In older adults, specialty geriatrics care, multicomponent interventions, and cognitive stimulation reduce nursing home admission.

SOURCE CITATION: Gaugler JE, Zmora R, Peterson CM, et al. What interventions keep older people out of nursing homes? A systematic review and meta-analysis. J Am Geriatr Soc. 2023;71:3609-3621. 37526432.

Frailty in stroke.

Stroke is predominantly a condition of older age. So, it seems sensible that specialists working in stroke services should understand the primary clinical syndrome of ageing-frailty. Recent studies have highlighted the prevalence of frailty in stroke and its associated poor outcomes, yet frailty does not feature prominently in stroke research, practice or policy. Frailty-informed stroke care may differ from the interventional management that dominates contemporary practice. However, this is not therapeutic nihilism. A person-centred approach ensures that every care decision is appropriate and based on a shared understanding of the person's goals and likely prognosis. We present a primer on frailty in stroke, describing definition(s), epidemiology and prognostic implications. We discuss the challenges surrounding assessment and management of frailty in stroke units and offer practical guidance suitable for the stroke clinician.

A systematic review of frailty assessment tools used in vascular surgery research.

OBJECTIVE: Frailty is common in vascular patients and is recognized for its prognostic value. In the absence of consensus, a multitude of frailty assessment tools exist. This systematic review aimed to quantify the variety in these tools and describe their content and application to inform future research and clinical practice. METHODS: Multiple cross-disciplinary electronic literature databases were searched from inception to August 2022. Studies describing frailty assessment in a vascular surgical population were eligible. Data extraction to a validated template included patient demographics, tool content, and analysis methods. A secondary systematic search for papers describing the psychometric properties of commonly used frailty tools was then performed. RESULTS: Screening 5358 records identified 111 eligible studies, with an aggregate population of 5,418,236 patients. Forty-three differing frailty assessment tools were identified. One-third of these failed to assess frailty as a multidomain deficit and there was a reliance on assessing function and presence of comorbidity. Substantial methodological variability in data analysis and lack of methodological description was also identified. Published psychometric assessment was available for only 4 of the 10 most commonly used frailty tools. The Clinical Frailty Scale was the most studied and demonstrates good psychometric properties within a surgical population. CONCLUSIONS: Substantial heterogeneity in frailty assessment is demonstrated, precluding meaningful comparisons of services and data pooling. A uniform approach to assessment is required to guide future frailty research. Based on the literature, we make the following recommendations: frailty should be considered a continuous construct and the reporting of frailty tools' application needs standardized. In the absence of consensus, the Clinical Frailty Scale is a validated tool with good psychometric properties that demonstrates usefulness in vascular surgery.

MetaBayesDTA: codeless Bayesian meta-analysis of test accuracy, with or without a gold standard.

BACKGROUND: The statistical models developed for meta-analysis of diagnostic test accuracy studies require specialised knowledge to implement. This is especially true since recent guidelines, such as those in Version 2 of the Cochrane Handbook of Systematic Reviews of Diagnostic Test Accuracy, advocate more sophisticated methods than previously. This paper describes a web-based application - MetaBayesDTA - that makes many advanced analysis methods in this area more accessible. RESULTS: We created the app using R, the Shiny package and Stan. It allows for a broad array of analyses based on the bivariate model including extensions for subgroup analysis, meta-regression and comparative test accuracy evaluation. It also conducts analyses not assuming a perfect reference standard, including allowing for the use of different reference tests. CONCLUSIONS: Due to its user-friendliness and broad array of features, MetaBayesDTA should appeal to researchers with varying levels of expertise. We anticipate that the application will encourage higher levels of uptake of more advanced methods, which ultimately should improve the quality of test accuracy reviews.

Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) for the diagnosis of delirium in adults in critical care settings.

