MACE for Diagnosis of Dementia and MCI: Examining Cut-Offs and Predictive Values

Comparison of the Diagnostic Accuracy of Five Cognitive Screening Tests for Diagnosing Mild Cognitive Impairment in Patients Consulting for Memory Loss

Objectives: We aimed to evaluate and compare the diagnostic capacity of five cognitive screening tests for the diagnosis of mild cognitive impairment (MCI) in patients consulting by memory loss. Methods: A cross-sectional study involving 140 participants with a mean age of 74.42 ± 7.60 years, 87 (62.14%) women. Patients were classified as MCI or cognitively unimpaired according to a comprehensive neuropsychological battery. The diagnostic properties of the following screening tests were compared: Mini-Mental State Examination (MMSE), Addenbrooke's Cognitive Examination III (ACE-III) and Mini-Addenbrooke (M-ACE), Memory Impairment Screen (MIS), Montreal Cognitive Assessment (MoCA), and Rowland Universal Dementia Assessment Scale (RUDAS). Results: The area under the curve (AUC) was 0.861 for the ACE-III, 0.867 for M-ACE, 0.791 for MoCA, 0.795 for MMSE, 0.731 for RUDAS, and 0.672 for MIS. For the memory components, the AUC was 0.869 for ACE-III, 0.717 for MMSE, 0.755 for MoCA, and 0.720 for RUDAS. Cronbach's alpha was 0.827 for ACE-III, 0.505 for MMSE, 0.896 for MoCA, and 0.721 for RUDAS. Correlations with Free and Cued Selective Reminding Test were moderate with M-ACE, ACE-III, and MoCA, and moderate for the other tests. The M-ACE showed the best balance between diagnostic capacity and time of administration. Conclusions: ACE-III and its brief version M-ACE showed better diagnostic properties for the diagnosis of MCI than the other screening tests. MoCA and MMSE showed adequate properties, while the diagnostic capacity of MIS and RUDAS was limited.

Impact of aging on copper isotopic composition in the murine brain

Aging is the main risk factor for Alzheimer's disease (AD). AD is linked to alterations in metal homeostasis and changes in stable metal isotopic composition can occur, possibly allowing the latter to serve as relevant biomarkers for potential AD diagnosis. Copper stable isotopes are used to investigate changes in Cu homeostasis associated with various diseases. Prior work has shown that in AD mouse models, the accumulation of 63Cu in the brain is associated with the disease's progression. However, our understanding of how the normal aging process influences the brain's isotopic composition of copper remains limited. In order to determine the utility and predictive power of Cu isotopes in AD diagnostics, we aim-in this study-to develop a baseline trajectory of Cu isotopic composition in the normally aging mouse brain. We determined the copper concentration and isotopic composition in brains of 30 healthy mice (WT) ranging in age from 6 to 12 mo, and further incorporate prior data obtained for 3-mo-old healthy mice; this range approximately equates to 20-50 yr in human equivalency. A significant 65Cu enrichment has been observed in the 12-mo-old mice compared to the youngest group, concomitant with an increase in Cu concentration with age. Meanwhile, literature data for brains of AD mice display an enrichment in 63Cu isotope compared to WT. It is acutely important that this baseline enrichment in 65Cu is fully constrained and normalized against if any coherent diagnostic observations regarding 63Cu enrichment as a biomarker for AD are to be developed.

On the Dependence of the Critical Success Index (CSI) on Prevalence

The critical success index (CSI) is an established metric used in meteorology to verify the accuracy of weather forecasts. It is defined as the ratio of hits to the sum of hits, false alarms, and misses. Translationally, CSI has gained popularity as a unitary outcome measure in various clinical situations where large numbers of true negatives may influence the interpretation of other, more traditional, outcome measures, such as specificity (Spec) and negative predictive value (NPV), or when unified interpretation of positive predictive value (PPV) and sensitivity (Sens) is needed. The derivation of CSI from measures including PPV has prompted questions as to whether and how CSI values may vary with disease prevalence (P), just as PPV estimates are dependent on P, and hence whether CSI values are generalizable between studies with differing prevalences. As no detailed study of the relation of CSI to prevalence has been undertaken hitherto, the dataset of a previously published test accuracy study of a cognitive screening instrument was interrogated to address this question. Three different methods were used to examine the change in CSI across a range of prevalences, using both the Bayes formula and equations directly relating CSI to Sens, PPV, P, and the test threshold (Q). These approaches showed that, as expected, CSI does vary with prevalence, but the dependence differs according to the method of calculation that is adopted. Bayesian rescaling of both Sens and PPV generates a concave curve, suggesting that CSI will be maximal at a particular prevalence, which may vary according to the particular dataset.

