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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.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.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.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.

This is a protocol for a Cochrane Review (prognosis). The objectives are as follows: Primary objective To assess whether anticholinergic burden, as defined at the level of each individual scale, is a prognostic factor for further cognitive decline or neuropsychiatric disturbances in people with mild cognitive impairment (MCI) or dementia. Secondary objective To compare the prognostic validity of different anticholinergic burden scales. To examine the effect of type of dementia and severity of dementia on the association between anticholinergic burden and rate of cognitive decline or neuropsychiatric disturbances. To examine the effect of setting (care home versus non‐care home) on the association between anticholinergic burden and rate of cognitive decline or neuropsychiatric disturbances. To examine whether anticholinergic burden is a prognostic factor for other clinical outcomes in people with MCI or dementia.

Various informant-based questionnaires are used in clinical practice to screen for pre-stroke cognitive problems. However, there is no guidance on which tool should be preferred. We compared the validity of the two most commonly used informant-based tools.We recruited consecutively admitted stroke patients. Patients' informants completed the Informant Questionnaire for Cognitive Decline in the Elderly Short Form (IQCODE-SF, 16-item) and Ascertain Dementia 8 (AD8). We assessed construct validity (accuracy) against a semi-structured clinical interview for dementia or mild cognitive impairment (MCI), describing test accuracy metrics and comparing area under ROC curves (AUROC). We described criterion validity by evaluating associations between test scores and neuroimaging markers of dementia and overall 'brain frailty'. Finally, we described prognostic validity comparing ROC curves for 18-month clinical outcomes of dementia, death, stroke, and disability.One-hundred-thirty-seven patient-informant dyads were recruited. At usual clinical cut-points, the IQCODE-SF had comparable sensitivity to the AD8 (both = 92%) for pre-stroke dementia, but superior specificity (IQCODE-SF: 82% vs. AD8: 58%). Youden index suggested that the optimal AD8 threshold for diagnosis of dementia is ≥4. The IQCODE-SF demonstrated stronger associations with markers of generalised and medial-temporal lobe atrophy, neurovascular disease, and overall brain frailty. IQCODE-SF also demonstrated greater accuracy for predicting future dementia (IQCODE-SF AUROC = 0.903, 95% CI = 0.798-1.00; AD8 AUROC = 0.821, 95% CI = 0.664-0.977).Both IQCODE-SF and AD8 are valid measures of pre-stroke dementia. Higher cut points for AD8 may improve performance in the acute stroke setting. Based on consistent superiority across a range of validity analyses, IQCODE-SF may be preferable to AD8 for pre-stroke dementia screening.

Background and Purpose— Delirium is a common and serious complication of acute illness. We describe delirium occurrence in an unselected, acute stroke population. Methods— We collected data from consecutive stroke admissions. We performed comprehensive cognitive assessment within the first week including Diagnostic Statistical Manual-5–based delirium diagnosis. We reported proportion with delirium and the clinical and demographic associations with delirium using multiple logistic regression. Results— Of 708 patients, median age of 71 years (interquartile range, 59–80), we recorded delirium in 187 of 708 (26.4%; 95% CI, 23.0–30.0). Across 395 patients with complete risk factor data (105 delirium), factors independently associated with delirium were: age (odds ratio, 1.05; 95% CI, 1.03–1.08), drug/alcohol misuse (odds ratio, 2.64; 95% CI, 1.10–6.26), and stroke severity (odds ratio, 1.22; 95% CI, 1.14–1.31). Conclusions— Delirium is common in acute stroke, affecting 1 in 4. It may be possible to predict those at risk using prestroke and stroke-specific factors. Clinical Trial Registration— URL: researchregistry.com . Protocol: 1147.

Shortened versions of self-reported questionnaires may be used to reduce respondent burden. When shortened screening tools are used, it is desirable to maintain equivalent diagnostic accuracy to full-length forms. This manuscript presents a case study that illustrates how external data and individual participant data meta-analysis can be used to assess the equivalence in diagnostic accuracy between a shortened and full-length form. This case study compares the Patient Health Questionnaire-9 (PHQ-9) and a 4-item shortened version (PHQ-Dep-4) that was previously developed using optimal test assembly methods. Using a large database of 75 primary studies (34,698 participants, 3,392 major depression cases), we evaluated whether the PHQ-Dep-4 cutoff of ≥ 4 maintained equivalent diagnostic accuracy to a PHQ-9 cutoff of ≥ 10. Using this external validation dataset, a PHQ-Dep-4 cutoff of ≥ 4 maximized the sum of sensitivity and specificity, with a sensitivity of 0.88 (95% CI 0.81, 0.93), 0.68 (95% CI 0.56, 0.78), and 0.80 (95% CI 0.73, 0.85) for the semi-structured, fully structured, and MINI reference standard categories, respectively, and a specificity of 0.79 (95% CI 0.74, 0.83), 0.85 (95% CI 0.78, 0.90), and 0.83 (95% CI 0.80, 0.86) for the semi-structured, fully structured, and MINI reference standard categories, respectively. While equivalence with a PHQ-9 cutoff of ≥ 10 was not established, we found the sensitivity of the PHQ-Dep-4 to be non-inferior to that of the PHQ-9, and the specificity of the PHQ-Dep-4 to be marginally smaller than the PHQ-9.

Background Informant-based questionnaires may have utility for cognitive impairment or dementia screening. Reviews describing the accuracy of respective questionnaires are available, but their focus on individual questionnaires precludes comparisons across tools. We conducted an overview of systematic reviews to assess the comparative accuracy of informant questionnaires and identify areas where evidence is lacking. Methods We searched six databases to identify systematic reviews describing diagnostic test accuracy of informant questionnaires for cognitive impairment or dementia. We pooled sensitivity and specificity data for each questionnaire and used network approaches to compare accuracy estimates across the differing tests. We used grading of recommendations, assessment, development and evaluation (GRADE) to evaluate the overall certainty of evidence. Finally, we created an evidence ‘heat-map’, describing the availability of accurate data for individual tests in different populations and settings. Results We identified 25 reviews, consisting of 93 studies and 13 informant questionnaires. Pooled analysis (37 studies; 11 052 participants) ranked the eight-item interview to ascertain dementia (AD8) highest for sensitivity [90%; 95% credible intervals (CrI) = 82–95; ‘best-test’ probability = 36]; while the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) was most specific (81%; 95% CrI = 66–90; ‘best-test’ probability = 29%). GRADE-based evaluation of evidence suggested certainty was ‘low’ overall. Our heat-map indicated that only AD8 and IQCODE have been extensively evaluated and most studies have been in the secondary care settings. Conclusions AD8 and IQCODE appear to be valid questionnaires for cognitive impairment or dementia assessment. Other available informant-based cognitive screening questionnaires lack evidence to justify their use at present. Evidence on the accuracy of available tools in primary care settings and with specific populations is required.

Atherosclerotic stenosis of the internal carotid artery is an important cause of stroke. The aim of this guideline is to analyse the evidence pertaining to medical, surgical and endovascular treatment of patients with carotid stenosis. These guidelines were developed based on the ESO standard operating procedure and followed the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. The working group identified relevant questions, performed systematic reviews and meta-analyses of the literature, assessed the quality of the available evidence, and wrote recommendations. Based on moderate quality evidence, we recommend carotid endarterectomy (CEA) in patients with ≥60–99% asymptomatic carotid stenosis considered to be at increased risk of stroke on best medical treatment (BMT) alone. We also recommend CEA for patients with ≥70–99% symptomatic stenosis, and we suggest CEA for patients with 50–69% symptomatic stenosis. Based on high quality evidence, we recommend CEA should be performed early, ideally within two weeks of the last retinal or cerebral ischaemic event in patients with ≥50–99% symptomatic stenosis. Based on low quality evidence, carotid artery stenting (CAS) may be considered in patients

Background: \ud 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.\ud \ud Objectives: \ud 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.\ud \ud Search methods: \ud 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).\ud \ud Selection criteria: \ud 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.\ud \ud Data collection and analysis: \ud 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.\ud \ud Main results: \ud 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.\ud \ud Authors' conclusions: \ud 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.

Background Following the initial identification of the 2019 coronavirus disease (covid-19), the subsequent months saw substantial increases in published biomedical research. Concerns have been raised in both scientific and lay press around the quality of some of this research. We assessed clinical research from major clinical journals, comparing methodological and reporting quality of covid-19 papers published in the first wave (here defined as December 2019 to May 2020 inclusive) of the viral pandemic with non-covid papers published at the same time. Methods We reviewed research publications (print and online) from The BMJ, Journal of the American Medical Association (JAMA), The Lancet, and New England Journal of Medicine, from first publication of a covid-19 research paper (February 2020) to May 2020 inclusive. Paired reviewers were randomly allocated to extract data on methodological quality (risk of bias) and reporting quality (adherence to reporting guidance) from each paper using validated assessment tools. A random 10% of papers were assessed by a third, independent rater. Overall methodological quality for each paper was rated high, low or unclear. Reporting quality was described as percentage of total items reported. Results From 168 research papers, 165 were eligible, including 54 (33%) papers with a covid-19 focus. For methodological quality, 18 (33%) covid-19 papers and 83 (73%) non-covid papers were rated as low risk of bias, OR 6.32 (95%CI 2.85 to 14.00). The difference in quality was maintained after adjusting for publication date, results, funding, study design, journal and raters (OR 6.09 (95%CI 2.09 to 17.72)). For reporting quality, adherence to reporting guidelines was poorer for covid-19 papers, mean percentage of total items reported 72% (95%CI:66 to 77) for covid-19 papers and 84% (95%CI:81 to 87) for non-covid. Conclusions Across various measures, we have demonstrated that covid-19 research from the first wave of the pandemic was potentially of lower quality than contemporaneous non-covid research. While some differences may be an inevitable consequence of conducting research during a viral pandemic, poor reporting should not be accepted.

Objectives This systematic review (PROSPERO CRD42019115918) compared the evidence behind anticholinergic burden (ACB) measures and their ability to predict changes in older people's physical function and quality of life. Design Eligible cohort or case-control studies were identified systematically using comprehensive search terms and a validated search filter for prognostic studies. Medline (OVID), EMBASE (OVID), CINAHL (EMBSCO), and PsycINFO (OVID) databases were searched. Risk of bias, using Quality in Prognosis Studies tool, and quality of evidence, using the Grading of Recommendations, Assessment, Development and Evaluation, were assessed. Setting and Participants People aged 65 years and older from any clinical setting. Measures Any ACB measures were accepted (including the anticholinergic domain of the Drug Burden Index). Any global/multidimensional measure for physical function and/or quality of life was accepted for outcome. Results Thirteen studies reporting associations between ACB and physical function (n = 10) or quality of life (n = 4) were included. Exposure measures included Anticholinergic Cognitive Burden Scale, Anticholinergic Drug Scale, Anticholinergic Risk Scale, Clinician Rated Anticholinergic Score, and the anticholinergic domain of the Drug Burden Index. All studies were rated moderate risk of bias in ≥2 Quality in Prognosis Studies categories with 5 rated high risk in ≥1 categories. Seven of 10 studies (5251 of 7569 participants) reported significant decline in physical function with increased burden. All 4 studies (2635 participants) reporting quality of life demonstrated similar association with increased burden. High risk of biases and inadequate data reporting restricted analysis. There was no evidence to support one measure being superior to another. Conclusions and Implications The evidence supports association between increased ACB and future impairments in physical function and quality of life. No conclusion can be made regarding which ACB measure has the best prognostic value. Well-designed longitudinal studies are required to address this. Clinicians should be aware of patient's anticholinergic burden and consider alternative medications where appropriate.

Introduction: Several adverse outcomes have been associated with anticholinergic burden (ACB), and these risks increase with age. Several approaches to measuring this burden are available but, to date, no comparison of their prognostic abilities has been conducted. This PROSPERO-registered systematic review (CRD42019115918) compared the evidence behind ACB measures in relation to their ability to predict risk of falling in older people. Methods: Medline (OVID), EMBASE (OVID), CINAHL (EMBSCO) and PsycINFO (OVID) were searched using comprehensive search terms and a validated search filter for prognostic studies. Inclusion criteria included: participants aged 65 years and older, use of one or more ACB measure(s) as a prognostic factor, cohort or case-control in design, and reporting falls as an outcome. Risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool. Results: Eight studies reporting temporal associations between ACB and falls were included. All studies were rated high risk of bias in ⩾1 QUIPS tool categories, with five rated high risk ⩾3 categories. All studies (274,647 participants) showed some degree of association between anticholinergic score and increased risk of falls. Findings were most significant with moderate to high levels of ACB. Most studies (6/8) utilised the anticholinergic cognitive burden scale. No studies directly compared two or more ACB measures and there was variation in how falls were measured for analysis. Conclusion: The evidence supports an association between moderate to high ACB and risk of falling in older people, but no conclusion can be made regarding which ACB scale offers best prognostic value in older people. Plain language summary A review of published studies to explore which anticholinergic burden scale is best at predicting the risk of falls in older people Introduction: One third of older people will experience a fall. Falls have many consequences including fractures, a loss of independence and being unable to enjoy life. Many things can increase the chances of having a fall. This includes some medications. One type of medication, known as anticholinergic medication, may increase the risk of falls. These medications are used to treat common health issues including depression and bladder problems. Anticholinergic burden is the term used to describe the total effects from taking these medications. Some people may use more than one of these medications. This would increase their anticholinergic burden. It is possible that reducing the use of these medications could reduce the risk of falls. We need to carry out studies to see if this is possible. To do this, we need to be able to measure anticholinergic burden. There are several scales available, but we do not know which is best. Methods: We wanted to answer: ‘Which anticholinergic scale is best at predicting the risk of falling in older people?’. We reviewed studies that could answer this. We did this in a systematic way to capture all published studies. We restricted the search in several ways. We only included studies relevant to our question. Results: We found eight studies. We learned that people who are moderate to high users of these medications (often people who will use more than one of these medications) had a higher risk of falling. It was less clear if people who have a lower burden (often people who only use one of these medications) had an increased risk of falling. The low number of studies prevented us from determining if one scale was better than another. Conclusion: These findings suggest that we should reduce use of these medications. This could reduce the number falls and improve the well-being of older people.

