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<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<0.001), pre-stroke cognitive impairment (Unstandardized-Beta=-2.28; p=0.001), and stroke-severity (Unstandardized-Beta=-0.20; p<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).
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 strokepatients 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 strokepatients. 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).
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: Caglar Cosarderelioglu; Lolita S Nidadavolu; