This case demonstrates that TBI may cause vulnerability to psychiatric disorders, with long latency periods, and that its course may be independent of cognitive impairment and recovery. Key Words: Bipolar disorder, cognitive dysfunction, traumatic brain injury. Multidisciplinary Screening of Cognitive Impair-ment Following Acquired Brain Impairment. The neuropsychological test battery included administration of the Mini Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975), the Brief Neuropsychology Cognitive Evaluation (BNCE) (Tonkonogy, 1997), and The Neurobehavioural. Byterun builder for php crackle. Demographically corrected norms for African Americans and Caucasians on the Hopkins Verbal Learning Test-Revised, Brief Visuospatial Memory Test-Revised, Stroop Color and Word Test, and Wisconsin Card Sorting Test 64-Card Version.

1. Cognitive Examination Example
2. Brief Neuropsychological Screening

Identify all potential conflicts of interest that might be relevant to your comment.Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.Err on the side of full disclosure.If you have no conflicts of interest, check 'No potential conflicts of interest' in the box below. The information will be posted with your response.Not all submitted comments are published. Please see our for details. Dear Drs Tsoi, Chan, Hirai, Wong, and Kwok, A recently published meta-analysis of the effectiveness of different cognitive screens in detecting dementia stated that the Mini-Cog and the ACE-R are the best alternative screening tests to the MMSE due to their high pooled sensitivity and specificity compared to other alternative screens 4. However the data are at odds with this conclusion.

The Mini-Cog is reported to have pooled sensitivity and specificity values of 0.91 (0.80-0.96) and 0.86 (0.74-0.93), respectively. However, the reported values for the GPCOG are numerically higher with respective values of 0.92 (0.81-0.97) and 0.87 (0.83-0.90). In addition, while the confidence intervals are equally wide between the tests for sensitivity, for specificity they are narrower for the GPCOG than the Mini-Cog. In contrast to these reported measures, in the Methods the authors state that a diagnostic odds ratio (DOR) was used as a single indicator of test performance, to account for the trade-off between sensitivity and specificity in the context of different thresholds used across studies 5. While we agree with this approach, this measure was not reported in the Abstract, Results or online Supplementary Material, so it is unclear to the reader how or if the DOR was actually used to support their conclusions independently of pooled sensitivity and specificity.

Taking reported pooled sensitivity (Se) and specificity (Sp) alone 5, where DOR = (Se x Sp)/((1 – Se) x (1 – Sp)) the GPCOG (76.96) performs better than the Mini-Cog (62.11). Furthermore, the reported prevalence of dementia in the Mini-Cog studies (1182/4178; 28.3%) was slightly higher than that of the GPCOG (292/1082; 27.0%). Since a higher level of dementia prevalence positively biases the chances of detecting dementia, accounting for prevalence may have further increased the sensitivity and specificity of the GPCOG relative to the Mini-Cog. Unless the authors can demonstrate how their conclusions are supported by their data, we believe that the conclusion should have been revised to reflect that the Mini-Cog and GPCOG have at least equivalent diagnostic efficiency for detecting dementia.

REFERENCES 1.Lorentz WJ, Scanlan JM, Borson S. Brief screening tests for dementia. Can J Psychiatry. 2.Milne A, Culverwell A, Guss R, Tuppen J, Whelton R.

Screening for dementia in primary care: a review of the use, efficacy and quality of measures. Int Psychogeriatr.

3.Cullen B, O'Neill B, Evans JJ, Coen RF, Lawlor BA. A review of screening tests for cognitive impairment. J Neurol Neurosurg Psychiatry.

4.Tsoi KKF, Chan JYC, Hirai HW, Wong SYS, Kwok TCY. Cognitive Tests to Detect Dementia: A Systematic Review and Meta-analysis. JAMA Int Med. 5.Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PM. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol. Dear Drs Tsoi, Chan, Hirai, Wong, and Kwok, Several recent reviews 1-3 of the relative utility of cognitive screening instruments have come to different conclusions.

While two sets of reviews recommended the very brief Mini-Cog, GPCOG and MIS for use in general practice 1,2, another review recommended more comprehensive screens (3MS, CASI, SASSI, and ACE-R) 3. A recently published meta-analysis of the effectiveness of different cognitive screens in detecting dementia stated that the Mini-Cog and the ACE-R are the best alternative screening tests to the MMSE due to their high pooled sensitivity and specificity compared to other alternative screens 4. However the data are at odds with this conclusion. The Mini-Cog is reported to have pooled sensitivity and specificity values of 0.91 (0.80-0.96) and 0.86 (0.74-0.93), respectively. However, the reported values for the GPCOG are numerically higher with respective values of 0.92 (0.81-0.97) and 0.87 (0.83-0.90). In addition, while the confidence intervals are equally wide between the tests for sensitivity, for specificity they are narrower for the GPCOG than the Mini-Cog.

In contrast to these reported measures, in the Methods the authors state that a diagnostic odds ratio (DOR) was used as a single indicator of test performance, to account for the trade-off between sensitivity and specificity in the context of different thresholds used across studies 5. While we agree with this approach, this measure was not reported in the Abstract, Results or online Supplementary Material, so it is unclear to the reader how or if the DOR was actually used to support their conclusions independently of pooled sensitivity and specificity. Taking reported pooled sensitivity (Se) and specificity (Sp) alone 5, where DOR = (Se x Sp)/((1 – Se) x (1 – Sp)) the GPCOG (76.96) performs better than the Mini-Cog (62.11). Furthermore, the reported prevalence of dementia in the Mini-Cog studies (1182/4178; 28.3%) was slightly higher than that of the GPCOG (292/1082; 27.0%).

Since a higher level of dementia prevalence positively biases the chances of detecting dementia, accounting for prevalence may have further increased the sensitivity and specificity of the GPCOG relative to the Mini-Cog. Unless the authors can demonstrate how their conclusions are supported by their data, we believe that the conclusion should have been revised to reflect that the Mini-Cog and GPCOG have at least equivalent diagnostic efficiency for detecting dementia. REFERENCES 1.Lorentz WJ, Scanlan JM, Borson S.

Brief screening tests for dementia. Can J Psychiatry. 2.Milne A, Culverwell A, Guss R, Tuppen J, Whelton R. Screening for dementia in primary care: a review of the use, efficacy and quality of measures. Int Psychogeriatr. 3.Cullen B, O'Neill B, Evans JJ, Coen RF, Lawlor BA. A review of screening tests for cognitive impairment.

J Neurol Neurosurg Psychiatry. 4.Tsoi KKF, Chan JYC, Hirai HW, Wong SYS, Kwok TCY. Cognitive Tests to Detect Dementia: A Systematic Review and Meta-analysis.

JAMA Int Med. 5.Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PM. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol. AbstractImportance Dementia is a global public health problem. The Mini-Mental State Examination (MMSE) is a proprietary instrument for detecting dementia, but many other tests are also available.Objective To evaluate the diagnostic performance of all cognitive tests for the detection of dementia.Data Sources Literature searches were performed on the list of dementia screening tests in MEDLINE, EMBASE, and PsychoINFO from the earliest available dates stated in the individual databases until September 1, 2014. Because Google Scholar searches literature with a combined ranking algorithm on citation counts and keywords in each article, our literature search was extended to Google Scholar with individual test names and dementia screening as a supplementary search.Study Selection Studies were eligible if participants were interviewed face to face with respective screening tests, and findings were compared with criterion standard diagnostic criteria for dementia.

Bivariate random-effects models were used, and the area under the summary receiver-operating characteristic curve was used to present the overall performance.Main Outcomes and Measures Sensitivity, specificity, and positive and negative likelihood ratios were the main outcomes.Results Eleven screening tests were identified among 149 studies with more than 49 000 participants. Most studies used the MMSE (n = 102) and included 10 263 patients with dementia. The combined sensitivity and specificity for detection of dementia were 0.81 (95% CI, 0.78-0.84) and 0.89 (95% CI, 0.87-0.91), respectively. Among the other 10 tests, the Mini-Cog test and Addenbrooke’s Cognitive Examination–Revised (ACE-R) had the best diagnostic performances, which were comparable to that of the MMSE (Mini-Cog, 0.91 sensitivity and 0.86 specificity; ACE-R, 0.92 sensitivity and 0.89 specificity). Subgroup analysis revealed that only the Montreal Cognitive Assessment had comparable performance to the MMSE on detection of mild cognitive impairment with 0.89 sensitivity and 0.75 specificity.Conclusions and Relevance Besides the MMSE, there are many other tests with comparable diagnostic performance for detecting dementia. The Mini-Cog test and the ACE-R are the best alternative screening tests for dementia, and the Montreal Cognitive Assessment is the best alternative for mild cognitive impairment.

