Diagnostic test accuracy of telehealth assessment for dementia and mild cognitive impairment

BACKGROUND

Many millions of people living with dementia around the world are not diagnosed, which has a negative impact both on their access to care and treatment and on rational service planning. Telehealth - the use of information and communication technology (ICT) to provide health services at a distance - may be a way to increase access to specialist assessment for people with suspected dementia, especially those living in remote or rural areas. It has also been much used during the COVID-19 pandemic. It is important to know whether diagnoses made using telehealth assessment are as accurate as those made in conventional, face-to-face clinical settings.

OBJECTIVES

Primary objective: to assess the diagnostic accuracy of telehealth assessment for dementia and mild cognitive impairment. Secondary objectives: to identify the quality and quantity of the relevant research evidence; to identify sources of heterogeneity in the test accuracy data; to identify and synthesise any data on patient or clinician satisfaction, resource use, costs or feasibility of the telehealth assessment models in the included studies.

SEARCH METHODS

We searched multiple databases and clinical trial registers on 4 November 2020 for published and 'grey' literature and registered trials. We applied no search filters and no language restrictions. We screened the retrieved citations in duplicate and assessed in duplicate the full texts of papers considered potentially relevant.

SELECTION CRITERIA

We included in the review cross-sectional studies with 10 or more participants who had been referred to a specialist service for assessment of a suspected cognitive disorder. Within a period of one month or less, each participant had to undergo two clinical assessments designed to diagnose dementia or mild cognitive impairment (MCI): a telehealth assessment (the index test) and a conventional face-to-face assessment (the reference standard). The telehealth assessment could be informed by some data collected face-to-face, e.g. by nurses working in primary care, but all contact between the patient and the specialist clinician responsible for synthesising the information and making the diagnosis had to take place remotely using ICT.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data from included studies. Data extracted covered study design, setting, participants, details of index test and reference standard, and results in the form of numbers of participants given diagnoses of dementia or MCI. Data were also sought on dementia subtype diagnoses and on quantitative measures of patient or clinician satisfaction, resource use, costs and feasibility. We assessed risk of bias and applicability of each included study using QUADAS-2. We entered the results into 2x2 tables in order to calculate the sensitivity and specificity of telehealth assessment for the diagnosis of all-cause dementia, MCI, and any cognitive syndrome (combining dementia and MCI). We presented the results of included studies narratively because there were too few studies to derive summary estimates of sensitivity and specificity.

MAIN RESULTS

Three studies with 136 participants were eligible for inclusion. Two studies (20 and 100 participants) took place in community settings in Australia and one study (16 participants) was conducted in veterans' homes in the USA. Participants were referred from primary care with undiagnosed cognitive symptoms or were identified as being at high risk of having dementia on a screening test in the care homes. Dementia and MCI were target conditions in the larger study; the other studies targeted dementia diagnosis only. Only one small study used a 'pure' telehealth model, i.e. not involving any elements of face-to-face assessment. The studies were generally well-conducted. We considered two studies to be at high risk of incorporation bias because a substantial amount of information collected face-to-face by nurses was used to inform both index test and reference standard assessments. One study was at unclear risk of selection bias. For the diagnosis of all-cause dementia, sensitivity of telehealth assessment ranged from 0.80 to 1.00 and specificity from 0.80 to 1.00. We considered this to be very low-certainty evidence due to imprecision, inconsistency between studies and risk of bias. For the diagnosis of MCI, data were available from only one study (100 participants) giving a sensitivity of 0.71 (95% CI 0.54 to 0.84) and a specificity of 0.73 (95% CI 0.60 to 0.84). We considered this to be low-certainty evidence due to imprecision and risk of bias. For diagnosis of any cognitive syndrome (dementia or MCI), data from the same study gave a sensitivity of 0.97 (95% CI 0.91 to 0.99) and a specificity of 0.22 (95% CI 0.03 to 0.60). The majority of diagnostic disagreements concerned the distinction between MCI and dementia, occurring approximately equally in either direction. There was also a tendency for patients identified as cognitively healthy at face-to-face assessment to be diagnosed with MCI at telehealth assessment (but numbers were small). There were insufficient data to make any assessment of the accuracy of dementia subtype diagnosis. One study provided a small amount of data indicating a good level of clinician and especially patient satisfaction with the telehealth model. There were no data on resource use, costs or feasibility.

AUTHORS' CONCLUSIONS

We found only very few eligible studies with a small number of participants. An important difference between the studies providing data for the analyses was whether the target condition was dementia only (two studies) or dementia and MCI (one study). The data suggest that telehealth assessment may be highly sensitive and specific for the diagnosis of all-cause dementia when assessed against a reference standard of conventional face-to-face assessment, but the estimates are imprecise due to small sample sizes and between-study heterogeneity, and may apply mainly to telehealth models which incorporate a considerable amount of face-to-face contact with healthcare professionals other than the doctor responsible for making the diagnosis. For the diagnosis of MCI by telehealth assessment, best estimates of both sensitivity and specificity were somewhat lower, but were based on a single study. Errors occurred at the cognitively healthy/MCI and the MCI/dementia boundaries. However, there is no evidence that diagnostic disagreements were more frequent than would be expected due to the known variation between clinicians' opinions when assigning a dementia diagnosis.

Non-pharmacological interventions for preventing delirium in hospitalised non-ICU patients

BACKGROUND

Delirium is an acute neuropsychological disorder that is common in hospitalised patients. It can be distressing to patients and carers and it is associated with serious adverse outcomes. Treatment options for established delirium are limited and so prevention of delirium is desirable. Non-pharmacological interventions are thought to be important in delirium prevention.  OBJECTIVES: To assess the effectiveness of non-pharmacological interventions designed to prevent delirium in hospitalised patients outside intensive care units (ICU).

SEARCH METHODS

We searched ALOIS, the specialised register of the Cochrane Dementia and Cognitive Improvement Group, with additional searches conducted in MEDLINE, Embase, PsycINFO, CINAHL, LILACS, Web of Science Core Collection, ClinicalTrials.gov and the World Health Organization Portal/ICTRP to 16 September 2020. There were no language or date restrictions applied to the electronic searches, and no methodological filters were used to restrict the search.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) of single and multicomponent non-pharmacological interventions for preventing delirium in hospitalised adults cared for outside intensive care or high dependency settings. We only included non-pharmacological interventions which were designed and implemented to prevent delirium.  DATA COLLECTION AND ANALYSIS: Two review authors independently examined titles and abstracts identified by the search for eligibility and extracted data from full-text articles. Any disagreements on eligibility and inclusion were resolved by consensus. We used standard Cochrane methodological procedures. The primary outcomes were: incidence of delirium; inpatient and later mortality; and new diagnosis of dementia. We included secondary and adverse outcomes as pre-specified in the review protocol. We used risk ratios (RRs) as measures of treatment effect for dichotomous outcomes and between-group mean differences for continuous outcomes. The certainty of the evidence was assessed using GRADE. A complementary exploratory analysis was undertaker using a Bayesian component network meta-analysis fixed-effect model to evaluate the comparative effectiveness of the individual components of multicomponent interventions and describe which components were most strongly associated with reducing the incidence of delirium.

MAIN RESULTS

We included 22 RCTs that recruited a total of 5718 adult participants. Fourteen trials compared a multicomponent delirium prevention intervention with usual care. Two trials compared liberal and restrictive blood transfusion thresholds. The remaining six trials each investigated a different non-pharmacological intervention. Incidence of delirium was reported in all studies.  Using the Cochrane risk of bias tool, we identified risks of bias in all included trials. All were at high risk of performance bias as participants and personnel were not blinded to the interventions. Nine trials were at high risk of detection bias due to lack of blinding of outcome assessors and three more were at unclear risk in this domain.  Pooled data showed that multi-component non-pharmacological interventions probably reduce the incidence of delirium compared to usual care (10.5% incidence in the intervention group, compared to 18.4% in the control group, risk ratio (RR) 0.57, 95% confidence interval (CI) 0.46 to 0.71, I2 = 39%; 14 studies; 3693 participants; moderate-certainty evidence, downgraded due to risk of bias).  There may be little or no effect of multicomponent interventions on inpatient mortality compared to usual care (5.2% in the intervention group, compared to 4.5% in the control group, RR 1.17, 95% CI 0.79 to 1.74, I2 = 15%; 10 studies; 2640 participants; low-certainty evidence downgraded due to inconsistency and imprecision).  No studies of multicomponent interventions reported data on new diagnoses of dementia.  Multicomponent interventions may result in a small reduction of around a day in the duration of a delirium episode (mean difference (MD) -0.93, 95% CI -2.01 to 0.14 days, I2 = 65%; 351 participants; low-certainty evidence downgraded due to risk of bias and imprecision). The evidence is very uncertain about the effect of multicomponent interventions on delirium severity (standardised mean difference (SMD) -0.49, 95% CI -1.13 to 0.14, I2=64%; 147 participants; very low-certainty evidence downgraded due to risk of bias and serious imprecision). Multicomponent interventions may result in a reduction in hospital length of stay compared to usual care (MD -1.30 days, 95% CI -2.56 to -0.04 days, I2=91%; 3351 participants; low-certainty evidence downgraded due to risk of bias and inconsistency), but little to no difference in new care home admission at the time of hospital discharge (RR 0.77, 95% CI 0.55 to 1.07; 536 participants; low-certainty evidence downgraded due to risk of bias and imprecision). Reporting of other adverse outcomes was limited.  Our exploratory component network meta-analysis found that re-orientation (including use of familiar objects), cognitive stimulation and sleep hygiene were associated with reduced risk of incident delirium. Attention to nutrition and hydration, oxygenation, medication review, assessment of mood and bowel and bladder care were probably associated with a reduction in incident delirium but estimates included the possibility of no benefit or harm.  Reducing sensory deprivation, identification of infection, mobilisation and pain control all had summary estimates that suggested potential increases in delirium incidence, but the uncertainty in the estimates was substantial.  Evidence from two trials suggests that use of a liberal transfusion threshold over a restrictive transfusion threshold probably results in little to no difference in incident delirium (RR 0.92, 95% CI 0.62 to 1.36; I2 = 9%; 294 participants; moderate-certainty evidence downgraded due to risk of bias).  Six other interventions were examined, but evidence for each was limited to single studies and we identified no evidence of delirium prevention.  AUTHORS' CONCLUSIONS: There is moderate-certainty evidence regarding the benefit of multicomponent non-pharmacological interventions for the prevention of delirium in hospitalised adults, estimated to reduce incidence by 43% compared to usual care. We found no evidence of an effect on mortality. There is emerging evidence that these interventions may reduce hospital length of stay, with a trend towards reduced delirium duration, although the effect on delirium severity remains uncertain. Further research should focus on implementation and detailed analysis of the components of the interventions to support more effective, tailored practice recommendations.

Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within a secondary care setting

BACKGROUND

The diagnosis of dementia relies on the presence of new-onset cognitive impairment affecting an individual's functioning and activities of daily living. The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) is a questionnaire instrument, completed by a suitable 'informant' who knows the patient well, designed to assess change in functional performance secondary to cognitive change; it is used as a tool for identifying those who may have dementia. In secondary care there are two specific instances where patients may be assessed for the presence of dementia. These are in the general acute hospital setting, where opportunistic screening may be undertaken, or in specialist memory services where individuals have been referred due to perceived cognitive problems. To ensure an instrument is suitable for diagnostic use in these settings, its test accuracy must be established.

OBJECTIVES

To determine the accuracy of the informant-based questionnaire IQCODE for detection of dementia in a secondary care setting.

SEARCH METHODS

We searched the following sources on the 28th of January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (Ovid SP), EMBASE (Ovid SP), PsycINFO (Ovid SP), BIOSIS Previews (Thomson Reuters Web of Science), Web of Science Core Collection (includes Conference Proceedings Citation Index) (Thomson Reuters Web of Science), CINAHL (EBSCOhost) and LILACS (BIREME). We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects - via the Cochrane Library); HTA Database (Health Technology Assessment Database via the Cochrane Library) and ARIF (Birmingham University). We also checked reference lists of relevant studies and reviews, used searches of known relevant studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel and included terms relating to cognitive tests, cognitive screening and dementia. We used standardised database subject headings such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate.

SELECTION CRITERIA

We selected those studies performed in secondary-care settings, which included (not necessarily exclusively) IQCODE to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. For the 'secondary care' setting we included all studies which assessed patients in hospital (e.g. acute unscheduled admissions, referrals to specialist geriatric assessment services etc.) and those referred for specialist 'memory' assessment, typically in psychogeriatric services.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by electronic database searches, and reviewed abstracts of all potentially relevant studies. Two independent assessors checked full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reporting quality using the STARD tool.

MAIN RESULTS

From 72 papers describing IQCODE test accuracy, we included 13 papers, representing data from 2745 individuals (n = 1413 (51%) with dementia). Pooled analysis of all studies using data presented closest to a cut-off of 3.3 indicated that sensitivity was 0.91 (95% CI 0.86 to 0.94); specificity 0.66 (95% CI 0.56 to 0.75); the positive likelihood ratio was 2.7 (95% CI 2.0 to 3.6) and the negative likelihood ratio was 0.14 (95% CI 0.09 to 0.22). There was a statistically significant difference in test accuracy between the general hospital setting and the specialist memory setting (P = 0.019), suggesting that IQCODE performs better in a 'general' setting. We found no significant differences in the test accuracy of the short (16-item) versus the 26-item IQCODE, or in the language of administration. There was significant heterogeneity in the included studies, including a highly varied prevalence of dementia (10.5% to 87.4%). Across the included papers there was substantial potential for bias, particularly around sampling of included participants and selection criteria, which may limit generalisability. There was also evidence of suboptimal reporting, particularly around disease severity and handling indeterminate results, which are important if considering use in clinical practice.

AUTHORS' CONCLUSIONS

The IQCODE can be used to identify older adults in the general hospital setting who are at risk of dementia and require specialist assessment; it is useful specifically for ruling out those without evidence of cognitive decline. The language of administration did not affect test accuracy, which supports the cross-cultural use of the tool. These findings are qualified by the significant heterogeneity, the potential for bias and suboptimal reporting found in the included studies.

Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within a general practice (primary care) setting

BACKGROUND

The IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly) is a commonly used questionnaire based tool that uses collateral information to assess for cognitive decline and dementia. Brief tools that can be used for dementia "screening" or "triage" may have particular utility in primary care / general practice healthcare settings but only if they have suitable test accuracy. A synthesis of the available data regarding IQCODE accuracy in a primary care setting should help inform cognitive assessment strategies for clinical practice; research and policy.

OBJECTIVES

To determine the accuracy of the informant-based questionnaire IQCODE, for detection of dementia in a primary care setting.

SEARCH METHODS

A search was performed in the following sources on the 28th of January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (Ovid SP), EMBASE (Ovid SP), PsycINFO (Ovid SP), BIOSIS (Ovid SP), ISI Web of Science and Conference Proceedings (ISI Web of Knowledge), CINHAL (EBSCOhost) and LILACs (BIREME). We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (York University); HTA Database (Health Technology Assessments Database via The Cochrane Library) and ARIF (Birmingham University). We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel and included terms relating to cognitive tests, cognitive screening and dementia. We used standardized database subject headings such as MeSH terms (in MEDLINE) and other standardized headings (controlled vocabulary) in other databases, as appropriate.

SELECTION CRITERIA

We selected those studies performed in primary care settings, which included (not necessarily exclusively) IQCODE to assess for the presence of dementia and where dementia diagnosis was confirmed with clinical assessment. For the "primary care" setting, we included those healthcare settings where unselected patients, present for initial, non-specialist assessment of memory or non-memory related symptoms; often with a view to onward referral for more definitive assessment.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by electronic database searches and abstracts of all potentially relevant studies were reviewed. Full papers were assessed for eligibility and data extracted by two independent assessors. Quality assessment (risk of bias and applicability) was determined using the QUADAS-2 tool. Reporting quality was determined using the STARDdem extension to the STARD tool.

MAIN RESULTS

From 71 papers describing IQCODE test accuracy, we included 1 paper, representing data from 230 individuals (n=16 [7%] with dementia). The paper described those patients consulting a primary care service who self-identified as Japanese-American. Dementia diagnosis was made using Benson & Cummings criteria and the IQCODE was recorded as part of a longer interview with the informant. IQCODE accuracy was assessed at various test thresholds, with a "trade-off" between sensitivity and specificity across these cutpoints. At an IQCODE threshold of 3.2 sensitivity: 100%, specificity: 76%; for IQCODE 3.7 sensitivity: 75%, specificity: 98%. Applying the QUADAS-2 assessments, the study was at high risk of bias in all categories. In particular degree of blinding was unclear and not all participants were included in the final analysis.

AUTHORS' CONCLUSIONS

It is not possible to give definitive guidance on the test accuracy of IQCODE for the diagnosis of dementia in a primary care setting based on the single study identified. We are surprised by the lack of research using the IQCODE in primary care as this is, arguably, the most appropriate setting for targeted case finding of those with undiagnosed dementia in order to maximise opportunities to intervene and provide support for the individual and their carers.

Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the detection of dementia within community dwelling populations

BACKGROUND

Various tools exist for initial assessment of possible dementia with no consensus on the optimal assessment method. Instruments that use collateral sources to assess change in cognitive function over time may have particular utility. The most commonly used informant dementia assessment is the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). A synthesis of the available data regarding IQCODE accuracy will help inform cognitive assessment strategies for clinical practice, research and policy.

OBJECTIVES

Our primary obective was to determine the accuracy of the informant-based questionnaire IQCODE for detection of dementia within community dwelling populations. Our secondary objective was to describe the effect of heterogeneity on the summary estimates. We were particularly interested in the traditional 26-item scale versus the 16-item short form; and language of administration. We explored the effect of varying the threshold IQCODE score used to define 'test positivity'.

SEARCH METHODS

We searched the following sources on 28 January 2013: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), BIOSIS Previews (ISI Web of Knowledge), Web of Science with Conference Proceedings (ISI Web of Knowledge), LILACS (BIREME). We also searched sources relevant or specific to diagnostic test accuracy: MEDION (Universities of Maastrict and Leuven); DARE (York University); ARIF (Birmingham University). We used sensitive search terms based on MeSH terms and other controlled vocabulary.

SELECTION CRITERIA

We selected those studies performed in community settings that used (not necessarily exclusively) the IQCODE to assess for presence of dementia and, where dementia diagnosis was confirmed with clinical assessment. Our intention with limiting the search to a 'community' setting was to include those studies closest to population level assessment. Within our predefined community inclusion criteria, there were relevant papers that fulfilled our definition of community dwelling but represented a selected population, for example stroke survivors. We included these studies but performed sensitivity analyses to assess the effects of these less representative populations on the summary results.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches and abstracts of all potentially relevant studies were reviewed. Full papers were assessed for eligibility and data extracted by two independent assessors. For quality assessment (risk of bias and applicability) we used the QUADAS 2 tool. We included test accuracy data on the IQCODE used at predefined diagnostic thresholds. Where data allowed, we performed meta-analyses to calculate summary values of sensitivity and specificity with corresponding 95% confidence intervals (CIs). We pre-specified analyses to describe the effect of IQCODE format (traditional or short form) and language of administration for the IQCODE.

MAIN RESULTS

From 16,144 citations, 71 papers described IQCODE test accuracy. We included 10 papers (11 independent datasets) representing data from 2644 individuals (n = 379 (14%) with dementia). Using IQCODE cut-offs commonly employed in clinical practice (3.3, 3.4, 3.5, 3.6) the sensitivity and specificity of IQCODE for diagnosis of dementia across the studies were generally above 75%. Taking an IQCODE threshold of 3.3 (or closest available) the sensitivity was 0.80 (95% CI 0.75 to 0.85); specificity was 0.84 (95% CI 0.78 to 0.90); positive likelihood ratio was 5.2 (95% CI 3.7 to 7.5) and the negative likelihood ratio was 0.23 (95% CI 0.19 to 0.29). Comparative analysis suggested no significant difference in the test accuracy of the 16 and 26-item IQCODE tests and no significant difference in test accuracy by language of administration. There was little difference in sensitivity across our predefined diagnostic cut-points. There was substantial heterogeneity in the included studies. Sensitivity analyses removing potentially unrepresentative populations in these studies made little difference to the pooled data estimates. The majority of included papers had potential for bias, particularly around participant selection and sampling. The quality of reporting was suboptimal particularly regarding timing of assessments and descriptors of reproducibility and inter-observer variability.