BACKGROUND: Delirium is an underdiagnosed clinical syndrome typified by an acute alteration of mental state. It is an important problem in critical care and intensive care units (ICU) due to its high prevalence and its association with adverse outcomes. Delirium is a very distressing condition for patients, with a huge impact on their well-being. Diagnosis of delirium in the critical care setting is challenging. This is especially true for patients who are mechanically ventilated and are therefore unable to engage in a verbal interview. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is a tool specifically designed to assess for delirium in the context of ICU patients, including those on mechanical ventilation. CAM-ICU can be administered by non-specialists to give a dichotomous delirium present/absent result. OBJECTIVES: To determine the diagnostic accuracy of the CAM-ICU for the diagnosis of delirium in adult patients in critical care units. SEARCH METHODS: We searched MEDLINE (Ovid SP, 1946 to 8 July 2022), Embase (Ovid SP, 1982 to 8 July 2022), Web of Science Core Collection (ISI Web of Knowledge, 1945 to 8 July 2022), PsycINFO (Ovid SP, 1806 to 8 July 2022), and LILACS (BIREME, 1982 to 8 July 2022). We checked the reference lists of included studies and other resources for additional potentially relevant studies. We also searched the Health Technology Assessment database, the Cochrane Library, Aggressive Research Intelligence Facility database, WHO ICTRP, ClinicalTrials.gov, and websites of scientific associations to access any annual meetings and abstracts of conference proceedings in the field. SELECTION CRITERIA: We included diagnostic studies enrolling adult ICU patients assessed using the CAM-ICU tool, regardless of language or publication status and reporting sufficient data on delirium diagnosis for the construction of 2 x 2 tables. Eligible studies evaluated the diagnostic performance of the CAM-ICU versus a clinical reference standard based on any iteration of the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria applied by a clinical expert. DATA COLLECTION AND ANALYSIS: Two review authors independently selected and collated study data. We assessed the methodological quality of studies using the QUADAS-2 tool. We used two univariate fixed-effect or random-effects models to determine summary estimates of sensitivity and specificity. We performed sensitivity analyses that excluded studies considered to be at high risk of bias and high concerns in applicability, due mainly to the target population included (e.g. patients with traumatic brain injury). We also investigated potential sources of heterogeneity, assessing the effect of reference standard diagnosis and proportion of patients ventilated. MAIN RESULTS: We included 25 studies (2817 participants). The mean age of participants ranged from 48 to 69 years; 15 of the studies included critical care units admitting mixed populations (e.g. medical, trauma, surgery patients). The percentage of patients receiving mechanical ventilation ranged from 11.8% to 100%. The prevalence of delirium in the studies included ranged from 12.5% to 83.9%. Presence of delirium was determined by the application of DSM-IV criteria in 13 out of 25 included studies. We assessed 13 studies as at low risk of bias and low applicability concerns for all QUADAS-2 domains. The most common issue of concern was flow and timing of the tests, followed by patient selection. Overall, we estimated a pooled sensitivity of 0.78 (95% confidence interval (CI) 0.72 to 0.83) and a pooled specificity of 0.95 (95% CI 0.92 to 0.97). Sensitivity analysis restricted to studies at low risk of bias and without any applicability concerns (n = 13 studies) gave similar summary accuracy indices (sensitivity 0.80 (95% CI 0.72 to 0.86), specificity 0.95 (95% CI 0.93 to 0.97)). Subgroup analyses based on diagnostic assessment found summary estimates of sensitivity and specificity for studies using DSM-IV of 0.79 (95% CI 0.72 to 0.85) and 0.94 (95% CI 0.90 to 0.96). For studies that used DSM-5 criteria, summary estimates of sensitivity and specificity were 0.75 (95% CI 0.67 to 0.82) and 0.98 (95% CI 0.95 to 0.99). DSM criteria had no significant effect on sensitivity (P = 0.421), but the specificity for detection of delirium was higher when DSM-5 criteria were used (P = 0.024). The relative specificity comparing DSM-5 versus DSM-IV criteria was 1.05 (95% CI 1.02 to 1.08). Summary estimates of sensitivity and specificity for studies recruiting < 100% of patients with mechanical ventilation were 0.81 (95% CI 0.75 to 0.85) and 0.95 (95% CI 0.91 to 0.98). For studies that exclusively recruited patients with mechanical ventilation, summary estimates of sensitivity and specificity were 0.91 (95% CI 0.76 to 0.97) and 0.98 (95% CI 0.92 to 0.99). Although there was a suggestion of differential performance of CAM-ICU in ventilated patients, the differences were not significant in sensitivity (P = 0.316) or in specificity (P = 0.493). AUTHORS' CONCLUSIONS: The CAM-ICU tool may have a role in the early identification of delirium, in adult patients hospitalized in intensive care units, including those on mechanical ventilation, when non-specialized, properly trained clinical personnel apply the CAM-ICU. The test is most useful for exclusion of delirium. The test may miss a proportion of patients with incident delirium, therefore in situations where detection of all delirium cases is desirable, it may be best to repeat the test or combine CAM-ICU with another assessment. Future studies should compare different screening tests proposed for bedside assessment of delirium, as this approach will reveal which tool yields superior accuracy. In addition, future studies should consider and report the flow and timing of the tests and clearly report key characteristics related to patient selection. Finally, future research should focus on the impact of CAM-ICU screening on patient outcomes.

Multi-domain prognostic models used in middle-aged adults without known cognitive impairment for predicting subsequent dementia.

BACKGROUND: Dementia, a global health priority, has no current cure. Around 50 million people worldwide currently live with dementia, and this number is expected to treble by 2050. Some health conditions and lifestyle behaviours can increase or decrease the risk of dementia and are known as 'predictors'. Prognostic models combine such predictors to measure the risk of future dementia. Models that can accurately predict future dementia would help clinicians select high-risk adults in middle age and implement targeted risk reduction. OBJECTIVES: Our primary objective was to identify multi-domain prognostic models used in middle-aged adults (aged 45 to 65 years) for predicting dementia or cognitive impairment. Eligible multi-domain prognostic models involved two or more of the modifiable dementia predictors identified in a 2020 Lancet Commission report and a 2019 World Health Organization (WHO) report (less education, hearing loss, traumatic brain injury, hypertension, excessive alcohol intake, obesity, smoking, depression, social isolation, physical inactivity, diabetes mellitus, air pollution, poor diet, and cognitive inactivity). Our secondary objectives were to summarise the prognostic models, to appraise their predictive accuracy (discrimination and calibration) as reported in the development and validation studies, and to identify the implications of using dementia prognostic models for the management of people at a higher risk for future dementia. SEARCH METHODS: We searched MEDLINE, Embase, PsycINFO, CINAHL, and ISI Web of Science Core Collection from inception until 6 June 2022. We performed forwards and backwards citation tracking of included studies using the Web of Science platform.  SELECTION CRITERIA: We included development and validation studies of multi-domain prognostic models. The minimum eligible follow-up was five years. Our primary outcome was an incident clinical diagnosis of dementia based on validated diagnostic criteria, and our secondary outcome was dementia or cognitive impairment determined by any other method. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the references, extracted data using a template based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS), and assessed risk of bias and applicability of included studies using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We synthesised the C-statistics of models that had been externally validated in at least three comparable studies.  MAIN RESULTS: We identified 20 eligible studies; eight were development studies and 12 were validation studies. There were 14 unique prognostic models: seven models with validation studies and seven models with development-only studies. The models included a median of nine predictors (range 6 to 34); the median number of modifiable predictors was five (range 2 to 11). The most common modifiable predictors in externally validated models were diabetes, hypertension, smoking, physical activity, and obesity. In development-only models, the most common modifiable predictors were obesity, diabetes, hypertension, and smoking. No models included hearing loss or air pollution as predictors. Nineteen studies had a high risk of bias according to the PROBAST assessment, mainly because of inappropriate analysis methods, particularly lack of reported calibration measures. Applicability concerns were low for 12 studies, as their population, predictors, and outcomes were consistent with those of interest for this review. Applicability concerns were high for nine studies, as they lacked baseline cognitive screening or excluded an age group within the range of 45 to 65 years. Only one model, Cardiovascular Risk Factors, Ageing, and Dementia (CAIDE), had been externally validated in multiple studies, allowing for meta-analysis. The CAIDE model included eight predictors (four modifiable predictors): age, education, sex, systolic blood pressure, body mass index (BMI), total cholesterol, physical activity and APOEƐ4 status. Overall, our confidence in the prediction accuracy of CAIDE was very low; our main reasons for downgrading the certainty of the evidence were high risk of bias across all the studies, high concern of applicability, non-overlapping confidence intervals (CIs), and a high degree of heterogeneity. The summary C-statistic was 0.71 (95% CI 0.66 to 0.76; 3 studies; very low-certainty evidence) for the incident clinical diagnosis of dementia, and 0.67 (95% CI 0.61 to 0.73; 3 studies; very low-certainty evidence) for dementia or cognitive impairment based on cognitive scores. Meta-analysis of calibration measures was not possible, as few studies provided these data. AUTHORS' CONCLUSIONS: We identified 14 unique multi-domain prognostic models used in middle-aged adults for predicting subsequent dementia. Diabetes, hypertension, obesity, and smoking were the most common modifiable risk factors used as predictors in the models. We performed meta-analyses of C-statistics for one model (CAIDE), but the summary values were unreliable. Owing to lack of data, we were unable to meta-analyse the calibration measures of CAIDE. This review highlights the need for further robust external validations of multi-domain prognostic models for predicting future risk of dementia in middle-aged adults.

Anticholinergic deprescribing interventions for reducing risk of cognitive decline or dementia in older adults with and without prior cognitive impairment.