IntroductionEarly diagnosis of dementia can identify people at risk for complications. Previous studies, have found that health care professionals commonly miss the diagnosis of cognitive impairment or dementia; the prevalence of missed diagnosis ranges from 25% to 90%. Primary care physicians may not recognize cognitive impairment until the moderate to severe stage. Screening tests are quick and useful tools to assess the cognitive condition of patients.The Mini-Mental State Examination (MMSE) is the most widely applied test for dementia screening. Search StrategyA list of screening tests was identified in previous systematic reviews., Literature searches were performed on the list of dementia screening tests in MEDLINE, EMBASE, and PsychoINFO from the earliest available dates stated in the individual databases until September 1, 2014.

Each screening test was separately searched with general keywords of dementia, including Alzheimer, Parkinson, vascular, stroke, cognitive impairment, and dementia. Diagnostic studies comparing accuracy of screening tests for detection of dementia were manually identified from the title or abstract preview of all search records.

The selection was limited to peer-reviewed articles published in English abstracts. Because Google Scholar searches literature with a combined ranking algorithm on citation counts and keywords in each article, our literature search was extended to Google Scholar with individual test names and dementia screening as a supplementary search. The first 10 pages of all search records were scanned. Manual searches were extended to the bibliographies of review articles and included research studies. Screening tests were classified into different categories according to the administration time: 5 minutes or less, 10 minutes or less, and 20 minutes or less.

Data ExtractionTwo investigators (J.Y.C.C., H.W.H.) independently assessed the relevancy of search results and abstracted the data into a data extraction form. This form was used to record the demographic details of individual articles, including year of publication, study location, number of participants included, mean age of participants, percentage of male participants, type of dementia, recruitment site, number of participants with dementia or mild cognitive impairment (MCI), diagnostic criteria, cutoff values, sensitivity, specificity, and true-positive, false-positive, true-negative, and false-negative likelihood ratios. When a study reported results of sensitivity and specificity across different cutoff values of a screening test, only the results from a recommended cutoff by the authors of the article were selected. If the study did not have this recommendation, the cutoff used to summarize sensitivity and specificity in the abstract was chosen. When discrepancies were found regarding inclusion of studies or data extraction, the third investigator (K.K.F.T.) would make the definitive decision for study eligibility and data extraction.

Risk of Bias and Study QualityPotential risks of bias in each screening test were evaluated by the Quality Assessment of Diagnostic Accuracy Studies 2 instrument, which evaluated patient selection, execution of the index test and the reference standard, and flow of patients. All high risk of bias was counted in an Excel worksheet (Microsoft Inc) and presented as a percentage in each screening test. The quality of study was also assessed according to the methods section of the Standards for Reporting of Diagnostic Accuracy statement. An 8-point scale was designed for the evaluation of study quality, including description of the following: (1) study population, (2) participant recruitment, (3) sampling of participant selection, (4) data collection plan, (5) reference standard and its rationale, (6) technical specifications, (7) rationale for units and cutoffs, and (8) methods for calculating diagnostic accuracy with CIs.

This quality score was presented as median and range across the screening tests. Data Synthesis and Statistical AnalysisStatistical analyses were performed with the Metandi and Midas procedures in STATA statistical software, version 11 (StataCorp). The overall sensitivity and specificity of each diagnostic test were pooled using a bivariate random-effects model.

Forest plots were used to graphically present the combined sensitivity and specificity. The accuracy of a screening test had to allow trade-off between sensitivity and specificity that occurs when different threshold values were used to define positive and negative likelihood ratios of the tests.

Therefore, a diagnostic odds ratio was used as a single indicator of test performance. In addition, a hierarchical summary receiver-operating characteristic (HSROC) curve was generated to present the summary estimates of sensitivities and specificities along with 95% CIs and prediction region.

The area under the curve (AUC) for the HSROC was also calculated, and an area between 0.9 and 1.0 indicated that the diagnostic accuracy was good. When the Hessian matrix of bivariate approach was unstable or asymmetric, a random-effects model following the approach of DerSimonian and Laird was applied to estimate the pooled sensitivity and specificity, and a summary receiver-operating characteristic (SROC) curve was generated to present the summary estimates of sensitivities and specificities with an AUC for SROC presented as a summary statistic., Statistical heterogeneity among the trials was assessed by I 2, which describes the percentage of total variation across studies due to the heterogeneity rather than the chance alone. Literature Search and Study SelectionA total of 26 165 abstracts were identified from the databases, and 215 potential studies were further extracted from the bibliographies. All titles or abstracts were screened, and 346 articles were relevant to screening tools for dementia. One hundred ninety-seven were excluded for the following reasons: studies were systematic reviews (n = 30), studies did not fulfill inclusion criteria (n = 121), studies lacked data details for meta-analysis (n = 39), and studies reported results of screening tests without comparing to a criterion standard (n = 7).