Cut-off scores for mild and moderate dementia on the Addenbrooke's Cognitive Examination-III and the Mini-Addenbrooke's Cognitive Examination compared with the Mini-Mental State Examination

AIMS AND METHOD

We aimed to establish cut-off scores to stage dementia on the Addenbrooke's Cognitive Examination-III (ACE-III) and the Mini-Addenbrooke's Cognitive Examination (M-ACE) compared with scores traditionally used with the Mini-Mental State Examination (MMSE). Our cross-sectional study recruited 80 patients and carers from secondary care services in the UK.

RESULTS

A score ≤76 on the ACE-III and ≤19 on the M-ACE correlated well with MMSE cut-offs for mild dementia, with a good fit on the receiver operating characteristic analysis for both the ACE-III and M-ACE. The cut-off for moderate dementia had lower sensitivity and specificity. There were low to moderate correlations between the cognitive scales and scales for everyday functioning and behaviour.

CLINICAL IMPLICATIONS

Our findings allow an objective interpretation of scores on the ACE-III and the M-ACE relative to the MMSE, which may be helpful for clinical services and research trials.

Mini-ACE: Validation Study Among Older People in Long-Term Care

Background

The Mini-Addenbrooke's Cognitive Examination (M-ACE) is a valid and reliable tool that accurately differentiates various types of cognitive impairment from Normal-cognition assessed in multiple settings. However, its validity among older individuals in long-term care (LTC) was not yet established. Therefore, we sought to assess the Portuguese M-ACE's validity, reliability, and accuracy in detecting cognitive impairment no-dementia (CIND) in LTC users.

Methods

A comprehensive assessment was performed on 196 LTC Portuguese users aged ≥ 60 years, among whom 71 had Normal-cognition, and 125 had CIND.

Results

The M-ACE was found to be reliable (McDonald's ω = .86, Cronbach's α = .85) and consistent over time (r = .72; ICC = .83) and between raters (k = .92). Strong correlations with related measures supported construct validity (both r = .67). The M-ACE accurately distinguished CIND from Normal-cognition with a cut-off of 17 points (AUC = 0.81, Sensitivity = 81.7%, Specificity = 74.4%).

Conclusion

Our findings suggest that the Portuguese M-ACE is a valid and reliable cognitive assessment tool for LTC users, allowing for accurate differentiation between CIND and Normal-cognition. Thus, the M-ACE's use could contribute to the early detection and intervention of cognitive disorders, especially among older adults in LTC.

Applying ACE-III, M-ACE and MMSE to Diagnostic Screening Assessment of Cognitive Functions within the Polish Population

The research aims to compare the accuracy of the mini-mental state examination (MMSE), the Addenbrooke's cognitive examination III (ACE-III) and the mini-Addenbrooke's cognitive examination (M-ACE) within the Polish population. The model comprised several stages: the features of each test were compared; the shifts in result categorisations between the norm and below the norm were analysed; a third category-mild cognitive impairment (MCI)-was included. Additionally, particular ACE-III domains that scored below domain-specific norm thresholds were analysed to establish the potential early predictors of dementia. All tests correlated to a high and very high degree-cf. MMSE and ACE-III (r = 0.817; p < 0.001), MMSE and M-ACE (r = 0.753; p < 0.001), ACE-III and M-ACE (r = 0.942; p < 0.001). The area under the ROC curve for the ACE-III diagnostic variable had a high value (AUC = 0.920 ± 0.014). A cut-off point of 81 points was suggested for ACE-III; the M-ACE diagnostic variable had an equally high value (AUC = 0.891 ± 0.017). A cut-off point of 20 points was suggested. A significant decrease in the mean score values for people who scored norm or below the norm under ACE-III, as compared to the MMSE results for norm (p < 0.0001), occurred for speech fluency (which decreased by 26.4%). The tests in question are characterised by high sensitivity and specificity. Targeted ACE-III seems best recommended for use in specialised diagnostic centres, whereas M-ACE appears to be a better suited diagnostic alternative for primary health care centres in comparison to MMSE.