Supplemental Digital Content is available in the text., Serum urate has been implicated in hypertension and cardiovascular disease, but it is not known whether it is exerting a causal effect. To investigate this, we performed Mendelian randomization analysis using data from UK Biobank, Million Veterans Program and genome-wide association study consortia, and meta-analysis of randomized controlled trials. The main Mendelian randomization analyses showed that every 1-SD increase in genetically predicted serum urate was associated with an increased risk of coronary heart disease (odds ratio, 1.19 [95% CI, 1.10–1.30]; P=4×10−5), peripheral artery disease (1.12 [95% CI, 1.03–1.21]; P=9×10−3), and stroke (1.11 [95% CI, 1.05–1.18]; P=2×10−4). In Mendelian randomization mediation analyses, elevated blood pressure was estimated to mediate approximately one-third of the effect of urate on cardiovascular disease risk. Systematic review and meta-analysis of randomized controlled trials showed a favorable effect of urate-lowering treatment on systolic blood pressure (mean difference, −2.55 mm Hg [95% CI, −4.06 to −1.05]; P=1×10−3) and major adverse cardiovascular events in those with previous cardiovascular disease (odds ratio, 0.40 [95% CI, 0.22–0.73]; P=3×10−3) but no significant effect on major adverse cardiovascular events in all individuals (odds ratio, 0.67 [95% CI, 0.44–1.03]; P=0.07). In summary, these Mendelian randomization and clinical trial data support an effect of higher serum urate on increasing blood pressure, which may mediate a consequent effect on cardiovascular disease risk. High-quality trials are necessary to provide definitive evidence on the specific clinical contexts where urate lowering may be of cardiovascular benefit.

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.

Background Cognitive impairment is an important consequence of stroke and transient ischaemic attack, but its determinants are not fully understood. Simple univariable or multivariable models have not shown clinical utility for predicting cognitive impairment. Cardiovascular risk factors may influence cognition through multiple, direct, and indirect pathways, including effects on prior cognition and stroke severity. Understanding these complex relationships may help clinical teams plan intervention and follow-up strategies. Methods We analysed clinical and demographic data from consecutive patients admitted to an acute stroke ward. Cognitive assessment comprised Abbreviated Mental Test and mini-Montreal Cognitive Assessment. We constructed bias-corrected confidence intervals to test indirect effects of cardiovascular risk factors (hypertension, vascular disease, atrial fibrillation, diabetes mellitus, previous stroke) on cognitive function, mediated through stroke severity and history of dementia, and we assessed moderation effects due to comorbidity. Results From 594 eligible patients, we included 587 in the final analysis (age range 26–100; 45% female). Our model explained R2 = 62.10% of variance in cognitive test scores. We found evidence for an indirect effect of previous stroke that was associated with increased risk of prevalent dementia and in turn predicted poorer cognitive score (estimate = − 0.39; 95% bias-corrected CI, − 0.75 to − 0.13; p = 0.02). Atrial fibrillation was associated with greater stroke severity and in turn with a poorer cognitive score (estimate = − 0.27; 95% bias-corrected CI, − 0.49 to − 0.05; p = 0.02). Conversely, previous TIA predicted decreased stroke severity and, through that, lesser cognitive impairment (estimate = 0.38; 95% bias-corrected CI, 0.08 to 0.75; p = 0.02). Through an association with reduced stroke severity, vascular disease was associated with lesser cognitive impairment, conditional on presence of hypertension and absence of diabetes mellitus (estimate = 0.36; 95% bias-corrected CI, 0.03 to 0.68; p = 0.02), although the modelled interaction effects did not reach statistical significance. Conclusions We have shown that relationships between cardiovascular risk factors and cognition are complex and simple multivariable models may be overly reductionist. Including direct and indirect effects of risk factors, we constructed a model that explained a substantial proportion of variation in cognitive test scores. Models that include multiple paths of influence and interactions could be used to create dementia prognostic tools for use in other healthcare settings.