BACKGROUND: Anticholinergics are medications that block the action of acetylcholine in the central or peripheral nervous system. 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. A high anticholinergic burden may cause cognitive impairment in people who are otherwise cognitively healthy, or cause further cognitive decline in people with pre-existing cognitive problems. Reducing anticholinergic burden through deprescribing interventions may help to prevent onset of cognitive impairment or slow the rate of cognitive decline. OBJECTIVES: Primary objective • To assess the efficacy and safety of anticholinergic medication reduction interventions for improving cognitive outcomes in cognitively healthy older adults and older adults with pre-existing cognitive issues. Secondary Objectives • To compare the effectiveness of different types of reduction interventions (e.g. pharmacist-led versus general practitioner-led, educational versus audit and feedback) for reducing overall anticholinergic burden. • To establish optimal duration of anticholinergic reduction interventions, sustainability, and lessons learnt for upscaling • To compare results according to differing anticholinergic scales used in medication reduction intervention trials • To assess the efficacy of anticholinergic medication reduction interventions for improving other clinical outcomes, including mortality, quality of life, clinical global impression, physical function, institutionalisation, falls, cardiovascular diseases, and neurobehavioral outcomes. SEARCH METHODS: We searched CENTRAL on 22 December 2022, and we searched MEDLINE, Embase, and three other databases from inception to 1 November 2022. SELECTION CRITERIA: We included randomised controlled trials (RCTs) of interventions that aimed to reduce anticholinergic burden in older people and that investigated cognitive outcomes. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed studies for inclusion, extracted data, and assessed the risk of bias of included studies. The data were not suitable for meta-analysis, so we summarised them narratively. We used GRADE methods to rate our confidence in the review results. MAIN RESULTS: We included three trials with a total of 299 participants. All three trials were conducted in a cognitively mixed population (some cognitively healthy participants, some participants with dementia). Outcomes were assessed after one to three months. One trial reported significantly improved performance on the Digit Symbol Substitution Test (DSST) in the intervention group (treatment difference 0.70, 95% confidence interval (CI) 0.11 to 1.30), although there was no difference between the groups in the proportion of participants with reduced anticholinergic burden. Two trials successfully reduced anticholinergic burden in the intervention group. Of these, one reported no significant difference between the intervention versus control in terms of their effect on cognitive performance measured by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) immediate recall (mean between-group difference 0.54, 95% CI -0.91 to 2.05), CERAD delayed recall (mean between-group difference -0.23, 95% CI-0.85 to 0.38), CERAD recognition (mean between-group difference 0.77, 95% CI -0.39 to 1.94), and Mini-Mental State Examination (mean between-group difference 0.39, 95% CI -0.96 to 1.75). The other trial reported a significant correlation between anticholinergic burden and a test of working memory after the intervention (which suggested reducing the burden improved performance), but reported no effect on multiple other cognitive measures. In GRADE terms, the results were of very low certainty. There were no reported between-group differences for any other clinical outcome we investigated. It was not possible to investigate differences according to type of reduction intervention or type of anticholinergic scale, to measure the sustainability of interventions, or to establish lessons learnt for upscaling. No trials investigated safety outcomes. AUTHORS' CONCLUSIONS: There is insufficient evidence to reach any conclusions on the effects of anticholinergic burden reduction interventions on cognitive outcomes in older adults with or without prior cognitive impairment. The evidence from RCTs was of very low certainty so cannot support or refute the hypothesis that actively reducing or stopping prescription of medications with anticholinergic properties can improve cognitive outcomes in older people. There is no evidence from RCTs that anticholinergic burden reduction interventions improve other clinical outcomes such as mortality, quality of life, clinical global impression, physical function, institutionalisation, falls, cardiovascular diseases, or neurobehavioral outcomes. Larger RCTs investigating long-term outcomes are needed. Future RCTs should also investigate potential benefits of anticholinergic reduction interventions in cognitively healthy populations and cognitively impaired populations separately.

Thyroid antibodies and levothyroxine effects in subclinical hypothyroidism: A pooled analysis of two randomized controlled trials.

BACKGROUND: Antithyroid antibodies increase the likelihood of developing overt hypothyroidism, but their clinical utility remains unclear. No large randomized controlled trial (RCT) has assessed whether older adults with subclinical hypothyroidism (SHypo) caused by autoimmune thyroid disease derive more benefits from levothyroxine treatment (LT4). OBJECTIVE: To determine whether older adults with SHypo and positive antibodies derive more clinical benefits from LT4 than those with negative antibodies. METHODS: We pooled individual participant data from two RCTs, Thyroid Hormone Replacement for Untreated Older Adults with Subclinical Hypothyroidism and IEMO 80+. Participants with persistent SHypo were randomly assigned to receive LT4 or placebo. We compared the effects of LT4 versus placebo in participants with and without anti-thyroid peroxidase (TPO) at baseline. The two primary outcomes were 1-year change in Hypothyroid Symptoms and Tiredness scores on the Thyroid-Related Quality-of-Life Patient-Reported Outcome Questionnaire. RESULTS: Among 660 participants (54% women) ≥65 years, 188 (28.5%) had positive anti-TPO. LT4 versus placebo on Hypothyroid Symptoms lead to an adjusted between-group difference of -2.07 (95% confidence interval: -6.04 to 1.90) for positive antibodies versus 0.89 (-1.76 to 3.54) for negative antibodies (p for interaction = 0.31). Similarly, there was no treatment effect modification by baseline antibody status for Tiredness scores-adjusted between-group difference 1.75 (-3.60 to 7.09) for positive antibodies versus 1.14 (-1.90 to 4.19) for negative antibodies (p for interaction = 0.98). Positive anti-TPO were not associated with better quality of life, improvement in handgrip strength, or fewer cardiovascular outcomes with levothyroxine treatment. CONCLUSIONS: Among older adults with SHypo, positive antithyroid antibodies are not associated with more benefits on clinical outcomes with LT4.