AUTHORS' CONCLUSIONS

Published data suggest that if using the IQCODE for community dwelling older adults, the 16 item IQCODE may be preferable to the traditional scale due to lesser test burden and no obvious difference in accuracy. Although IQCODE test accuracy is in a range that many would consider 'reasonable', in the context of community or population settings the use of the IQCODE alone would result in substantial misdiagnosis and false reassurance. Across the included studies there were issues with heterogeneity, several potential biases and suboptimal reporting quality.

Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early detection of dementia across a variety of healthcare settings

BACKGROUND

The Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) is a structured interview based on informant responses that is used to assess for possible dementia. IQCODE has been used for retrospective or contemporaneous assessment of cognitive decline. There is considerable interest in tests that may identify those at future risk of developing dementia. Assessing a population free of dementia for the prospective development of dementia is an approach often used in studies of dementia biomarkers. In theory, questionnaire-based assessments, such as IQCODE, could be used in a similar way, assessing for dementia that is diagnosed on a later (delayed) assessment.

OBJECTIVES

To determine the accuracy of the informant-based questionnaire IQCODE for the early detection of dementia across a variety of health care settings.

SEARCH METHODS

We searched these sources on 16 January 2016: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE Ovid SP, Embase Ovid SP, PsycINFO Ovid SP, BIOSIS Previews on Thomson Reuters Web of Science, Web of Science Core Collection (includes Conference Proceedings Citation Index) on Thomson Reuters Web of Science, CINAHL EBSCOhost, and LILACS BIREME. We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects, in the Cochrane Library); HTA Database (Health Technology Assessment Database, in the Cochrane Library), and ARIF (Birmingham University). We checked reference lists of included studies and reviews, used searches of included studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel, and included terms relating to cognitive tests, cognitive screening, and dementia. We used standardised database subject headings, such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate.

SELECTION CRITERIA

We selected studies that included a population free from dementia at baseline, who were assessed with the IQCODE and subsequently assessed for the development of dementia over time. The implication was that at the time of testing, the individual had a cognitive problem sufficient to result in an abnormal IQCODE score (defined by the study authors), but not yet meeting dementia diagnostic criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches, and reviewed abstracts of all potentially relevant studies. Two assessors independently checked the full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reported quality using the STARDdem tool.

MAIN RESULTS

From 85 papers describing IQCODE, we included three papers, representing data from 626 individuals. Of this total, 22% (N = 135/626) were excluded because of prevalent dementia. There was substantial attrition; 47% (N = 295) of the study population received reference standard assessment at first follow-up (three to six months) and 28% (N = 174) received reference standard assessment at final follow-up (one to three years). Prevalence of dementia ranged from 12% to 26% at first follow-up and 16% to 35% at final follow-up. The three studies were considered to be too heterogenous to combine, so we did not perform meta-analyses to describe summary estimates of interest. Included patients were poststroke (two papers) and hip fracture (one paper). The IQCODE was used at three thresholds of positivity (higher than 3.0, higher than 3.12 and higher than 3.3) to predict those at risk of a future diagnosis of dementia. Using a cut-off of 3.0, IQCODE had a sensitivity of 0.75 (95%CI 0.51 to 0.91) and a specificity of 0.46 (95%CI 0.34 to 0.59) at one year following stroke. Using a cut-off of 3.12, the IQCODE had a sensitivity of 0.80 (95%CI 0.44 to 0.97) and specificity of 0.53 (95C%CI 0.41 to 0.65) for the clinical diagnosis of dementia at six months after hip fracture. Using a cut-off of 3.3, the IQCODE had a sensitivity of 0.84 (95%CI 0.68 to 0.94) and a specificity of 0.87 (95%CI 0.76 to 0.94) for the clinical diagnosis of dementia at one year after stroke. In generaI, the IQCODE was sensitive for identification of those who would develop dementia, but lacked specificity. Methods for both excluding prevalent dementia at baseline and assessing for the development of dementia were varied, and had the potential to introduce bias.

AUTHORS' CONCLUSIONS

Included studies were heterogenous, recruited from specialist settings, and had potential biases. The studies identified did not allow us to make specific recommendations on the use of the IQCODE for the future detection of dementia in clinical practice. The included studies highlighted the challenges of delayed verification dementia research, with issues around prevalent dementia assessment, loss to follow-up over time, and test non-completion potentially limiting the studies. Future research should recognise these issues and have explicit protocols for dealing with them.

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.

The role of C-reactive protein as a prognostic marker in COVID-19

Background

C-reactive protein (CRP) is a non-specific acute phase reactant elevated in infection or inflammation. Higher levels indicate more severe infection and have been used as an indicator of COVID-19 disease severity. However, the evidence for CRP as a prognostic marker is yet to be determined. The aim of this study is to examine the CRP response in patients hospitalized with COVID-19 and to determine the utility of CRP on admission for predicting inpatient mortality.

Methods

Data were collected between 27 February and 10 June 2020, incorporating two cohorts: the COPE (COVID-19 in Older People) study of 1564 adult patients with a diagnosis of COVID-19 admitted to 11 hospital sites (test cohort) and a later validation cohort of 271 patients. Admission CRP was investigated, and finite mixture models were fit to assess the likely underlying distribution. Further, different prognostic thresholds of CRP were analysed in a time-to-mortality Cox regression to determine a cut-off. Bootstrapping was used to compare model performance [Harrell’s C statistic and Akaike information criterion (AIC)].

Results

The test and validation cohort distribution of CRP was not affected by age, and mixture models indicated a bimodal distribution. A threshold cut-off of CRP ≥40 mg/L performed well to predict mortality (and performed similarly to treating CRP as a linear variable).

Conclusions

The distributional characteristics of CRP indicated an optimal cut-off of ≥40 mg/L was associated with mortality. This threshold may assist clinicians in using CRP as an early trigger for enhanced observation, treatment decisions and advanced care planning.

Closing the UK care home data gap - methodological challenges and solutions

UK care home residents are invisible in national datasets. The COVID-19 pandemic has exposed data failings that have hindered service development and research for years. Fundamental gaps, in terms of population and service demographics coupled with difficulties identifying the population in routine data are a significant limitation. These challenges are a key factor underpinning the failure to provide timely and responsive policy decisions to support care homes. In this commentary we propose changes that could address this data gap, priorities include: (1) Reliable identification of care home residents and their tenure; (2) Common identifiers to facilitate linkage between data sources from different sectors; (3) Individual-level, anonymised data inclusive of mortality irrespective of where death occurs; (4) Investment in capacity for large-scale, anonymised linked data analysis within social care working in partnership with academics; (5) Recognition of the need for collaborative working to use novel data sources, working to understand their meaning and ensure correct interpretation; (6) Better integration of information governance, enabling safe access for legitimate analyses from all relevant sectors; (7) A core national dataset for care homes developed in collaboration with key stakeholders to support integrated care delivery, service planning, commissioning, policy and research. Our suggestions are immediately actionable with political will and investment. We should seize this opportunity to capitalise on the spotlight the pandemic has thrown on the vulnerable populations living in care homes to invest in data-informed approaches to support care, evidence-based policy making and research.