Importance The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9. Objective To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression. Data sources MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, PsycINFO, and Web of Science (January 2000-May 2018). Study selection Eligible data sets compared PHQ-2 scores with major depression diagnoses from a validated diagnostic interview. Data extraction and synthesis Individual participant data were synthesized with bivariate random-effects meta-analysis to estimate pooled sensitivity and specificity of the PHQ-2 alone among studies using semistructured, fully structured, or Mini International Neuropsychiatric Interview (MINI) diagnostic interviews separately and in combination with the PHQ-9 vs the PHQ-9 alone for studies that used semistructured interviews. The PHQ-2 score ranges from 0 to 6, and the PHQ-9 score ranges from 0 to 27. Results Individual participant data were obtained from 100 of 136 eligible studies (44 318 participants; 4572 with major depression [10%]; mean [SD] age, 49 [17] years; 59% female). Among studies that used semistructured interviews, PHQ-2 sensitivity and specificity (95% CI) were 0.91 (0.88-0.94) and 0.67 (0.64-0.71) for cutoff scores of 2 or greater and 0.72 (0.67-0.77) and 0.85 (0.83-0.87) for cutoff scores of 3 or greater. Sensitivity was significantly greater for semistructured vs fully structured interviews. Specificity was not significantly different across the types of interviews. The area under the receiver operating characteristic curve was 0.88 (0.86-0.89) for semistructured interviews, 0.82 (0.81-0.84) for fully structured interviews, and 0.87 (0.85-0.88) for the MINI. There were no significant subgroup differences. For semistructured interviews, sensitivity for PHQ-2 scores of 2 or greater followed by PHQ-9 scores of 10 or greater (0.82 [0.76-0.86]) was not significantly different than PHQ-9 scores of 10 or greater alone (0.86 [0.80-0.90]); specificity for the combination was significantly but minimally higher (0.87 [0.84-0.89] vs 0.85 [0.82-0.87]). The area under the curve was 0.90 (0.89-0.91). The combination was estimated to reduce the number of participants needing to complete the full PHQ-9 by 57% (56%-58%). Conclusions and relevance In an individual participant data meta-analysis of studies that compared PHQ scores with major depression diagnoses, the combination of PHQ-2 (with cutoff ≥2) followed by PHQ-9 (with cutoff ≥10) had similar sensitivity but higher specificity compared with PHQ-9 cutoff scores of 10 or greater alone. Further research is needed to understand the clinical and research value of this combined approach to screening.

Objectives: Depression symptom questionnaires are not for diagnostic classification. Patient Health Questionnaire-9 (PHQ-9) scores >= 10 are nonetheless often used to estimate depression prevalence. We compared PHQ-9 >= 10 prevalence to Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders (SCID) major depression prevalence and assessed whether an alternative PHQ-9 cutoff could more accurately estimate prevalence. Study Design and Setting: Individual participant data meta-analysis of datasets comparing PHQ-9 scores to SCID major depression status. Results: A total of 9,242 participants (1,389 SCID major depression cases) from 44 primary studies were included. Pooled PHQ-9 >= 10 prevalence was 24.6% (95% confidence interval [CI]: 20.8%, 28.9%); pooled SCID major depression prevalence was 12.1% (95% CI: 9.6%, 15.2%); and pooled difference was 11.9% (95% CI: 9.3%, 14.6%). The mean study-level PHQ-9 >= 10 to SCID-based prevalence ratio was 2.5 times. PHQ-9 >= 14 and the PHQ-9 diagnostic algorithm provided prevalence closest to SCID major depression prevalence, but study-level prevalence differed from SCID-based prevalence by an average absolute difference of 4.8% for PHQ-9 >= 14 (95% prediction interval: -13.6%, 14.5%) and 5.6% for the PHQ-9 diagnostic algorithm (95% prediction interval: -16.4%, 15.0%). Conclusion: PHQ-9 >= 10 substantially overestimates depression prevalence. There is too much heterogeneity to correct statistically in individual studies. (C) 2020 Elsevier Inc. All rights reserved.

1.1 Background Greater anticholinergic burden (ACB) increases the risk of mortality in older individuals, yet the strength of this association varies between studies. One possible explanation for this variance is the use of different approaches to quantify ACB. This systematic review (PROSPERO number CRD42019115918) assessed the prognostic utility of ACB-specific measures on mortality in older individuals. 1.2 Methods Multiple cross-disciplinary databases were searched from 2006-2018. Observational studies assessing the association between ACB and mortality utilizing ≥1 ACB measure, involving persons aged ≥65 years were included. Screening and data extraction were performed by two independent reviewers, with disagreements resolved by a third independent reviewer. Risk of bias and quality of evidence were assessed using Quality in Prognosis Studies (QUIPS) and Grading of Recommendations, Assessment, Development and Evaluations (GRADE) criteria. Meta-analysis was conducted where appropriate. 1.3 Results Of 19,224 titles, 20 articles describing 18 cohort studies involving 498,056 older individuals were eligible. Eight anticholinergic-specific measures were identified; the Anticholinergic Cognitive Burden Scale (ACBS, n=9) and Anticholinergic Risk scale (ARS, n=8) were most frequently reported. The evidence base was of poor quality, with moderate to high risk of bias. Meta-analysis showed increased mortality risk. 1.4 Conclusions There was a modest association between some ACB measures and mortality, with most evidence derived from the ACBS. Studies comparing different measures within the same population were lacking. Analysis was limited by poor generalizability between studies, specifically regarding heterogeneity in methodology and reporting, as well as high risk of bias for most studies in the evidence base.