Study CharacteristicsA total of 149 studies with more than 40 000 patients across the 11 screening tests were included. One hundred ten eligible studies (73.8%) reported the diagnostic performances of at least 2 screening tests, including those compared with the MMSE. Approximately 12 000 participants were confirmed as having dementia. Most studies (68.5%) used the MMSE as the screening test for dementia in 29 regions.

The next most common screening test studied was the MoCA, which was used in 20 studies (13.4%) from 9 countries. Patients were mainly recruited from community or clinic settings (80.3%). One hundred ten (73.8%) of 149 studies had good study quality with quality scores of 7 to 8. The quality scores were comparable across the 11 screening tests with median scores of approximately 7 (range, 3-8). The original data of each study on the true-positive, false-positive, false-negative, and true-negative likelihood ratios were presented (eTable 2 in the ). Furthermore, risks of bias were not identified among these studies, and only the studies for the GPCOG, MoCA and modified MMSE revealed approximately 20% to 30% high risks of bias on execution for the index test and the reference standard. Diagnostic Accuracy of the MMSEThere were 10 263 cases of dementia identified from 36 080 participants in 108 cohorts studying the MMSE.

The most common cutoff values to define participants with dementia were 23 and 24, used in 48 cohorts (44.4%). With different cutoff threshold values, we found considerable variation in the sensitivity and specificity estimates reported by individual studies. The sensitivities ranged from 0.25 to 1.00, and the specificities ranged from 0.54 to 1.00. The heterogeneity among studies was large, with I 2 statistics for sensitivity and specificity of 92% and 94%, respectively.

The diagnostic accuracy is summarized by meta-analysis. The combined data in the bivariate random-effects model gave a summary point with 0.81 sensitivity (95% CI, 0.78-0.84) and 0.89 specificity (95% CI, 0.87-0.91). The HSROC curve was plotted with a diagnostic odds ratio of 35.4, and the AUC was 92% (95% CI, 90%-94%) (eFigure 1 in the ).

Diagnostic Accuracy of Other Screening TestsThe performances of the other 10 screening tests were summarized by random-effects models. All tests presented with AUCs of at least 85%, and most of the tests had comparable performance to that of the MMSE.

The Mini-Cog test and the ACE-R were the best alternative tests. Among the studies with the Mini-Cog test, - the pooled sensitivity was 0.91 (95% CI, 0.80-0.96), and the pooled specificity was 0.86 (95% CI, 0.74-0.93) (A). The heterogeneity among studies was large, with I 2 statistics for sensitivity and specificity of 89% and 97%, respectively. Among studies that used the ACE-R, - the pooled sensitivity was 0.92 (95% CI, 0.90-0.94) and the pooled specificity was 0.89 (95% CI, 0.84-0.93) (B). The confidence regions of the HSROC curves for sensitivity and specificity of the Mini-Cog test and the ACE-R were plotted with reference to the HSROC curve of the MMSE (eFigure 2 in the ). Studies of the MMSEOnly the MMSE had a sufficient number of studies to perform subgroup analysis.

For the geographic regions, studies were conducted in Europe (44.4%), Americas (31.5%), and Asia (23.1%). The diagnostic performances of the MMSE were comparable across these regions with similar AUCs (eFigure 2 in the ). For the recruitment settings, participants were recruited in hospital (9.3%), clinic (32.4%), primary care (12.0%), community (38.9%), and other settings (7.4%). The diagnostic performances were comparable across different recruitments settings ( P.05 for all) (eTable 3 in the ).

Patients With MCIOnly 21 of 108 cohorts reported diagnostic performance of the MMSE for the detection of MCI. The combined data gave a summary point of 0.62 sensitivity (95% CI, 0.52-0.71) and 0.87 specificity (95% CI, 0.80-0.92). Nine of 20 studies reported diagnostic performance of the MoCA for the detection of MCI., - The combined data gave a summary point of 0.89 sensitivity (95% CI, 0.84-0.92) and 0.75 specificity (95% CI, 0.62-0.85) (C). The confidence regions of the HSROC curve for sensitivity and specificity of the MoCA were plotted with reference to the HSROC curve of the MMSE (eFigure 3 in the ).

