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Background: There is increasing interest in the concept of frailty in stroke, including both physical frailty and imaging-evidence of brain frailty. We aimed to establish the prevalence of brain frailty in stroke survivors as well as the concurrent and predictive validity of various frailty measures against long-term cognitive outcomes., Methods: We included consecutively admitted stroke or transient ischaemic attack (TIA) survivors from participating stroke centres. Baseline CT scans were used to generate an overall brain frailty score for each participant. We measured frailty via the Rockwood frailty index, and a Fried frailty screening tool. Presence of major or minor neurocognitive disorder at 18-months following stroke or TIA was established via a multicomponent assessment. Prevalence of brain frailty was established based upon observed percentages within groups defined by frailty status (robust, pre-frail, frail). We assessed the concurrent validity of brain frailty and frailty scales via Spearman's rank correlation. We conducted multivariable logistic regression analyses, controlling for age, sex, baseline education and stroke severity, to evaluate association between each frailty measure and 18-month cognitive impairment., Results: Three-hundred-forty-one stroke survivors participated. Three-quarters of people who were frail had moderate-severe brain frailty and prevalence increased according to frailty status. Brain frailty was weakly correlated with Rockwood frailty (Rho: 0.336; p  < 0.001) and with Fried frailty (Rho: 0.230; p  < 0.001). Brain frailty (OR: 1.64, 95% CI = 1.17-2.32), Rockwood frailty (OR: 1.05, 95% CI = 1.02-1.08) and Fried frailty (OR: 1.93, 95% CI = 1.39-2.67) were each independently associated with cognitive impairment at 18 months following stroke., Conclusions: There appears to be value in the assessment of both physical and brain frailty in patients with ischaemic stroke and TIA. Both are associated with adverse cognitive outcomes and physical frailty remains important when assessing cognitive outcomes., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objectives: 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., Methods: 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., Results: 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)., Conclusions: 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., (© 2022 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.)

Background: frailty is common in older adults and associated with poor outcomes following illness. Although stroke is predominantly a disease of older people, our knowledge of frailty in stroke is limited. We aimed to collate the literature on acute stroke and frailty to estimate the prevalence of pre-stroke frailty and its associations with outcomes., Methods: paired researchers searched multidisciplinary electronic databases for papers describing frailty and acute stroke. We assessed risk of bias using Newcastle-Ottawa tools appropriate to study design. We created summary estimates of pre-stroke frailty using random effects models. We collated whether studies reported significant positive associations between frailty and clinical outcomes in adjusted models., Results: we included 14 studies (n = 27,210 participants). Seven studies (n = 8,840) used a frailty index approach, four studies (n = 14,924) used Hospital Frailty Risk Scores. Pooled prevalence of pre-stroke frailty was 24.6% (95% confidence interval, CI: 16.2-33.1%; low quality evidence, downgraded due to heterogeneity, bias). Combining frailty and pre-frailty (nine studies, n = 23,827), prevalence of any frailty syndrome was 66.8% (95%CI: 49.9-83.7%). Seven studies were at risk of bias, from participant selection or method of frailty assessment. Pre-stroke frailty was associated with all adverse outcomes assessed, including longer-term mortality (positive association in 6 of 6 studies reporting this outcome; odds ratio: 3.75 [95%CI: 2.41-5.70]), length of admission (3 of 4 studies) and disability (4 of 6 studies)., Conclusions: despite substantial heterogeneity, whichever way it is measured, frailty is common in patients presenting with acute stroke and associated with poor outcomes. This has implications for the design of stroke services and pathways., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Introduction: Mechanical thrombectomy (MT) can improve outcomes following ischaemic stroke. Patient selection for MT is predominantly based on physiological and imaging parameters. We assessed whether people living with pre-stroke frailty had differing outcomes following MT., Methods: We included consecutive patients undergoing MT at a UK comprehensive stroke centre. We calculated a cumulative deficits frailty index to identify pre-stroke frailty in those patients presenting directly to the centre. Frailty was defined as an index score ≥ 0.24. We assessed univariable and multivariable association between pre-stroke frailty and stroke outcomes. Our primary outcomes were modified Rankin Scale (mRS) and mortality at 90 days., Results: Of 175 patients who underwent MT (2014-2018), we identified frailty in 49 (28%). Frail and non-frail patients had similar rates of thrombolysis administration, successful recanalization and onset to recanalization times. Those with pre-stroke frailty had higher 24 hour National Institutes of Health Stroke Scale (12(IQR: 8-17) versus 3(IQR: 2-13); P = 0.001); were less likely to be independent (mRS 0-2: 18% versus 61%; P < 0.001) and more likely to die (47% versus 14%; P < 0.001) within 90 days. Adjusting for age, baseline NIHSS and thrombolysis, frailty remained a strong, independent predictor of poor clinical outcome at 90 days (Death OR: 3.12 (95% CI: 1.32-7.4); dependency OR: 3.04 (95%CI: 1.10-8.44). Age was no longer a predictor of outcome when adjusted for frailty., Conclusion: Pre-stroke frailty is prevalent in real-world patients eligible for MT and is an important predictor of poor outcomes. Routine assessment of pre-stroke frailty could help decision-making around patient selection for MT., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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.

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; p&lt;0.001) and this association was independent of covariates (Unstandardized-Beta=-0.05; p=0.005). Additional significant variables in the multiple regression model were age (Unstandardized-Beta=-0.05; p=0.002), delirium (Unstandardized-Beta=-2.81; p&lt;0.001), pre-stroke cognitive impairment (Unstandardized-Beta=-2.28; p=0.001), and stroke-severity (Unstandardized-Beta=-0.20; p&lt;0.001)., Conclusions: 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).