Screening Accuracy of Mini Addenbrooke's Cognitive Examination Test for HIV-Associated Neurocognitive Disorders in People Ageing with HIV

Aging and increased cardiovascular risk are major drivers for HIV-associated neurocognitive disorders (HAND), for which accurate screenings are lacking. Mini-Addenbrooke's Cognitive Examination (MACE) reliably detects vascular and neurodegenerative cognitive decline among HIV-negative patients. We evaluated MACE diagnostic accuracy in detecting HAND in people living with HIV (PLWH) and we compared it with the International HIV Dementia Scale (IHDS). A single-centre double-blind study of diagnostic accuracy on adult outpatient PLWH without neurocognitive confounding was performed. MACE and IHDS were administered in 5 and 10 min by clinicians, followed by the reference standard battery (14 tests) by neuropsychologists. HAND diagnosis was based on the modified version of Frascati's criteria by Gisslén to reduce false positives. Exploratory cut-offs were evaluated for MACE. Diagnostic accuracy and clinical utility parameters were assessed. 231 patients were enrolled. 75.7% men with a median age, education, and length of infection of 54 (48-59), 10 (8-13) and 16 (5-25) years. HAND prevalence was 48.5% (38.9% asymptomatic impairment). Compared to IHDS, MACE sensitivity (89.3% vs 70.5%), specificity (94.1% vs 63.0%), correct classification rate (86.5% vs 66.7%), J index (0.83 vs 0.34), AUROC (0.97 vs 0.79), agreement with the gold standard (k 0.84 vs 0.33) and effect size in distinguishing HAND vs non-HAND (d 2.11 vs 1.15) were higher. Among PLWH aged 65 years and above (n = 37) MACE performance was consistently better than IHDS. The quick and easy-to-perform MACE could possess an accurate and useful screening performance for HAND in otherwise neurocognitively healthy cohorts of PLWH.

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.

Evaluating binary classifiers: extending the Efficiency Index

Aim: To further develop an 'efficiency index' (EI), the ratio of classifier accuracy to inaccuracy, to construct balanced EI (BEI) and unbiased EI (UEI) measures to evaluate a dementia screening test. EI formulations were compared with cognate formulations of the identification index (II). Materials & methods: A prospective pragmatic test accuracy study dataset examining Mini-Addenbrooke's Cognitive Examination (MACE) was used. Results: EI, BEI and UEI varied with test cutoff. UEI was the most stringent measure, correcting for both disease prevalence and test threshold. Unlike II formulations, the boundary values of EI formulations (0,∞) ensure that negative values never occur. Conclusion: EI metrics may be useful for the evaluation of cognitive screening instruments and other diagnostic tests used for neurodegenerative disorders.

Accuracy of cognitive screening instruments reconsidered: overall, balanced or unbiased accuracy?

Aim: To examine three different accuracy metrics for evaluation of cognitive screening instruments: overall correct classification accuracy (Acc), the sum of true positives and negatives divided by the total number tested; balanced accuracy (balanced Acc), half of the sum of sensitivity and specificity; and unbiased accuracy (unbiased Acc), removing biasing effects of random associations between test results and disease prevalence. Materials & methods: Data from a prospective test accuracy study of Mini-Addenbrooke's Cognitive Examination were used to calculate and plot the Acc measures. Results: Each Acc metric resulted in a similar pattern of results across the range of Mini-Addenbrooke's Cognitive Examination cut-offs for diagnosis of both dementia and mild cognitive impairment. Acc and balanced Acc gave more optimistic outcomes (closer to possible maximum value of 1) than unbiased Acc. Conclusion: Unbiased Acc may have advantages over Acc and balanced Acc by removing biasing effects of random associations between test result and disease prevalence.

Cognitive screening instruments for dementia: comparing metrics of test limitation

Cognitive screening instruments (CSIs) for dementia and mild cognitive impairment are usually characterized in terms of measures of discrimination such as sensitivity, specificity, and likelihood ratios, but these CSIs also have limitations.