Anticholinergic burden (prognostic factor) for prediction of dementia or cognitive decline in older adults with no known cognitive syndrome

BACKGROUND

Medications with anticholinergic properties are commonly prescribed to older adults. The cumulative anticholinergic effect of all the medications a person takes is referred to as the 'anticholinergic burden' because of its potential to cause adverse effects. It is possible that high anticholinergic burden may be a risk factor for development of cognitive decline or dementia. There are various scales available to measure anticholinergic burden but agreement between them is often poor.

OBJECTIVES

To assess whether anticholinergic burden, as defined at the level of each individual scale, is a prognostic factor for future cognitive decline or dementia in cognitively unimpaired older adults.

SEARCH METHODS

We searched the following databases from inception to 24 March 2021: MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), CINAHL (EBSCOhost), and ISI Web of Science Core Collection (ISI Web of Science).

SELECTION CRITERIA

We included prospective and retrospective longitudinal cohort and case-control observational studies with a minimum of one year' follow-up that examined the association between an anticholinergic burden measurement scale and future cognitive decline or dementia in cognitively unimpaired older adults.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed studies for inclusion, and undertook data extraction, assessment of risk of bias, and GRADE assessment. We extracted odds ratios (OR) and hazard ratios, with 95% confidence intervals (CI), and linear data on the association between anticholinergic burden and cognitive decline or dementia. We intended to pool each metric separately; however, only OR-based data were suitable for pooling via a random-effects meta-analysis. We initially established adjusted and unadjusted pooled rates for each available anticholinergic scale; then, as an exploratory analysis, established pooled rates on the prespecified association across scales. We examined variability based on severity of anticholinergic burden.

MAIN RESULTS

We identified 25 studies that met our inclusion criteria (968,428 older adults). Twenty studies were conducted in the community care setting, two in primary care clinics, and three in secondary care settings. Eight studies (320,906 participants) provided suitable data for meta-analysis. The Anticholinergic Cognitive Burden scale (ACB scale) was the only scale with sufficient data for 'scale-based' meta-analysis. Unadjusted ORs suggested an increased risk for cognitive decline or dementia in older adults with an anticholinergic burden (OR 1.47, 95% CI 1.09 to 1.96) and adjusted ORs similarly suggested an increased risk for anticholinergic burden, defined according to the ACB scale (OR 2.63, 95% CI 1.09 to 6.29). Exploratory analysis combining adjusted ORs across available scales supported these results (OR 2.16, 95% CI 1.38 to 3.38), and there was evidence of variability in risk based on severity of anticholinergic burden (ACB scale 1: OR 2.18, 95% CI 1.11 to 4.29; ACB scale 2: OR 2.71, 95% CI 2.01 to 3.56; ACB scale 3: OR 3.27, 95% CI 1.41 to 7.61); however, overall GRADE evaluation of certainty of the evidence was low.

AUTHORS' CONCLUSIONS

There is low-certainty evidence that older adults without cognitive impairment who take medications with anticholinergic effects may be at increased risk of cognitive decline or dementia.

Patient-reported outcome measures (PROMs) use in post-stroke patient care and clinical practice: a realist synthesis protocol

BACKGROUND

There is growing interest in the use of routine patient-reported outcome measures (PROMs) to influence the care of individual patients with stroke. However, there are significant gaps in our understanding as to how PROMs influence post-stroke patient care and clinical practice. This is due to factors including the number of purported uses for PROMs and that PROMs are complex interventions, which attempt to stimulate varied actions or behaviours. Therefore, the objective of this realist synthesis is to offer theory-based explanations as to how PROMs influence post-stroke clinical practice and patient care.

METHODS

This is a protocol for a realist synthesis, which involves three distinct phases: theory building (phase 1), theory testing and refinement (phase 2) and synthesis (phase 3). Phase 1 will develop initial rough programme theories (IRPTs), through literature searches (from January 2000 onwards) of MEDLINE, EMBASE, PsycINFO, CINAHL, Cochrane Library and the grey literature. Only secondary sources will be included that contribute to the development of IRPTs. Only two IRPTs, prioritised by the stakeholder group, will be taken forward to be tested and refined during phase 2. Further novel searches will be employed in phase 2, utilising the same criteria as phase 1; however, phase 2 searches will not utilise grey literature searches, and only primary research studies that contribute to the refinement of programme theories under investigation will be included. Two independent reviewers will screen and select all returned results. The reviewers will code and annotate relevant sources, resulting in 'fragments' to be extracted and graded based on the richness of their contribution to explanation and causal insight. Further, these fragments will be organised into 'Context-Mechanism-Outcome' configurations. Phase 3 of the review will involve the synthesis of context-mechanism-outcome configurations to form middle-range theory-based explanations and developed logic models for stakeholders to understand how PROMs in post-stroke clinical practice and patient care work for whom, how and under what circumstances.

DISCUSSION

The resulting realist synthesis will provide guidance on the implementation of PROMs within routine post-stroke clinical practice and patient care and act as a touchstone for further testing and refinement of PROMs programmes.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020138649 .

36 Feasibility of Resistance Exercise to Failure at Different Loads in Frail and Healthy Older Adults?

Introduction

Resistance training (RT) is the most effective way to increase muscle mass and function in older adults both with/without sarcopenia/frailty. In younger adults, when RT is performed to muscle failure the load lifted does not mediate the magnitude of response, but there are no studies in older adults. We aimed to determine the feasibility of recruitment to a RT intervention working to muscle failure at different loads in frail and healthy older adults.

Methods

We performed an 8-week randomised feasibility trial of lower limb RT to volitional muscular failure, at high and low load. Participants were recruited via hospital outpatient clinics and newspaper advertisements. Outcomes included: frailty assessment (Fried criteria); muscle strength (maximum voluntary contraction/one-repetition maximum); functional abilities (Short Physical Performance Battery); safety/adverse events were recorded via a log, and patient experiences from focus groups.

Results

110 people were assessed for eligibility, and 58 randomised (frail n = 6, prefrail n = 20, robust n = 32) to either high (n = 30) or low load (n = 28) groups. Mean age of participants was 72 years (range 65–93), 36 were female, 22 male. Session attendance was 95% (high load) and 90.4% (low load). Most participants were recruited via advertisements. All participants reported feeling safe and reassured in the RT sessions. Two participants had a serious adverse event, one related to RT (hypotension) and several had adverse events (three intervention-related). Pain was reported at both loads (high n = 9, low n = 8) yet all completed. There were no differences (P > 0.05) in effects of RT outcome variables between low and high load groups.

Conclusion

In this feasibility trial the recruitment of frail patients via clinics was limited. Performing supervised RT to muscle failure in older adults was safe/acceptable and the load at which RT was performed did not influence its efficacy. Future research into the effectiveness of such RT is warranted.