DiscussionThis systematic review and meta-analysis included 149 studies that assessed the accuracy of the MMSE and 10 other screening tests for the detection of dementia. Compared with other screening tests, the Mini-Cog test and the ACE-R had better diagnostic performance for dementia, and the MoCA had better diagnostic performance for MCI. The Mini-Cog test is relatively simple and short compared with the MMSE.In a previous meta-analysis, Mitchell combined 34 diagnostic studies to evaluate the accuracy of the MMSE, but he only combined the sensitivity and specificity without mentioning the methodologic details.

Mitchell and Malladi, also published 2 meta-analyses that included 45 studies to compare diagnostic performance of single-domain and multidomain tests. They found that 15 brief single-domain tests were less accurate than that of the MMSE in detecting dementia in community and primary care settings. These studies used an uncommon approach of Bayesian curve modeling, instead of using the ROC curve to evaluate the diagnostic performance of the tests. A systematic review reported a combined diagnostic accuracy of the MMSE and summarized the sensitivity and specificity ranges of 10 other screening tests, but the literature search was limited to studies from systematic reviews conducted in primary care settings. In some other studies, dementia screening was performed in secondary or tertiary care settings. Therefore, the review combined only 14 studies with 10 185 participants using the MMSE as the screening test. The lack of a precise estimate of sensitivity has resulted in confusion among health care professionals to apply the MMSE for dementia screening.

In our meta-analysis, we tried to make our findings more comprehensive, using publications from all possible sources, and included 102 studies with 36 080 participants to evaluate the diagnostic performance of the MMSE. The results reported a sensitivity of 0.81 and a specificity of 0.89 for the MMSE. The diagnostic performance of MMSE is good because the AUC was 92%.Diagnostic sensitivity improves with lower cutoff values but with a corresponding decrease in specificity. High sensitivity corresponds to high negative predictive value and is the ideal to rule out dementia. We found considerable variation on the definitions of cutoff thresholds among the individual studies. According to our selection criteria, the most common cutoff scores for the MMSE for dementia were 23 and 24 (44.4% study cohorts), and approximately 20% of eligible cohorts used cutoff scores of 25 to 26 (range, 17-28). The range of scores for the Mini-Cog test is similarly 0 to 5, and 7 cohorts (77.8%) used a score of less than 3 as the cutoff for dementia, indicating disagreement on the optimal cutoff score across different screening tests.

The users of screening tests should strike a balance between sensitivity and specificity to rule in or out the participants with dementia according to the available resources.This study has several limitations. First, the screening tests were not directly compared in the same populations. Each study used different populations, and the inclusion criteria and prevalence of dementia varied. It would be preferable to directly compare screening tests using the same group of participants with similar educational levels. Second, only a few studies were included that showed head-to-head comparison between the screening tests, so the test performance could not be directly compared. Third, the screening tests were translated into different languages, which may have unknown effects on the results. We assumed that the tests were all validated in various languages in the individual studies although this was not guaranteed, and unidentified cultural effects on the use of screening tests may still exist.

Fourth, we only included studies that reported the diagnostic performance of screening tests for dementia. Although we used MCI as a secondary outcome, the definitions of MCI were heterogeneous across studies.

Studies that only reported the results of MCI or cognitive impairment but not dementia (cognitive impairment no dementia) were not included in this meta-analysis. Finally, some unpublished studies may not have been identified through the literature search in OVID databases, and publication bias may exist. ConclusionsThis review systematic and meta-analysis found that the MMSE is the most frequently studied test for dementia screening. However, many other screening tests have comparable diagnostic performance. The Mini-Cog test and the ACE-R had better performance than the other dementia screening tests.

The MoCA had better performance than the other MCI screening tests. Although the MMSE is a proprietary instrument for dementia screening, the other screening tests are comparably effective but easier to perform and freely available. Article InformationAccepted for Publication: April 8, 2015.Corresponding Author: Timothy C. Kwok, MD, PhD, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, 9/F, Clinical Sciences Building, Prince of Wales Hospital, Ngan Shing Street, Shatin, Hong Kong.Published Online: June 8, 2015.