Communicating Risk: Developing an "Efficiency Index" for Dementia Screening Tests

Diagnostic and screening tests may have risks such as misdiagnosis, as well as the potential benefits of correct diagnosis. Effective communication of this risk to both clinicians and patients can be problematic. The purpose of this study was to develop a metric called the "efficiency index" (EI), defined as the ratio of test accuracy and inaccuracy, to evaluate screening tests for dementia. This measure was compared with a previously described "likelihood to be diagnosed or misdiagnosed" (LDM), also based on "numbers needed" metrics. Datasets from prospective pragmatic test accuracy studies examining four brief cognitive screening instruments (Mini-Mental State Examination; Montreal Cognitive Assessment; Mini-Addenbrooke's Cognitive Examination (MACE); and Free-Cog) were analysed to calculate values for EI and LDM, and to examine their variation with test cut-off for MACE and dementia prevalence. EI values were also calculated using a modification of McGee's heuristic for the simplification of likelihood ratios to estimate percentage change in diagnostic probability. The findings indicate that EI is easier to calculate than LDM and, unlike LDM, may be classified either qualitatively or quantitatively in a manner similar to likelihood ratios. EI shows the utility or inutility of diagnostic and screening tests, illustrating the inevitable trade-off between diagnosis and misdiagnosis. It may be a useful metric to communicate risk in a way that is easily intelligible for both clinicians and patients.

Receiver operating characteristic plot and area under the curve with binary classifiers: pragmatic analysis of cognitive screening instruments

Aim: To examine whether receiver operating characteristic plots and area under the curve (AUC) values may be potentially misleading when assessing cognitive screening instruments as binary predictors rather than as categorical or continuous scales. Materials & methods: AUC was calculated using different methods (rank-sum, diagnostic odds ratio) using data from test accuracy studies of two binary classifiers of cognitive status (applause sign, attended with sign), a screener producing categorical data (Codex), and a continuous scale screening test (Mini-Addenbrooke's Cognitive Examination). Results: For all screeners, AUC calculated using diagnostic odds ratio method was greater than using rank-sum method. When Codex and Mini-Addenbrooke's Cognitive Examination were analyzed as binary (single fixed threshold) tests, AUC using rank-sum method was lower than when screeners were analyzed as categorical or continuous scales, respectively. Conclusion: If cognitive screeners producing categorical or continuous measures are dichotomized, calculated AUC may be an underestimate, thus affecting screening test accuracy.

Defining 'optimal' test cut-off using global test metrics: evidence from a cognitive screening instrument

Aim: To examine the variation of several global metrics of test accuracy with test cut-off for the diagnosis of dementia. These metrics included some based on the receiver operating characteristic curve, such as Youden index, and some independent of receiver operating characteristic curve, such as correct classification accuracy. Materials & methods: Data from a test accuracy study of Mini-Addenbrooke's Cognitive Examination were used to calculate and plot each global measure against test cut-off. Results: Different 'optimal' cut-points were identified for the different global measures, with a spread of ten points in observed optimal cut-off in the 30-point Mini-Addenbrooke's Cognitive Examination scale. Using these optima gave a large variation in test sensitivity from very high (diagnostic odds ratio) to very low (likelihood to be diagnosed or misdiagnosed), but all had high negative predictive value. Conclusion: The method used to determine the cut-off of cognitive screening instruments may have significant implications for test performance.

Mini-Addenbrooke's Cognitive Examination (MACE): a Useful Cognitive Screening Instrument in Older People?

Background

The Mini-Addenbrooke’s Cognitive Examination (MACE) is a recently described brief cognitive screening instrument.

Objective

To examine the test accuracy of MACE for the identification of dementia and mild cognitive impairment (MCI) in a cohort of older patients assessed in a neurology-led dedicated cognitive disorders clinic.

Methods

Cross-sectional assessment of consecutive patients with MACE was performed independent of the reference standard diagnosis based on clinical interview of patient and, where possible, informant and structural brain imaging, and applying standard clinical diagnostic criteria for dementia and MCI. Various test accuracy metrics were examined at two MACE cut-offs ( ≤ 25/30 and ≤ 21/30), comparing the whole patient cohort with those aged ≥ 65 or ≥ 75 years, hence at different disease prevalences.

Results

Dependent upon the chosen cut-off, MACE was either very sensitive or very specific for the identification of any cognitive impairment in the older patient cohorts with increased disease prevalence. However, at both cut-offs the positive predictive values and post-test odds increased in the older patient cohorts. At the more sensitive cut-off, improvements in some new unitary test metrics were also seen.