Antithrombotic therapy to prevent cognitive decline in people with small vessel disease on neuroimaging but without dementia.

BACKGROUND: Cerebral small vessel disease is a progressive disease of the brain's deep perforating blood vessels. It is usually diagnosed based on lesions seen on brain imaging. Cerebral small vessel disease is a common cause of stroke but can also cause a progressive cognitive decline. As antithrombotic therapy is an established treatment for stroke prevention, we sought to determine whether antithrombotic therapy might also be effective in preventing cognitive decline in people with small vessel disease. OBJECTIVES: To assess the effects of antithrombotic therapy for prevention of cognitive decline in people with small vessel disease on neuroimaging but without dementia. SEARCH METHODS: We searched ALOIS, the Cochrane Dementia and Cognitive Improvement Review Group's Specialised Register, and the Cochrane Stroke Group's Specialised Register; the most recent search was on 21 July 2021. We also searched MEDLINE, Embase, four other databases and two trials registries. We searched the reference lists of the articles retrieved from these searches. As trials with a stroke focus may include relevant subgroup data, we complemented these searches with a focussed search of all antithrombotic titles in the Cochrane Stroke Group database.  SELECTION CRITERIA: We included randomised controlled trials (RCT) of people with neuroimaging evidence of at least mild cerebral small vessel disease (defined here as white matter hyperintensities, lacunes of presumed vascular origin and subcortical infarcts) but with no evidence of dementia. The trials had to compare antithrombotic therapy of minimum 24 weeks' duration to no antithrombotic therapy (either placebo or treatment as usual), or compare different antithrombotic treatment regimens. Antithrombotic therapy could include antiplatelet agents (as monotherapy or combination therapy), anticoagulants or a combination. DATA COLLECTION AND ANALYSIS: Two review authors independently screened all the titles identified by the searches. We assessed full texts for eligibility for inclusion according to our prespecified selection criteria, extracted data to a proforma and assessed risk of bias using the Cochrane tool for RCTs. We evaluated the certainty of evidence using GRADE. Due to heterogeneity across included participants, interventions and outcomes of eligible trials, it was not possible to perform meta-analyses. MAIN RESULTS: We included three RCTs (3384 participants). One study investigated the effect of antithrombotic therapy in participants not yet on antithrombotic therapy; two studies investigated the effect of additional antithrombotic therapy, one in a population already taking a single antithrombotic agent and one in a mixed population (participants on an antithrombotic drug and antithrombotic-naive participants). Intervention and follow-up durations varied from 24 weeks to four years. Jia 2016 was a placebo-controlled trial assessing 24 weeks of treatment with DL-3-n-butylphthalide (a compound with multimodal actions, including a putative antiplatelet effect) in 280 Chinese participants with vascular cognitive impairment caused by subcortical ischaemic small vessel disease, but without dementia. There was very low-certainty evidence for a small difference in cognitive test scores favouring treatment with DL-3-n-butylphthalide, as measured by the 12-item Alzheimer's Disease Assessment Scale-Cognitive subscale (adjusted mean difference -1.07, 95% confidence interval (CI) -2.02 to -0.12), but this difference may not be clinically relevant. There was also very low-certainty evidence for greater proportional improvement measured with the Clinician Interview-Based Impression of Change-Plus Caregiver Input (57% with DL-3-n-butylphthalide versus 42% with placebo; P = 0.01), but there was no difference in other measures of cognition (Mini-Mental State Examination and Clinical Dementia Rating) or function. There was no evidence of a difference in adverse events between treatment groups. The SILENCE RCT compared antithrombotic therapy (aspirin) and placebo during four years of treatment in 83 participants with 'silent brain infarcts' who were on no prior antithrombotic therapy. There was very low-certainty evidence for no difference between groups across various measures of cognition and function, rates of stroke or adverse events. The Secondary Prevention of Subcortical Stroke Study (SPS3) compared dual antiplatelet therapy (clopidogrel plus aspirin) to aspirin alone in 3020 participants with recent lacunar stroke. There was low-certainty evidence of no effect on cognitive outcomes as measured by the Cognitive Abilities Screening Instruments (CASI) assessed annually over five years. There was also low-certainty evidence of no difference in the annual incidence of mild cognitive decline between the two treatment groups (9.7% with dual antiplatelet therapy versus 9.9% with aspirin), or the annual stroke recurrence rate (2.5% with dual antiplatelet therapy versus 2.7% with aspirin). Bleeding risk may be higher with dual antiplatelet therapy (hazard ratio (HR) 2.15, 95% CI 1.49 to 3.11; low certainty evidence), but there may be no significant increase in intracerebral bleeding risk (HR 1.52, 95% CI 0.79 to 2.93; low-certainty evidence). None of the included trials assessed the incidence of new dementia. AUTHORS' CONCLUSIONS: We found no convincing evidence to suggest any clinically relevant cognitive benefit of using antithrombotic therapy in addition to standard treatment in people with cerebral small vessel disease but without dementia, but there may be an increased bleeding risk with this approach. There was marked heterogeneity across the trials and the certainty of the evidence was generally poor.

