 without dementia who matched for age, gender, and education entered the study. The diagnostic and statistical manual of mental disorders criteria for dementia were used as gold standard. A battery of scales included the abbreviated mental test score (AMTS), the Geriatric Depression Scale, and the Mini-Cog was performed. Validity and reliability of the Mini-Cog determined using the Pearson product-moment correlation coefficient (Pearson's r), Cronbach's alpha, and Receiver Operating Characteristic (ROC) curve analysis. The Persian version of Mini-Cog showed a good inter-rater reliability ( K = 0.76, p < .01) and a positive concurrent validity ( r = 0.39, p < .01) with the AMTS. The sensitivity and specificity were 88% and 62.8%, respectively, using the original cutoff point of 2. The findings showed that the Persian version of Mini-Cog have an acceptable sensitivity, specificity, and substantial overall agreement with the AMTS.

[Organization of out-patient psychiatric care in dementia and cognitive impairment in aged. Part II: Clinical and economic efficacy of memory clinics and Alzheimer's disease centers]

The part II of the review is focused on a history of developing of memory clinics and Alzheimer's disease centers as well as on the indices of their activity in various countries and in Russia. Approaches to the evaluation of clinical and economic efficacy of new technologies of organization of care and a role of the national programs in solving of the problem of old age dementias were considered.

Screening for Dementia in Older Adults: Comparison of Mini-Mental State Examination, Mini-Cog, Clock Drawing Test and AD8

This study was conducted to estimate screening performance of dementia screening tools including Mini-Mental State Examination (MMSE), Mini-Cog, Clock Drawing Test (CDT) and Ascertain Dementia 8 questionnaire (AD8) for older adults. 2015 participants aged 65 years or more in eastern China were enrolled. 4 screening tests were administered and scored by specifically trained psychiatrists. We used data from two-by-two tables to calculate the sensitivity, specificity, and positive and negative predictive values (PPV/NPV). Our study showed that dementia was highly prevalent among elderly in Zhejiang province. The Mini-Cog, with excellent screening characteristics and spending less time, could be considered to be used as a screening tool among communities to help to diagnose dementia early.