Background: Cognitive and mood problems have been highlighted as priorities in stroke research and guidelines recommend early screening. However, there is limited detail on the preferred approach. We aimed to (1) determine the optimal methods for evaluating psychological problems that pre-date stroke; (2) assess the test accuracy, feasibility and acceptability of brief cognitive and mood tests used at various time-points following stroke; (3) describe temporal changes in cognition and mood following stroke and explore predictors of change. Methods: We established a multi-centre, prospective, observational cohort with acute stroke as the inception point - Assessing Post-stroke Psychology Longitudinal Evaluation (APPLE). We approached patients admitted with stroke or transient ischaemic attack (TIA) from 11 different hospital sites across the United Kingdom. Baseline demographics, clinical, functional, cognitive, and mood data were collected. Consenting stroke survivors were followed up with more extensive evaluations of cognition and mood at 1, 6, 12 and 18 months. Results: Continuous recruitment was from February 2017 to February 2019. With 357 consented to full follow-up. Eighteen-month assessments were completed in September 2020 with permissions in-place for longer term in-person or electronic follow-up. A qualitative study has been completed, and a participant sample biobank and individual participant database are both available. Discussion: The APPLE study will provide guidance on optimal tool selection for cognitive and mood assessment both before and after stroke, as well as information on prognosis and natural history of neuropsychological problems in stroke. The study data, neuroimaging and tissue biobank are all available as a resource for future research.

BackgroundDepression is a common post-stroke complication. Pre-stroke depression may be an important contributor, however the epidemiology of pre-stroke depression is poorly understood. Using systematic review and meta-analysis, we described the prevalence of pre-stroke depression and its association with post-stroke depression.MethodsWe searched multiple cross-disciplinary databases from inception to July 2017 and extracted data on the prevalence of pre-stroke depression and its association with post-stroke depression. We assessed the risk of bias (RoB) using validated tools. We described summary estimates of prevalence and summary odds ratio (OR) for association with post-stroke depression, using random-effects models. We performed subgroup analysis describing the effect of depression assessment method. We used a funnel plot to describe potential publication bias. The strength of evidence presented in this review was summarised via ‘GRADE’.ResultsOf 11 884 studies identified, 29 were included (total participantsn= 164 993). Pre-stroke depression pooled prevalence was 11.6% [95% confidence interval (CI) 9.2–14.7]; range: 0.4–24% (I295.8). Prevalence of pre-stroke depression varied by assessment method (p= 0.02) with clinical interview suggesting greater pre-stroke depression prevalence (~17%) than case-note review (9%) or self-report (11%). Pre-stroke depression was associated with increased odds of post-stroke depression; summary OR 3.0 (95% CI 2.3–4.0). All studies were judged to be at RoB: 59% of included studies had an uncertain RoB in stroke assessment; 83% had high or uncertain RoB for pre-stroke depression assessment. Funnel plot indicated no risk of publication bias. The strength of evidence based on GRADE was ‘very low’.ConclusionsOne in six stroke patients have had pre-stroke depression. Reported rates may be routinely underestimated due to limitations around assessment. Pre-stroke depression significantly increases odds of post-stroke depression.Protocol identifierPROSPERO identifier: CRD42017065544

Background and Purpose— There may be a potential to reduce the number of items assessed in the Barthel Index (BI), and shortened versions of the BI have been described. We sought to collate all existing short-form BI (SF-BI) and perform a comparative validation using clinical trial data. Methods— We performed a systematic review across multidisciplinary electronic databases to find all published SF-BI. Our validation used the VISTA (Virtual International Stroke Trials Archive) resource. We describe concurrent validity (agreement of each SF-BI with BI), convergent and divergent validity (agreement of each SF-BI with other outcome measures available in the data set), predictive validity (association of prognostic factors with SF-BI outcomes), and content validity (item correlation and exploratory factor analyses). Results— From 3546 titles, we found 8 articles describing 6 differing SF-BI. Using acute trial data (n=8852), internal reliability suggested redundancy in BI (Cronbach α, 0.96). Each SF-BI demonstrated a strong correlation with BI, modified Rankin Scale, National Institutes of Health Stroke Scale (all ρ≥0.83; P P P Conclusions— There is redundancy in the original BI; we have demonstrated internal and external validity of a 3-item SF-BI that should be simple to use.