Diagnostic test accuracy of remote, multidomain cognitive assessment (telephone and video call) for dementia.

BACKGROUND: Remote cognitive assessments are increasingly needed to assist in the detection of cognitive disorders, but the diagnostic accuracy of telephone- and video-based cognitive screening remains unclear. OBJECTIVES: To assess the test accuracy of any multidomain cognitive test delivered remotely for the diagnosis of any form of dementia. To assess for potential differences in cognitive test scoring when using a remote platform, and where a remote screener was compared to the equivalent face-to-face test. SEARCH METHODS: We searched ALOIS, the Cochrane Dementia and Cognitive Improvement Group Specialized Register, CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, LILACS, and ClinicalTrials.gov (www. CLINICALTRIALS: gov/) databases on 2 June 2021. We performed forward and backward searching of included citations. SELECTION CRITERIA: We included cross-sectional studies, where a remote, multidomain assessment was administered alongside a clinical diagnosis of dementia or equivalent face-to-face test. DATA COLLECTION AND ANALYSIS: Two review authors independently assessed risk of bias and extracted data; a third review author moderated disagreements. Our primary analysis was the accuracy of remote assessments against a clinical diagnosis of dementia. Where data were available, we reported test accuracy as sensitivity and specificity. We did not perform quantitative meta-analysis as there were too few studies at individual test level. For those studies comparing remote versus in-person use of an equivalent screening test, if data allowed, we described correlations, reliability, differences in scores and the proportion classified as having cognitive impairment for each test. MAIN RESULTS: The review contains 31 studies (19 differing tests, 3075 participants), of which seven studies (six telephone, one video call, 756 participants) were relevant to our primary objective of describing test accuracy against a clinical diagnosis of dementia. All studies were at unclear or high risk of bias in at least one domain, but were low risk in applicability to the review question. Overall, sensitivity of remote tools varied with values between 26% and 100%, and specificity between 65% and 100%, with no clearly superior test. Across the 24 papers comparing equivalent remote and in-person tests (14 telephone, 10 video call), agreement between tests was good, but rarely perfect (correlation coefficient range: 0.48 to 0.98). AUTHORS' CONCLUSIONS: Despite the common and increasing use of remote cognitive assessment, supporting evidence on test accuracy is limited. Available data do not allow us to suggest a preferred test. Remote testing is complex, and this is reflected in the heterogeneity seen in tests used, their application, and their analysis. More research is needed to describe accuracy of contemporary approaches to remote cognitive assessment. While data comparing remote and in-person use of a test were reassuring, thresholds and scoring rules derived from in-person testing may not be applicable when the equivalent test is adapted for remote use.

Anticholinergic burden for prediction of cognitive decline or neuropsychiatric symptoms in older adults with mild cognitive impairment or dementia.