Cholinesterase inhibitors for vascular dementia and other vascular cognitive impairments: a network meta-analysis

BACKGROUND

Vascular cognitive impairment (VCI) describes a broad spectrum of cognitive impairments caused by cerebrovascular disease, ranging from mild cognitive impairment to dementia. There are currently no pharmacological treatments recommended for improving either cognition or function in people with VCI. Three cholinesterase inhibitors (donepezil, galantamine, and rivastigmine) are licenced for the treatment of dementia due to Alzheimer's disease. They are thought to work by compensating for reduced cholinergic neurotransmission, which is also a feature of VCI. Through pairwise comparisons with placebo and a network meta-analysis, we sought to determine whether these medications are effective in VCI and whether there are differences between them with regard to efficacy or adverse events.

OBJECTIVES

(1) To assess the efficacy and safety of cholinesterase inhibitors in the treatment of adults with vascular dementia and other VCI. (2) To compare the effects of different cholinesterase inhibitors on cognition and adverse events, using network meta-analysis.

SEARCH METHODS

We searched ALOIS, the Cochrane Dementia and Cognitive Improvement Group's register, MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), CINAHL (EBSCOhost), Web of Science Core Collection (ISI Web of Science), LILACS (BIREME), ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform on 19 August 2020.

SELECTION CRITERIA

We included randomised controlled trials in which donepezil, galantamine, or rivastigmine was compared with placebo or in which the drugs were compared with each other in adults with vascular dementia or other VCI (excluding cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL)). We included all drug doses and routes of administration.

DATA COLLECTION AND ANALYSIS

Two review authors independently identified eligible trials, extracted data, assessed risk of bias, and applied the GRADE approach to assess the certainty of the evidence. The primary outcomes were cognition, clinical global impression, function (performance of activities of daily living), and adverse events. Secondary outcomes were serious adverse events, incidence of development of new dementia, behavioural disturbance, carer burden, institutionalisation, quality of life and death. For the pairwise analyses, we pooled outcome data at similar time points using random-effects methods. We also performed a network meta-analysis using Bayesian methods.

MAIN RESULTS

We included eight trials (4373 participants) in the review. Three trials studied donepezil 5 mg or 10 mg daily (n= 2193); three trials studied rivastigmine at a maximum daily dose of 3 to 12 mg (n= 800); and two trials studied galantamine at a maximum daily dose of 16 to 24 mg (n= 1380). The trials included participants with possible or probable vascular dementia or cognitive impairment following stroke. Mean ages were between 72.2 and 73.9 years. All of the trials were at low or unclear risk of bias in all domains, and the evidence ranged from very low to high level of certainty. For cognition, the results showed that donepezil 5 mg improves cognition slightly, although the size of the effect is unlikely to be clinically important (mean difference (MD) -0.92 Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) points (range 0 to 70), 95% confidence interval (CI) -1.44 to -0.40; high-certainty evidence). Donepezil 10 mg (MD -2.21 ADAS-Cog points, 95% CI -3.07 to -1.35; moderate-certainty evidence) and galantamine 16 to 24 mg (MD -2.01 ADAS-Cog point, 95%CI -3.18 to -0.85; moderate-certainty evidence) probably also improve cognition, although the larger effect estimates still may not be clinically important. With low certainty, there may be little to no effect of rivastigmine 3 to 12 mg daily on cognition (MD 0.03 ADAS-Cog points, 95% CI -3.04 to 3.10; low-certainty evidence). Adverse events reported in the studies included nausea and/or vomiting, diarrhoea, dizziness, headache, and hypertension. The results showed that there was probably little to no difference between donepezil 5 mg and placebo in the number of adverse events (odds ratio (OR) 1.22, 95% CI 0.94 to 1.58; moderate-certainty evidence), but there were slightly more adverse events with donepezil 10 mg than with placebo (OR 1.95, 95% CI 1.20 to 3.15; high-certainty evidence). The effect of rivastigmine 3 to 12 mg on adverse events was very uncertain (OR 3.21, 95% CI 0.36 to 28.88; very low-certainty evidence). Galantamine 16 to 24 mg is probably associated with a slight excess of adverse events over placebo (OR 1.57, 95% CI 1.02 to 2.43; moderate-certainty evidence). In the network meta-analysis (NMA), we included cognition to represent benefit, and adverse events to represent harm. All drugs ranked above placebo for cognition and below placebo for adverse events. We found donepezil 10 mg to rank first in terms of benefit, but third in terms of harms, when considering the network estimates and quality of evidence. Galantamine was ranked second in terms of both benefit and harm. Rivastigmine had the lowest ranking of the cholinesterase inhibitors in both benefit and harm NMA estimates, but this may reflect possibly inadequate doses received by some trial participants and small trial sample sizes.

AUTHORS' CONCLUSIONS

We found moderate- to high-certainty evidence that donepezil 5 mg, donepezil 10 mg, and galantamine have a slight beneficial effect on cognition in people with VCI, although the size of the change is unlikely to be clinically important. Donepezil 10 mg and galantamine 16 to 24 mg are probably associated with more adverse events than placebo. The evidence for rivastigmine was less certain. The data suggest that donepezil 10 mg has the greatest effect on cognition, but at the cost of adverse effects. The effect is modest, but in the absence of any other treatments, people living with VCI may still wish to consider the use of these agents. Further research into rivastigmine is needed, including the use of transdermal patches.

Plasma and cerebrospinal fluid ABeta42 for the differential diagnosis of Alzheimer's disease dementia in participants diagnosed with any dementia subtype in a specialist care setting

BACKGROUND

Dementia is a syndrome that comprises many differing pathologies, including Alzheimer's disease dementia (ADD), vascular dementia (VaD) and frontotemporal dementia (FTD). People may benefit from knowing the type of dementia they live with, as this could inform prognosis and may allow for tailored treatment. Beta-amyloid (1-42) (ABeta42) is a protein which decreases in both the plasma and cerebrospinal fluid (CSF) of people living with ADD, when compared to people with no dementia. However, it is not clear if changes in ABeta42 are specific to ADD or if they are also seen in other types of dementia. It is possible that ABeta42 could help differentiate ADD from other dementia subtypes.

OBJECTIVES

To determine the accuracy of plasma and CSF ABeta42 for distinguishing ADD from other dementia subtypes in people who meet the criteria for a dementia syndrome.

SEARCH METHODS

We searched MEDLINE, and nine other databases up to 18 February 2020. We checked reference lists of any relevant systematic reviews to identify additional studies.

SELECTION CRITERIA

We considered cross-sectional studies that differentiated people with ADD from other dementia subtypes. Eligible studies required measurement of participant plasma or CSF ABeta42 levels and clinical assessment for dementia subtype.