Background Delirium is a common severe neuropsychiatric condition secondary to physical illness, which predominantly affects older adults in hospital. Prior to this study, the UK point prevalence of delirium was unknown. We set out to ascertain the point prevalence of delirium across UK hospitals and how this relates to adverse outcomes. Methods We conducted a prospective observational study across 45 UK acute care hospitals. Older adults aged 65 years and older were screened and assessed for evidence of delirium on World Delirium Awareness Day (14th March 2018). We included patients admitted within the previous 48 h, excluding critical care admissions. Results The point prevalence of Diagnostic and Statistical Manual on Mental Disorders, Fifth Edition (DSM-5) delirium diagnosis was 14.7% (222/1507). Delirium presence was associated with higher Clinical Frailty Scale (CFS): CFS 4–6 (frail) (OR 4.80, CI 2.63–8.74), 7–9 (very frail) (OR 9.33, CI 4.79–18.17), compared to 1–3 (fit). However, higher CFS was associated with reduced delirium recognition (7–9 compared to 1–3; OR 0.16, CI 0.04–0.77). In multivariable analyses, delirium was associated with increased length of stay (+ 3.45 days, CI 1.75–5.07) and increased mortality (OR 2.43, CI 1.44–4.09) at 1 month. Screening for delirium was associated with an increased chance of recognition (OR 5.47, CI 2.67–11.21). Conclusions Delirium is prevalent in older adults in UK hospitals but remains under-recognised. Frailty is strongly associated with the development of delirium, but delirium is less likely to be recognised in frail patients. The presence of delirium is associated with increased mortality and length of stay at one month. A national programme to increase screening has the potential to improve recognition.

Full completion of cognitive screening tests can be problematic in the context of a stroke. Our aim was to examine the completion of various brief cognitive screens and explore reasons for untestability. Data were collected from consecutive stroke admissions (May 2016&ndash, August 2018). The cognitive assessment was attempted during the first week of admission. Patients were classified as partially untestable (&ge, 1 test item was incomplete) and fully untestable (where assessment was not attempted, and/or no questions answered). We assessed univariate and multivariate associations of test completion with: age (years), sex, stroke severity (National Institutes of Health Stroke Scale (NIHSS)), stroke classification, pre-morbid disability (modified Rankin Scale (mRS)), previous stroke and previous dementia diagnosis. Of 703 patients admitted (mean age: 69.4), 119 (17%) were classified as fully untestable and 58 (8%) were partially untestable. The 4A-test had 100% completion and the clock-draw task had the lowest completion (533/703, 76%). Independent associations with fully untestable status had a higher NIHSS score (odds ratio (OR): 1.18, 95% CI: 1.11&ndash, 1.26), higher pre-morbid mRS (OR: 1.28, 95% CI: 1.02&ndash, 1.60) and pre-stroke dementia (OR: 3.35, 95% CI: 1.53&ndash, 7.32). Overall, a quarter of patients were classified as untestable on the cognitive assessment, with test incompletion related to stroke and non-stroke factors. Clinicians and researchers would benefit from guidance on how to make the best use of incomplete test data.

Objective:We aimed to determine prevalence of pre-stroke frailty in acute stroke and describe validity of a Frailty Index–based assessment.Design:Cross-sectional.Setting:Single UK urban teaching hospital.Subjects:Consecutive acute stroke unit admissions, recruited in four waves (May 2016–August 2018). We performed the assessments within first week and attempted to include all admissions.Main measures:Our primary measure was a Frailty Index, based on cumulative disorders. A proportion of participants were also assessed with the ‘Frail non-disabled’ questionnaire. We evaluated concurrent validity of Frailty Index against variables associated with frailty in non-stroke populations. We described predictive validity of Frailty Index for stroke severity and delirium. We described convergent validity, quantifying agreement between frailty assessments and a measure of pre-stroke disability (modified Rankin Scale) using kappa statistics and correlations.Results:We included 546 patients. A Frailty Index–defined frailty syndrome was observed in 427 of 545 patients (78%), of whom, 151 (28%) had frank frailty and 276 (51%) were pre-frail. Phenotypic frailty was observed in 72 of 258 patients (28%). We demonstrated concurrent validity via significant associations with all variables (all p Conclusion:Frailty is present in around one in four patients with acute stroke; if pre-frailty is included, then a frailty syndrome is seen in three out of four patients. The Frailty Index is a valid measure of frailty in stroke; however, there is little agreement between this scale and other measurements of frailty.