BACKGROUND: Medications with anticholinergic properties are commonly prescribed to older adults with a pre-existing diagnosis of dementia or cognitive impairment. 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 a high anticholinergic burden may be a risk factor for further cognitive decline or neuropsychiatric disturbances in people with dementia. Neuropsychiatric disturbances are the most frequent complication of dementia that require hospitalisation, accounting for almost half of admissions; hence, identification of modifiable prognostic factors for these outcomes is crucial. There are various scales available to measure anticholinergic burden but agreement between them is often poor. OBJECTIVES: Our primary objective was to assess whether anticholinergic burden, as defined at the level of each individual scale, was a prognostic factor for further cognitive decline or neuropsychiatric disturbances in older adults with pre-existing diagnoses of dementia or cognitive impairment. Our secondary objective was to investigate whether anticholinergic burden was a prognostic factor for other adverse clinical outcomes, including mortality, impaired physical function, and institutionalisation. SEARCH METHODS: We searched these databases from inception to 29 November 2021: MEDLINE OvidSP, Embase OvidSP, PsycINFO OvidSP, CINAHL EBSCOhost, and ISI Web of Science Core Collection on ISI Web of Science. SELECTION CRITERIA: We included prospective and retrospective longitudinal cohort and case-control observational studies, with a minimum of one-month follow-up, which examined the association between an anticholinergic burden measurement scale and the above stated adverse clinical outcomes, in older adults with pre-existing diagnoses of dementia or cognitive impairment.   DATA COLLECTION AND ANALYSIS: Two review authors independently assessed studies for inclusion, and undertook data extraction, risk of bias assessment, and GRADE assessment. We summarised risk associations between anticholinergic burden and all clinical outcomes in a narrative fashion. We also evaluated the risk association between anticholinergic burden and mortality using a random-effects meta-analysis.  We established adjusted pooled rates for the anticholinergic cognitive burden (ACB) scale; then, as an exploratory analysis, established pooled rates on the prespecified association across scales.  MAIN RESULTS: We identified 18 studies that met our inclusion criteria (102,684 older adults). Anticholinergic burden was measured using five distinct measurement scales: 12 studies used the ACB scale; 3 studies used the Anticholinergic Risk Scale (ARS); 1 study used the Anticholinergic Drug Scale (ADS); 1 study used the Anticholinergic Effect on Cognition (AEC) Scale; and 2 studies used a list developed by Tune and Egeli.  Risk associations between anticholinergic burden and adverse clinical outcomes were highly heterogenous. Four out of 10 (40%) studies reported a significantly increased risk of greater long-term cognitive decline for participants with an anticholinergic burden compared to participants with no or minimal anticholinergic burden. No studies investigated neuropsychiatric disturbance outcomes. One out of four studies (25%) reported a significant association with reduced physical function for participants with an anticholinergic burden versus participants with no or minimal anticholinergic burden. No study (out of one investigating study) reported a significant association between anticholinergic burden and risk of institutionalisation. Six out of 10 studies (60%) found a significantly increased risk of mortality for those with an anticholinergic burden compared to those with no or minimal anticholinergic burden. Pooled analysis of adjusted mortality hazard ratios (HR) measured anticholinergic burden with the ACB scale, and suggested a significantly increased risk of death for those with a high ACB score relative to those with no or minimal ACB scores (HR 1.153, 95% confidence interval (CI) 1.030 to 1.292; 4 studies, 48,663 participants). An exploratory pooled analysis of adjusted mortality HRs across anticholinergic burden scales also suggested a significantly increased risk of death for those with a high anticholinergic burden (HR 1.102, 95% CI 1.044 to 1.163; 6 studies, 68,381 participants).   Overall GRADE evaluation of results found low- or very low-certainty evidence for all outcomes.  AUTHORS' CONCLUSIONS: There is low-certainty evidence that older adults with dementia or cognitive impairment who have a significant anticholinergic burden may be at increased risk of death. No firm conclusions can be drawn for risk of accelerated cognitive decline, neuropsychiatric disturbances, decline in physical function, or institutionalisation.

Interrater agreement in dementia diagnosis: A systematic review and meta-analysis.

OBJECTIVES: Dementia remains a clinical diagnosis with a degree of subjective assessment and potential for interrater disagreement. We described interrater agreement of clinical dementia diagnosis for various diagnostic criteria. METHODS: We conducted a PROSPERO-registered (CRD42020168245) systematic review and meta-analysis. We searched multiple cross-disciplinary databases from inception until April 2020 for relevant papers, extracted data and described study quality in duplicate. Study quality was assessed using the Guidelines for Reporting Reliability and Agreement Studies. We used random-effects models to obtain summary estimates of interrater agreement using kappa and, where possible, Gwet's AC1/2 coefficients. RESULTS: We found 7577 titles and 22 eligible studies. Meta-analysis was possible for all-cause dementia using the Diagnostic and Statistical Manual of Mental Disorders third edition revised (DSM-III-R) criteria (kappa = 0.66, 95% CI = [0.53,0.78]), Alzheimer's disease using the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's disease and Related Disorders Association (NINCDS-ADRDA) criteria (kappa = 0.71, 95% CI = [0.65,0.77] for presence/absence and AC2 = 0.61, 95% CI = [0.53,0.70] when distinguishing probable/possible cases), and vascular dementia using the International Classification of Diseases version 10 (ICD-10) criteria kappa = 0.79 (95% CI = [0.70,0.87]). Data was more limited for other criteria and dementia types. AC1/2 coefficients generally indicated higher agreement. One study was rated as high quality. CONCLUSIONS: Diagnostic criteria for clinical dementia may have good but imperfect agreement. This has important implications for clinical practice and research studies, which frequently assume these criteria are perfect tests, such as diagnostic test accuracy studies frequently conducted for biomarkers and neuropsychological tests, and for trials where incident dementia is the outcome.