DATA COLLECTION AND ANALYSIS

Seven review authors working independently screened the titles and abstracts generated by the searches. We collected data on study characteristics and test accuracy. We used the second version of the 'Quality Assessment of Diagnostic Accuracy Studies' (QUADAS-2) tool to assess internal and external validity of results. We extracted data into 2 x 2 tables, cross-tabulating index test results (ABeta42) with the reference standard (diagnostic criteria for each dementia subtype). We performed meta-analyses using bivariate, random-effects models. We calculated pooled estimates of sensitivity, specificity, positive predictive values, positive and negative likelihood ratios, and corresponding 95% confidence intervals (CIs). In the primary analysis, we assessed accuracy of plasma or CSF ABeta42 for distinguishing ADD from other mixed dementia types (non-ADD). We then assessed accuracy of ABeta42 for differentiating ADD from specific dementia types: VaD, FTD, dementia with Lewy bodies (DLB), alcohol-related cognitive disorder (ARCD), Creutzfeldt-Jakob disease (CJD) and normal pressure hydrocephalus (NPH). To determine test-positive cases, we used the ABeta42 thresholds employed in the respective primary studies. We then performed sensitivity analyses restricted to those studies that used common thresholds for ABeta42.

MAIN RESULTS

We identified 39 studies (5000 participants) that used CSF ABeta42 levels to differentiate ADD from other subtypes of dementia. No studies of plasma ABeta42 met the inclusion criteria. No studies were rated as low risk of bias across all QUADAS-2 domains. High risk of bias was found predominantly in the domains of patient selection (28 studies) and index test (25 studies). The pooled estimates for differentiating ADD from other dementia subtypes were as follows: ADD from non-ADD: sensitivity 79% (95% CI 0.73 to 0.85), specificity 60% (95% CI 0.52 to 0.67), 13 studies, 1704 participants, 880 participants with ADD; ADD from VaD: sensitivity 79% (95% CI 0.75 to 0.83), specificity 69% (95% CI 0.55 to 0.81), 11 studies, 1151 participants, 941 participants with ADD; ADD from FTD: sensitivity 85% (95% CI 0.79 to 0.89), specificity 72% (95% CI 0.55 to 0.84), 17 studies, 1948 participants, 1371 participants with ADD; ADD from DLB: sensitivity 76% (95% CI 0.69 to 0.82), specificity 67% (95% CI 0.52 to 0.79), nine studies, 1929 participants, 1521 participants with ADD. Across all dementia subtypes, sensitivity was greater than specificity, and the balance of sensitivity and specificity was dependent on the threshold used to define test positivity.

AUTHORS' CONCLUSIONS

Our review indicates that measuring ABeta42 levels in CSF may help differentiate ADD from other dementia subtypes, but the test is imperfect and tends to misdiagnose those with non-ADD as having ADD. We would caution against the use of CSF ABeta42 alone for dementia classification. However, ABeta42 may have value as an adjunct to a full clinical assessment, to aid dementia diagnosis.

Increased care at discharge from COVID-19: The association between pre-admission frailty and increased care needs after hospital discharge; a multicentre European observational cohort study

BACKGROUND

The COVID-19 pandemic has placed significant pressure on health and social care. Survivors of COVID-19 may be left with substantial functional deficits requiring ongoing care. We aimed to determine whether pre-admission frailty was associated with increased care needs at discharge for patients admitted to hospital with COVID-19.

METHODS

Patients were included if aged over 18 years old and admitted to hospital with COVID-19 between 27 February and 10 June 2020. The Clinical Frailty Scale (CFS) was used to assess pre-admission frailty status. Admission and discharge care levels were recorded. Data were analysed using a mixed-effects logistic regression adjusted for age, sex, smoking status, comorbidities, and admission CRP as a marker of severity of disease.

RESULTS

Thirteen hospitals included patients: 1671 patients were screened, and 840 were excluded including, 521 patients who died before discharge (31.1%). Of the 831 patients who were discharged, the median age was 71 years (IQR, 58-81 years) and 369 (44.4%) were women. The median length of hospital stay was 12 days (IQR 6-24). Using the CFS, 438 (47.0%) were living with frailty (≥ CFS 5), and 193 (23.2%) required an increase in the level of care provided. Multivariable analysis showed that frailty was associated with an increase in care needs compared to patients without frailty (CFS 1-3). The adjusted odds ratios (aOR) were as follows: CFS 4, 1.99 (0.97-4.11); CFS 5, 3.77 (1.94-7.32); CFS 6, 4.04 (2.09-7.82); CFS 7, 2.16 (1.12-4.20); and CFS 8, 3.19 (1.06-9.56).

CONCLUSIONS

Around a quarter of patients admitted with COVID-19 had increased care needs at discharge. Pre-admission frailty was strongly associated with the need for an increased level of care at discharge. Our results have implications for service planning and public health policy as well as a person's functional outcome, suggesting that frailty screening should be utilised for predictive modelling and early individualised discharge planning.

Informant-based screening tools for diagnosis of dementia, an overview of systematic reviews of test accuracy studies protocol

BACKGROUND

Robust diagnosis of dementia requires an understanding of the accuracy of the available diagnostic tests. Informant questionnaires are frequently used to assess for dementia in clinical practice. Recent systematic reviews have sought to establish the diagnostic test accuracy of various dementia informant screening tools. However, most reviews to date have focused on a single diagnostic tool and this does not address which tool is 'best'. A key aim of the overview of systematic reviews is to present a disparate evidence base in a single, easy to access platform.

METHODS

We will conduct an overview of systematic reviews in which we 'review the systematic reviews' of diagnostic test accuracy studies evaluating informant questionnaires for dementia. As an overview of systematic reviews of test accuracy is a relatively novel approach, we will use this review to explore methods for visual representation of complex data, for highlighting evidence gaps and for indirect comparative analyses. We will create a list of informant tools by consulting with dementia experts. We will search 6 databases (EMBASE (OVID); Health and Psychosocial Instruments (OVID); Medline (OVID); CINAHL (EBSCO); PSYCHinfo (EBSCO) and the PROSPERO registry of review protocols) to identify systematic reviews that describe the diagnostic test accuracy of informant questionnaires for dementia. We will assess review quality using the AMSTAR-2 (Assessment of Multiple Systematic Reviews) and assess reporting quality using PRISMA-DTA (Preferred Reporting Items for Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies) checklists. We will collate the identified reviews to create an 'evidence map' that highlights where evidence does and does not exist in relation to informant questionnaires. We will pool sensitivity and specificity data via meta-analysis to generate a diagnostic test accuracy summary statistic for each informant questionnaire. If data allow, we will perform a statistical comparison of the diagnostic test accuracy of each informant questionnaire using a network approach.

DISCUSSION

Our overview of systematic reviews will provide a concise summary of the diagnostic test accuracy of informant tools and highlight areas where evidence is currently lacking in this regard. It will also apply network meta-analysis techniques to a new area.

Nosocomial COVID-19 infection: examining the risk of mortality. The COPE-Nosocomial Study (COVID in Older PEople)

Background

Hospital admissions for non-coronavirus disease 2019 (COVID-19) pathology have decreased significantly. It is believed that this may be due to public anxiety about acquiring COVID-19 infection in hospital and the subsequent risk of mortality.

Aim

To identify patients who acquire COVID-19 in hospital (nosocomial COVID-19 infection (NC)) and their risk of mortality compared to those with community-acquired COVID-19 (CAC) infection.

