Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations

BACKGROUND: The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia. OBJECTIVES: To determine the diagnostic accuracy of the Mini‐Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia. SEARCH METHODS: We searched the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), LILACS (BIREME), ALOIS, BIOSIS previews (Thomson Reuters Web of Science), and Web of Science Core Collection, including the Science Citation Index and the Conference Proceedings Citation Index (Thomson Reuters Web of Science). We also searched specialised sources of diagnostic test accuracy studies and reviews: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). We attempted to locate possibly relevant but unpublished data by contacting researchers in this field. We first performed the searches in November 2012 and then fully updated them in May 2014. We did not apply any language or date restrictions to the electronic searches, and we did not use any methodological filters as a method to restrict the search overall. SELECTION CRITERIA: We included studies that compared the 11‐item (maximum score 30) MMSE test (at any cut point) in people who had not undergone prior testing versus a commonly accepted clinical reference standard for all‐cause dementia and subtypes (Alzheimer disease dementia, Lewy body dementia, vascular dementia, frontotemporal dementia). Clinical diagnosis included all‐cause (unspecified) dementia, as defined by any version of the Diagnostic and Statistical Manual of Mental Disorders (DSM); International Classification of Diseases (ICD) and the Clinical Dementia Rating. DATA COLLECTION AND ANALYSIS: At least three authors screened all citations.Two authors handled data extraction and quality assessment. We performed meta‐analysis using the hierarchical summary receiver‐operator curves (HSROC) method and the bivariate method. MAIN RESULTS: We retrieved 24,310 citations after removal of duplicates. We reviewed the full text of 317 full‐text articles and finally included 70 records, referring to 48 studies, in our synthesis. We were able to perform meta‐analysis on 28 studies in the community setting (44 articles) and on 6 studies in primary care (8 articles), but we could not extract usable 2 x 2 data for the remaining 14 community studies, which we did not include in the meta‐analysis. All of the studies in the community were in asymptomatic people, whereas two of the six studies in primary care were conducted in people who had symptoms of possible dementia. We judged two studies to be at high risk of bias in the patient selection domain, three studies to be at high risk of bias in the index test domain and nine studies to be at high risk of bias regarding flow and timing. We assessed most studies as being applicable to the review question though we had concerns about selection of participants in six studies and target condition in one study. The accuracy of the MMSE for diagnosing dementia was reported at 18 cut points in the community (MMSE score 10, 14‐30 inclusive) and 10 cut points in primary care (MMSE score 17‐26 inclusive). The total number of participants in studies included in the meta‐analyses ranged from 37 to 2727, median 314 (interquartile range (IQR) 160 to 647). In the community, the pooled accuracy at a cut point of 24 (15 studies) was sensitivity 0.85 (95% confidence interval (CI) 0.74 to 0.92), specificity 0.90 (95% CI 0.82 to 0.95); at a cut point of 25 (10 studies), sensitivity 0.87 (95% CI 0.78 to 0.93), specificity 0.82 (95% CI 0.65 to 0.92); and in seven studies that adjusted accuracy estimates for level of education, sensitivity 0.97 (95% CI 0.83 to 1.00), specificity 0.70 (95% CI 0.50 to 0.85). There was insufficient data to evaluate the accuracy of the MMSE for diagnosing dementia subtypes.We could not estimate summary diagnostic accuracy in primary care due to insufficient data. AUTHORS' CONCLUSIONS: The MMSE contributes to a diagnosis of dementia in low prevalence settings, but should not be used in isolation to confirm or exclude disease. We recommend that future work evaluates the diagnostic accuracy of tests in the context of the diagnostic pathway experienced by the patient and that investigators report how undergoing the MMSE changes patient‐relevant outcomes

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Enhancing the quality of open data

This paper looks at some of the quality issues relating to open data. This is problematic because of an open-data specific paradox: most metrics of quality are user-relative, but open data are aimed at no specific user and are simply available online under an open licence, so there is no user to be relevant to. Nevertheless, it is argued that opening data to scrutiny can improve quality by building feedback into the data production process, although much depends on the context of publication. The paper discusses various heuristics for addressing quality, and also looks at institutional approaches. Furthermore, if the open data can be published in linkable or bookmarkable form using Semantic Web technologies, that will provide further mechanisms to improve qualit

Single fluorescence probes along the reactive center loop reveal site-specific changes during the latency transition of PAI-1

The serine protease inhibitor (serpin), plasminogen activator inhibitor‐1 (PAI‐1), is an important biomarker for cardiovascular disease and many cancers. It is therefore a desirable target for pharmaceutical intervention. However, to date, no PAI‐1 inhibitor has successfully reached clinical trial, indicating the necessity to learn more about the mechanics of the serpin. Although its kinetics of inhibition have been extensively studied, less is known about the latency transition of PAI‐1, in which the solvent‐exposed reactive center loop (RCL) inserts into its central β‐sheet, rendering the inhibitor inactive. This spontaneous transition is concomitant with a large translocation of the RCL, but no change in covalent structure. Here, we conjugated the fluorescent probe, NBD, to single positions along the RCL (P13‐P5′) to detect changes in solvent exposure that occur during the latency transition. The results support a mousetrap‐like RCL‐insertion that occurs with a half‐life of 1–2 h in accordance with previous reports. Importantly, this study exposes unique transitions during latency that occur with a half‐life of ∼5 and 25 min at the P5′ and P8 RCL positions, respectively. We hypothesize that the process detected at P5′ represents s1C detachment, while that at P8 results from a steric barrier to RCL insertion. Together, these findings provide new insights by characterizing multiple steps in the latency transition