Functional assessment for acute stroke trials: properties, analysis, and application

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

Psychological problems in stroke: prevalence, risk factors, and assessment in the pre-stroke state

Background: The psychological impact of stroke is well recognised as being of clinical importance. Historically, this field has received less attention than the physical consequences of stroke, but work designed to develop our understanding of post-stroke psychology is now well underway. Much of the current research of post-stroke psychology is overly limited however; little attention has been paid to the potential impact of the pre-stroke state on post-stroke psychology. As a consequence, fundamental information in relation to the pre-stroke state is lacking, ranging from the prevalence and relevant risk associations of various psychological and physical conditions, to the validity and optimal use of pre-stroke state assessment methods. The purpose of this thesis is to improve our understanding of the pre-stroke state in relation to these under-researched areas. Method: I conducted a series of studies designed to improve our understanding of the pre-stroke state in the areas of prevalence, risk association, and method of assessment. Specifically, I conducted a diagnostic test accuracy study to evaluate the psychometric properties of two informant questionnaires that can be used to assess pre-stroke cognition: the Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) and Acquired Dementia 8 (AD8). I conducted a systematic review and meta-analyses to establish pre-stroke depression prevalence and investigate its association with post-stroke depression. Based on the findings of this, I explored the potential use of informant tools for pre-stroke depression assessment by comparing the diagnostic test accuracy of the Stroke Aphasic Depression Questionnaire (SADQ) against the Geriatric Depression Scale (GDS), and the diagnostic test accuracy of the best performing informant questionnaire against that of medical records. I conducted secondary analysis of existing data held in two databases to investigate pre-stroke functioning and pre-stroke frailty. The Anglia Stroke Clinical Network Evaluation Study database was utilised to assess the validity of the pre-stroke modified Rankin Scale (mRS) as a measure of function and explore if reported predictive validity of the tool could be influenced by differences in post-stroke care pathway. The Glasgow Royal Infirmary research database was used to investigate the prevalence of pre-stroke frailty, the validity of a Frailty Index for pre-stroke frailty assessment, and a risk association between pre-stroke frailty and acute post-stroke cognition. Findings: I found that the IQCODE and AD8 are valid tools for assessing pre-stroke cognition. However, when utilised at recommended published cut-points the IQCODE is more specific, while the AD8 is more sensitive to cognitive impairment. There is also potential that application of differing cut-points could improve performance when used in a pre-stroke context. My systematic review and meta-analysis suggested that pre-stroke depression prevalence is around 17% and its presence significantly increases odds of post-stroke depression. In addition, there is evidence that the most commonly used method to assess pre-stroke depression, patient medical records, is likely to lack sensitivity to pre-stroke depression. I explored the use of the SADQ and GDS informant tools for assessment of pre-stroke depression. I found that both tools are valid measures of pre-stroke depression, but the GDS has favourable diagnostic test accuracy properties in comparison to the SADQ; comparative test accuracy performance with medical records is inconclusive, but seems to favour the GDS. Pre-stroke mRS evaluation suggests it has moderate validity as a measure of pre-stroke functioning and has predictive validity that could not be accounted for by differences in care pathway. Pre-stroke frailty prevalence is around 28%, rising to ~80% if the pre-frailty state is considered, and the Frailty Index is a valid measure of pre-stroke frailty that can be completed in almost all stroke patients. Pre-stroke frailty also has an association with lower acute post-stroke cognition that is independent of other established risk factors. Conclusions: In conclusion these findings develop our overall understanding of the pre-stroke state. The IQCODE and AD8 are both valid tools for assessment of pre-stroke cognition; however, they demonstrate contrasting strengths when employed at their recommended cut-points and these cut-points may not be the most optimal when these tools are utilised for pre-stroke assessment. Pre-stroke depression appears prevalent, existing in around one in six stroke patients, and it increases the odds of patients experiencing post-stroke depression. It is possible that informant assessment for detection of pre-stroke depression can outperform patient medical records and the GDS appears to outperform the SADQ in the pre-stroke context; however further work is required to confirm this. The pre-stroke mRS is a valid measure of function but has only moderate validity overall and may not be ideally suited to assessment of function in a pre-stroke context. Pre-stroke frailty may exist in around one quarter of stroke patients, and utilisation of a Frailty index approach appears to be valid. The presence of pre-stroke frailty may also contribute to the poor cognitive performance often observed in patients following acute stroke based on an independent association with lower cognitive performance; hence identification of pre-stroke frailty could be of importance to our understanding of post-stroke psychology

Use of a 3-item short-form version of the Barthel Index for use in stroke: systematic review and external validation

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<0.001). Using rehabilitation trial data (n=332), SF-BI demonstrated modest correlation with quality of life measures Stroke Impact Scale and 5 domain EuroQOL (ρ≥0.50, P<0.001). Prespecified prognostic factors were associated with SF-BI outcomes (all P<0.001). Our factor analysis described a 3 factor structure, and item reduction suggested an optimal 3-item SF-BI comprising bladder control, transfer, and mobility items in keeping with 1 of the 3-item SF-BI previously described in the literature. 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

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

Peer reviewedPublisher PD

Anticholinergic burden measures and older people's falls risk : a systematic prognostic review.

Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Dunhill Medical Trust (grant number RPGF1806/66). Acknowledgements We thank Ms Kaisa Yrjana and Ms Mitrysha Kishor greatly for their help during the study search and screening phases of this review.Peer reviewedPublisher PD

Who is classified as untestable on brief cognitive screens in an acute stroke setting?

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–August 2018). The cognitive assessment was attempted during the first week of admission. Patients were classified as partially untestable (≥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: 1.11–1.26), higher pre-morbid mRS (OR: 1.28, 95% CI: 1.02–1.60) and pre-stroke dementia (OR: 3.35, 95% CI: 1.53–7.32). 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

Prevalence of pre-stroke depression and its association with post-stroke depression: a systematic review and meta-analysis

Background: Depression 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. Methods: We 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’. Results: Of 11 884 studies identified, 29 were included (total participants n = 164 993). Pre-stroke depression pooled prevalence was 11.6% [95% confidence interval (CI) 9.2–14.7]; range: 0.4–24% (I2 95.8). 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’. Conclusions: One 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 identifier: PROSPERO identifier: CRD42017065544

Informant-based screening tools for dementia: an overview of systematic reviews

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

Cardiovascular risk factors indirectly affect acute post-stroke cognition through stroke severity and prior cognitive impairment: A moderated mediation analysis

Abstract: 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

The prevalence of frailty amongst acute stroke patients, and evaluation of method of assessment

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 < 0.01). We demonstrated predictive validity for stroke severity and delirium (p < 0.01). Agreement between the frailty measures was poor (kappa = –0.06) and convergent validity was moderate (Frail non-disabled ‘Cramer’s V’ = 0.25; modified Rankin Scale ‘Cramer’s V’ = 0.47). 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