Methods

The COPE-Nosocomial Study was an observational cohort study. The primary outcome was the time to all-cause mortality (estimated with an adjusted hazard ratio (aHR)), and secondary outcomes were day 7 mortality and the time-to-discharge. A mixed-effects multivariable Cox's proportional hazards model was used, adjusted for demographics and comorbidities.

Findings

The study included 1564 patients from 10 hospital sites throughout the UK, and one in Italy, and collected outcomes on patients admitted up to April 28^th, 2020. In all, 12.5% of COVID-19 infections were acquired in hospital; 425 (27.2%) patients with COVID died. The median survival time in NC patients was 14 days compared with 10 days in CAC patients. In the primary analysis, NC infection was associated with lower mortality rate (aHR: 0.71; 95% confidence interval (CI): 0.51–0.98). Secondary outcomes found no difference in day 7 mortality (adjusted odds ratio: 0.79; 95% CI: 0.47–1.31), but NC patients required longer time in hospital during convalescence (aHR: 0.49, 95% CI: 0.37–0.66).

Conclusion

The minority of COVID-19 cases were the result of NC transmission. No COVID-19 infection comes without risk, but patients with NC had a lower risk of mortality compared to CAC infection; however, caution should be taken when interpreting this finding.

Aspirin and other non-steroidal anti-inflammatory drugs for the prevention of dementia

BACKGROUND

Dementia is a worldwide concern. Its global prevalence is increasing. At present, there is no medication licensed to prevent or delay the onset of dementia. Inflammation has been suggested as a key factor in dementia pathogenesis. Therefore, medications with anti-inflammatory properties could be beneficial for dementia prevention.

OBJECTIVES

To evaluate the effectiveness and adverse effects of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) for the primary or secondary prevention of dementia.

SEARCH METHODS

We searched ALOIS, the specialised register of the Cochrane Dementia and Cognitive Improvement Group up to 9 January 2020. ALOIS contains records of clinical trials identified from monthly searches of several major healthcare databases, trial registries and grey literature sources. We ran additional searches across MEDLINE (OvidSP), Embase (OvidSP) and six other databases to ensure that the searches were as comprehensive and up-to-date as possible. We also reviewed citations of reference lists of included studies.

SELECTION CRITERIA

We searched for randomised controlled trials (RCTs) and controlled clinical trials (CCTs) comparing aspirin or other NSAIDs with placebo for the primary or secondary prevention of dementia. We included trials with cognitively healthy participants (primary prevention) or participants with mild cognitive impairment (MCI) or cognitive complaints (secondary prevention).

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures according to the Cochrane Handbook for Systematic Reviews of Interventions. We rated the strength of evidence for each outcome using the GRADE approach.

MAIN RESULTS

We included four RCTs with 23,187 participants. Because of the diversity of these trials, we did not combine data to give summary estimates, but presented a narrative description of the evidence. We identified one trial (19,114 participants) comparing low-dose aspirin (100 mg once daily) to placebo. Participants were aged 70 years or older with no history of dementia, cardiovascular disease or physical disability. Interim analysis indicated no significant treatment effect and the trial was terminated slightly early after a median of 4.7 years' follow-up. There was no evidence of a difference in incidence of dementia between aspirin and placebo groups (risk ratio (RR) 0.98, 95% CI 0.83 to 1.15; high-certainty evidence). Participants allocated aspirin had higher rates of major bleeding (RR 1.37, 95% CI 1.17 to 1.60, high-certainty evidence) and slightly higher mortality (RR 1.14, 95% CI 1.01 to 1.28; high-certainty evidence). There was no evidence of a difference in activities of daily living between groups (RR 0.84, 95% CI 0.70 to 1.02; high-certainty evidence). We identified three trials comparing non-aspirin NSAIDs to placebo. All three trials were terminated early due to adverse events associated with NSAIDs reported in other trials. One trial (2528 participants) investigated the cyclo-oxygenase-2 (COX-2) inhibitor celecoxib (200 mg twice daily) and the non-selective NSAID naproxen (220 mg twice daily) for preventing dementia in cognitively healthy older adults with a family history of Alzheimer's disease (AD). Median follow-up was 734 days. Combining both NSAID treatment arms, there was no evidence of a difference in the incidence of AD between participants allocated NSAIDs and those allocated placebo (RR 1.91, 95% CI 0.89 to 4.10; moderate-certainty evidence). There was also no evidence of a difference in rates of myocardial infarction (RR 1.21, 95% CI 0.61 to 2.40), stroke (RR 1.82, 95% CI 0.76 to 4.37) or mortality (RR 1.37, 95% CI 0.78 to 2.43) between treatment groups (all moderate-certainty evidence). One trial (88 participants) assessed the effectiveness of celecoxib (200 mg or 400 mg daily) in delaying cognitive decline in participants aged 40 to 81 years with mild age-related memory loss but normal memory performance scores. Mean duration of follow-up was 17.6 months in the celecoxib group and 18.1 months in the placebo group. There was no evidence of a difference between groups in test scores in any of six cognitive domains. Participants allocated celecoxib experienced more gastrointestinal adverse events than those allocated placebo (RR 2.66, 95% CI 1.05 to 6.75; low-certainty evidence). One trial (1457 participants) assessed the effectiveness of the COX-2 inhibitor rofecoxib (25 mg once daily) in delaying or preventing a diagnosis of AD in participants with MCI. Median duration of study participation was 115 weeks in the rofecoxib group and 130 weeks in the placebo group. There was a higher incidence of AD in the rofecoxib than the placebo group (RR 1.32, 95% CI 1.01 to 1.72; moderate-certainty evidence). There was no evidence of a difference between groups in cardiovascular adverse events (RR 1.07, 95% CI 0.68 to 1.66; moderate-certainty evidence) or mortality (RR 1.62, 95% CI 0.85 to 3.05; moderate-certainty evidence). Participants allocated rofecoxib had more upper gastrointestinal adverse events (RR 3.53, 95% CI 1.17 to 10.68; moderate-certainty evidence). Reported annual mean difference scores showed no evidence of a difference between groups in activities of daily living (year 1: no data available; year 2: 0.0, 95% CI -0.1 to 0.2; year 3: 0.1, 95% CI -0.1 to 0.3; year 4: 0.1, 95% CI -0.1 to 0.4; moderate-certainty evidence).

AUTHORS' CONCLUSIONS

There is no evidence to support the use of low-dose aspirin or other NSAIDs of any class (celecoxib, rofecoxib or naproxen) for the prevention of dementia, but there was evidence of harm. Although there were limitations in the available evidence, it seems unlikely that there is any need for further trials of low-dose aspirin for dementia prevention. If future studies of NSAIDs for dementia prevention are planned, they will need to be cognisant of the safety concerns arising from the existing studies.

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.

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.

Cholinesterase inhibitors for vascular dementia and other vascular cognitive impairments: a network meta‐analysis

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the benefits and harms of each cholinesterase inhibitor in the treatment of adults with VCI To compare cholinesterase inhibitors for efficacy and safety in people with VCI