Conclusion

MACE is a valid instrument for identification of cognitive impairment in older people. Test accuracy metrics may differ with disease prevalence.

Mini-Cog versus Codex (cognitive disorders examination) Is there a difference?

Mini-Cog and Codex (cognitive disorders examination) are brief cognitive screening tests incorporating word-recall and clock drawing tests.

OBJECTIVE

To assess and compare the screening accuracy of Mini-Cog and Codex for diagnosis of dementia and mild cognitive impairment (MCI) in patients attending a dedicated cognitive disorders clinic.

METHODS

Tests were administered to a consecutive cohort of 162 patients, whose reference standard diagnoses based on clinical diagnostic criteria were dementia (44), MCI (26), and subjective memory complaint (92).

RESULTS

Both Mini-Cog and Codex had high sensitivity (>0.8) for dementia diagnosis, but Codex was more specific. For diagnosis of MCI, Mini-Cog had better sensitivity than Codex. Weighted comparisons of Mini-Cog and Codex showed only marginal net benefit for Mini-Cog for dementia diagnosis but larger net benefit for MCI diagnosis.

CONCLUSION

In this pragmatic study both Mini-Cog and Codex were accurate brief screening tests for dementia but Mini-Cog was better for identification of MCI.

Applying Kraemer's Q (Positive Sign Rate): Some Implications for Diagnostic Test Accuracy Study Results

Background/Aims

Sensitivity and specificity (Sens, Spec) are not invariant properties of diagnostic and screening tests, but vary in different patient samples. Kraemer [Evaluating medical tests. Objective and quantitative guidelines. 1992] used the level of test, Q, also known as "positive sign rate" (sum of true and false positives divided by sample size), to calculate quality sensitivity and specificity (QSN, QSP). These scaled indices may be more comparable across different patient samples, but have been little studied hitherto.

Methods

The dataset of a pragmatic test accuracy study of the Mini-Addenbrooke's Cognitive Examination (MACE) was re-interrogated to calculate values of QSN and QSP and other paired and unitary test outcome measures based on them, and comparison was made with outcomes previously calculated by standard methods.

Results

QSN and QSP values in this cohort (n = 755; overall prevalence of dementia and mild cognitive impairment [MCI] 0.15 and 0.29, respectively) were inferior to Sens and Spec, as were all other outcome measures for MACE for the diagnosis of both dementia and MCI. QSN was relatively preserved, indicating the sensitivity of MACE.

Conclusion

Indices of test outcome scaled according to Kraemer's Q, the positive sign rate, are less impressive than outcomes calculated by standard methods. These discrepancies may have implications for test evaluation.

Addenbrooke's Cognitive Examination III (ACE-III) and mini-ACE for the detection of dementia and mild cognitive impairment

BACKGROUND

The number of new cases of dementia is projected to rise significantly over the next decade. Thus, there is a pressing need for accurate tools to detect cognitive impairment in routine clinical practice. The Addenbrooke's Cognitive Examination III (ACE-III), and the mini-ACE are brief, bedside cognitive screens that have previously reported good sensitivity and specificity. The quality and quantity of this evidence has not, however, been robustly investigated.

OBJECTIVES

To assess the diagnostic test accuracy of the ACE-III and mini-ACE for the detection of dementia, dementia sub-types, and mild cognitive impairment (MCI) at published thresholds in primary, secondary, and community care settings in patients presenting with, or at high risk of, cognitive decline.

SEARCH METHODS

We performed the search for this review on 13 February 2019. We searched MEDLINE (OvidSP), Embase (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science Core Collection (ISI Web of Knowledge), PsycINFO (OvidSP), and LILACS (BIREME). We applied no language or date restrictions to the electronic searches; and to maximise sensitivity we did not use methodological filters. The search yielded 5655 records, of which 2937 remained after we removed duplicates. We identified a further four articles through PubMed 'related articles'. We found no additional records through reference list citation searching, or grey literature.

SELECTION CRITERIA

Cross-sectional studies investigating the accuracy of the ACE-III or mini-ACE in patients presenting with, or at high risk of, cognitive decline were suitable for inclusion. We excluded case-control, delayed verification and longitudinal studies, and studies which investigated a secondary cause of dementia. We did not restrict studies by language; and we included those with pre-specified thresholds (88 and 82 for the ACE-III, and 21 or 25 for the mini-ACE).