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.

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.

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.

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 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.

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.

ANTECEDENTES: A los adultos mayores se les prescriben con frecuencia fármacos con propiedades anticolinérgicas. El efecto anticolinérgico acumulado de todos los fármacos que toma una persona se denomina "carga anticolinérgica" por su potencial para causar efectos adversos. Es posible que una alta carga anticolinérgica sea un factor de riesgo para la aparición de un deterioro cognitivo o la demencia. Existen varias escalas para medir la carga anticolinérgica, pero la concordancia entre ellas suele ser mala. OBJETIVOS: Evaluar si la carga anticolinérgica, definida a nivel de cada escala individual, es un factor pronóstico de un futuro deterioro cognitivo o demencia en adultos mayores sin deterioro cognitivo. MÉTODOS DE BÚSQUEDA: Se realizaron búsquedas en las siguientes bases de datos desde su creación hasta el 24 de marzo de 2021: MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), CINAHL (EBSCOhost) e ISI Web of Science Core Collection (ISI Web of Science). CRITERIOS DE SELECCIÓN: Se incluyeron los estudios observacionales de cohortes y de casos y controles longitudinales prospectivos y retrospectivos con un seguimiento mínimo de un año, que examinaron la asociación entre una escala de medición de la carga anticolinérgica y el futuro deterioro cognitivo o demencia en adultos mayores sin deterioro cognitivo. OBTENCIÓN Y ANÁLISIS DE LOS DATOS: Dos autores de la revisión, de forma independiente, evaluaron los estudios para su inclusión y realizaron la extracción de los datos, la evaluación del riesgo de sesgo y la evaluación GRADE. Se extrajeron los odds ratios (OR) y los cociente de riesgos instantáneos, con intervalos de confianza (IC) del 95%, y los datos lineales sobre la asociación entre la carga anticolinérgica y el deterioro cognitivo o la demencia. La intención fue agrupar cada métrica por separado; sin embargo, sólo los datos basados en el OR fueron aptos para agruparlos mediante un metanálisis de efectos aleatorios. Inicialmente se establecieron las tasas agrupadas ajustadas y no ajustadas para cada escala anticolinérgica disponible; luego, como un análisis exploratorio, se establecieron las tasas agrupadas sobre la asociación predeterminada entre las escalas. Se examinó la variabilidad según la intensidad de la carga anticolinérgica. RESULTADOS PRINCIPALES: Se identificaron 25 estudios que cumplían los criterios de inclusión (968 428 adultos mayores). Veinte estudios se realizaron en ámbitos de atención comunitaria, dos en centros de atención primaria y tres en ámbitos de atención secundaria. Ocho estudios (320 906 participantes) proporcionaron datos adecuados para el metanálisis. La escala Anticholinergic Cognitive Burden (escala ACB) fue la única escala con datos suficientes para un metanálisis "basado en la escala". Los OR no ajustados indicaron un aumento en el riesgo de deterioro cognitivo o demencia en los adultos mayores con sobrecarga anticolinérgica (OR 1,47; IC del 95%: 1,09 a 1,96) y los OR ajustados indicaron igualmente un aumento en el riesgo de sobrecarga anticolinérgica, definida según la escala ACB (OR 2,63; IC del 95%: 1,09 a 6,29). El análisis exploratorio que combina los OR ajustados entre las escalas disponibles apoyó estos resultados (OR 2,16; IC del 95%: 1,38 a 3,38) y hubo evidencia de variabilidad en el riesgo según la intensidad de la carga anticolinérgica (1 en escala ACB): OR 2,18; IC del 95%: 1,11 a 4,29; 2 en escala ACB: OR 2,71; IC del 95%: 2,01 a 3,56; 3 en escala ACB: OR 3,27; IC del 95%: 1,41 a 7,61); sin embargo, la evaluación global de la certeza de la evidencia con el método GRADE fue baja. CONCLUSIONES DE LOS AUTORES: Existe evidencia de certeza baja de que los adultos mayores sin deterioro cognitivo que toman fármacos con efectos anticolinérgicos podrían tener un mayor riesgo de deterioro cognitivo o demencia.

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.