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: 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.
Authors: Henry de Berker; Archy de Berker; Htin Aung; Pedro Duarte; Salman Mohammed; Hamsaraj Shetty; Tom Hughes Journal: Clin Med (Lond) Date: 2021-03 Impact factor: 2.659
Authors: Nathan J Reinert; Bansri M Patel; Qasem N AlShaer; Liwen Wu; Stephen Wisniewski; Eric S Hager; Mitchell R Dyer; Parthasarathy D Thirumala Journal: Neurologist Date: 2021-11-30 Impact factor: 1.398
Authors: Jennifer K Burton; Jennifer Stewart; Mairi Blair; Sinead Oxley; Amy Wass; Martin Taylor-Rowan; Terence J Quinn Journal: Age Ageing Date: 2022-03-01 Impact factor: 12.782
Authors: Nicholas R Evans; Oliver M Todd; Jatinder S Minhas; Patricia Fearon; George W Harston; Jonathan Mant; Gillian Mead; Jonathan Hewitt; Terence J Quinn; Elizabeth A Warburton Journal: Int J Stroke Date: 2021-08-04 Impact factor: 5.266