DATA COLLECTION AND ANALYSIS

We extracted information on study and participant characteristics and used information on dementia and MCI prevalence, sensitivity, specificity, and sample size to generate 2×2 tables in Review Manager 5. We assessed methodological quality of included studies using the QUADAS-2 tool; and we assessed the quality of study reporting with the STARDdem tool. Due to significant heterogeneity in the included studies and an insufficient number of studies, we did not perform meta-analyses.

MAIN RESULTS

This review identified seven studies (1711 participants in total) of cross-sectional design, four examining the accuracy of the ACE-III, and three of the mini-ACE. Overall, the majority of studies were at low or unclear risk of bias and applicability on quality assessment. Studies were at high risk of bias for the index test (n = 4) and reference standard (n = 2). Study reporting was variable across the included studies. No studies investigated dementia sub-types. The ACE-III had variable sensitivity across thresholds and patient populations (range for dementia at 82 and 88: 82% to 97%, n = 2; range for MCI at 88: 75% to 77%, n = 2), but with more variability in specificity (range for dementia: 4% to 77%, n = 2; range for MCI: 89% to 92%, n = 2). Similarly, sensitivity of the mini-ACE was variable (range for dementia at 21 and 25: 70% to 99%, n = 3; range for MCI at 21 and 25: 64% to 95%, n = 3) but with more variability specificity (range for dementia: 32% to 100%, n = 3; range for MCI: 46% to 79%, n = 3). We identified no studies in primary care populations: four studies were conducted in outpatient clinics, one study in an in-patient setting, and in two studies the settings were unclear.

AUTHORS' CONCLUSIONS

There is insufficient information in terms of both quality and quantity to recommend the use of either the ACE-III or mini-ACE for the screening of dementia or MCI in patients presenting with, or at high risk of, cognitive decline. No studies were conducted in a primary care setting so the accuracy of the ACE-III and mini-ACE in this setting are not known. Lower thresholds (82 for the ACE-III, and 21 for the mini-ACE) provide better specificity with acceptable sensitivity and may provide better clinical utility. The ACE-III and mini-ACE should only be used to support the diagnosis as an adjunct to a full clinical assessment. Further research is needed to determine the utility of the ACE-III and mini-ACE for the detection of dementia, dementia sub-types, and MCI. Specifically, the optimal thresholds for detection need to be determined in a variety of settings (primary care, secondary care (inpatient and outpatient), and community services), prevalences, and languages.

Diagnosis of Dementia and Cognitive Impairment

In this special issue of Diagnostics, expert contributors have produced up-to-date research studies and reviews on various topics related to the diagnosis of dementia and cognitive impairment. The methods of the assessments discussed extend from simple neurological signs, which may be elicited in the clinical encounter, through cognitive screening instruments, to sophisticated analyses of neuroimaging and cerebrospinal fluid biomarkers of disease. It is hoped that these various methods may facilitate earlier diagnosis of dementia and its subtypes, and provide differential diagnosis of depression and functional cognitive disorders, as a prelude to meaningful interventions.

What is test accuracy? Comparing unitary accuracy metrics for cognitive screening instruments

Aim: To examine four different accuracy metrics for assessment of commonly used cognitive screening instruments: correct classification accuracy, area under the receiver operating characteristic curve, F measure (F) or F1 score and Matthews correlation coefficient (MCC). Methods: Raw data were extracted from test accuracy studies of Mini-Mental State Examination. Montreal Cognitive Assessment, Mini-Addenbrooke's Cognitive Examination, Six-item Cognitive Impairment Test, informant AD8 and Free-Cog, and used to calculate the accuracy measures. Results: Each metric resulted in similar ordering of the screening instruments for diagnosis of both dementia and mild cognitive impairment. Area under the receiver operating characteristic curve gave the highest (most optimistic) and MCC the lowest (most pessimistic) accuracy value for each test examined, with correct classification accuracy and F falling between. Conclusion: All the accuracy measures examined have potential shortcomings. None can be recommended as the definitive unitary outcome measure for test accuracy studies. However, MCC has theoretical advantages and might be more widely adopted.