Objective: Post-stroke cognitive impairment is common, but mechanisms and risk factors are poorly understood. Frailty may be an important risk factor for cognitive impairment after stroke. We investigated the association between pre-stroke frailty and acute post-stoke cognition. Methods: We studied consecutively admitted acute stroke patients in a single urban teaching hospital during three recruitment waves between May 2016 and December 2017. Cognition was assessed using the Mini-Montreal Cognitive Assessment (min=0; max=12). A Frailty Index was used to generate frailty scores for each patient (min=0; max=100). Clinical and demographic information were collected, including pre-stroke cognition, delirium, and stroke-severity. We conducted univariate and multiple-linear regression analyses with covariates forced in (covariates included were: age, sex, stroke severity, stroke-type, pre-stroke cognitive impairment, delirium, previous stroke/transient ischemic attack) to investigate the association between pre-stroke frailty and post-stroke cognition. Results: Complete data were available for 154 stroke patients. Mean age was 68 years (SD=11; range=32–97); 93 (60%) were male. Median mini-Montreal Cognitive Assessment score was 8 (IQR=4–12). Mean Frailty Index score was 18 (SD=11). Pre-stroke cognitive impairment was apparent in 13/154 (8%) patients. Pre-stroke frailty was significantly associated with lower post-stroke cognition (Standardized-Beta=−0.40; pConclusions: Pre-stroke frailty may be a moderator of post-stroke cognition, independent of other well-established post-stroke cognitive impairment risk factors. (JINS, 2019, 25, 501–506)

We applaud Dr. Gumbinger et al.1 for examining thrombolysis outcomes in a stroke population with premorbid disability. Stroke patients with prevalent disability have traditionally been excluded from trials. However, the proportion of older adult stroke with prestroke impairments is substantial, and the optimal management of this group requires more consideration.2 The study challenges the perception that prestroke disability precludes benefit from intervention and makes a call for more research in this patient group.

A measure of treatment effect is needed to assess the utility of any novel intervention in acute stroke. For a potentially disabling condition such as stroke, outcomes of interest should include some measure of functional recovery. There are many functional outcome assessments that can be used after stroke. In this narrative review, we discuss exemplars of assessments that describe impairment, activity, participation, and quality of life. We will consider the psychometric properties of assessment scales in the context of stroke trials, focusing on validity, reliability, responsiveness, and feasibility. We will consider approaches to the analysis of functional outcome measures, including novel statistical approaches. Finally, we will discuss how advances in audiovisual and information technology could further improve outcome assessment in trials.

Background and Purpose:The modified Rankin Scale (mRS) was designed to measure post-stroke recovery but is often used to describe pre-stroke disability. We sought to evaluate three aspects of pre-stroke mRS:validity as a measure of pre-stroke disability; prognostic accuracy and association of pre-stroke mRS scores and process of care.\ud \ud Methods:We used data from a large, UK clinical registry. For analysis of validity we compared pre-stroke mRS against other markers of pre-stroke function (age, comorbidity index, care needs). For analysis of prognostic accuracy we described univariable and multivariable models comparing pre-stroke mRS and other prognostic variables against a variety of outcomes (early and late mortality; length of stay; institutionalisation; incident complications). Finally, we described association of pre-stroke mRS and components of evidence-based stroke care (early neuroimaging, admission to stroke unit, assessment of swallow).\ud \ud Results:We analysed data of 2491 stroke patients. Concurrent validity analyses suggested statistically significant, but modest correlations between pre-stroke mRS and chosen variables (rho>0.40; p

Introduction: Guidelines recommend screening all stroke admissions for cognitive impairment. Delirium may be an important contributor to cognitive problems, but available data are limited by potential selection biases and imperfect delirium assessment. We aimed to describe robust estimates of delirium occurrence (incidence and prevalence) and risk factors in an acute stroke unit (ASU). Methods: We collected data from sequential admissions to our University Hospital ASU over a 20 week period (Feb-July 2016). The only exclusion was where the clinical team felt that any form of assessment was inappropriate. We aimed to perform cognitive assessments at 48 hours post stroke. Cognitive assessments were based on mini Montreal Cognitive Assessment (m-MoCA) and GP-Cog informant interview to assess for pre-stroke dementia. We assessed for delirium based on DSM-V criteria. We described univariable and multivariable associations with delirium occurrence. Results: Across the study period, 184 strokes were admitted; median age 71 years (IQR:61-79). Some form of cognitive assessment was available for 178 (97%). In total. 152 had evidence of cognitive impairment on m-MOCA, 55 (31%) met criteria for delirium and 25 (15%) had pre-stroke dementia. Significant univariable associations with delirium were:age and pre-existing cognitive decline. On logistic regression:age, history of drug or alcohol misuse and pre-stroke mRS were all independently associated with delirium. Discussion: In an unselected ASU population a substantial proportion will have cognitive impairment based on screening. Delirium is common and contributes to this cognitive problems seen in acute stroke. Independent associations with delirium occurrence were identified but were non-modifiable. Our results have implications for policy and practice. As post-stroke cognitive impairment is multifactorial, screening delirium and pre-existing cognitive issues should form part of the initial assessment.