BackgroundThe abolition of fixed retirement means that many people will work into their late 60s or even their early 70s. Older health care workers tend to suffer from the four Ds—drink, drugs, depression and dementia. Studies show negative correlations between performance on cognitive testing and job performance problems or with age. One study found cognitive impairment in doctors was responsible for 63% of all adverse medical events with most being preventable.Detection of cognitive impairment is essential in determining any risk to patient safety and to safeguard patients by designing and implementing effective remediation programmes. Dementia UK estimates that 1.3% of people aged 65–69 years have dementia rising to 2.9% for those aged 70–74 years.

Lesser degrees of cognitive impairment can be more common in people at these ages, increasing demand on occupational physicians to assess older workers for possible cognitive impairment(s). Mild cognitive impairment converts to dementia at a rate of 10% per year , a clinical challenge due to the variety and often dynamic nature of symptoms.There is need to determine whether cognitive impairment is present but also to establish which cognitive domains are affected in relation to skills and knowledge required by the person’s occupation. Screening must be effective, cost beneficial with suitable methods and therapeutic evidence. Patients may perform poorly on formal cognitive tests for other reasons, including acute illness, pain, lethargy, sleep deprivation, medication, depression, anxiety, not wishing to engage with testing, language barriers, cultural issues and learning disability. Hence these tests form part of the overall clinical assessment and clarity is needed as to the level of detail required for screening, differential diagnosis or detailed neuropsychological analysis. Brief historyThe original Addenbrooke’s Cognitive Examination (ACE) was developed in the Medical Research Council Cognition and Brain Sciences Unit in Cambridge in the late 1990s as a simple bedside test battery designed to detect mild dementia and differentiate Alzheimer’s disease from frontotemporal dementia. The diagnostic accuracy of ACE as a brief ‘bedside’ cognitive screening instrument led to its widespread adoption.

The original ACE included the mini-mental state examination (MMSE) or Folstein test, along with fronto-executive and extra visuospatial items. However, weaknesses were identified in the ACE, which prompted the development of the Addenbrooke’s Cognitive Examination-Revised (ACE-R) to facilitate cross-cultural usage and improve sensitivity. The original 26 components were combined to produce five subscores, each representing a specific cognitive domain: attention/orientation (18 points), memory (26 points), fluency (14 points), language (26 points) and visuospatial function (16 points)—100 in total. It gives a cut-off score for the five subdomains against controls and takes between 12 and 20min (average 16).

The ACE-R sensitivity to mild dementia (84–94% depending on cut-off point) is better than the MMSE. Three different alternative versions—A, B and C, with different stimuli for the name and address recall—prevent recalling from administration of previous tests. One cognitive domain that was not well covered by the ACE-R, but which is important in many occupations, is termed fluid intelligence, key to problem solving. There are tests of fluid intelligence, but these generally are the preserve of neuropsychologists. A review of the diagnostic accuracy of ACE and ACE-R found that ACE-R had somewhat superior diagnostic accuracy to the MMSE while ACE had less. Hence, the ACE-R was recommended in both moderate dementia (primary care and general hospital settings) and high dementia prevalence settings (memory clinics).

Cognitive Examination Example

Despite the wide use of ACE-R, the cognitive domains of the test have not been validated against standard neuropsychological tests.In light of weaknesses of certain domains in ACE-R, such as repetition, comprehension, visuospatial, items on the ACE-R were replaced to form the ACE-III. Failure on the verbal repetition item (‘no ifs, ands or buts’), for example, is often seen in healthy adults , which could be related to poor hearing or attention. Translation of this item is also known to be difficult. Measures of comprehension (such as the three-stage command and ‘close your eyes’) lack sensitivity to cognitive impairment as impaired individuals can often perform to normal limits. Spelling of the word ‘WORLD’ backwards is substituted with failure on serial 7s. These two items, however, correlate modestly and are known to differ in item difficulty. In light of these weaknesses, items on the ACE-R were replaced to form the ACE-III, which continues to be scored out of 100 and contain five cognitive domains but it is no longer possible to derive the MMSE score.

Brief Neuropsychological Screening

Comparison with other tests and previous versionsTesting shows that ACE-III cognitive domains correlate significantly with standardized neuropsychological tests used in the assessment of attention, language, verbal memory and visuospatial function. It also compared very favourably with its predecessor, the ACE-R, with similar levels of sensitivity and specificity and the two tests correlated significantly ( r = 0.99, P.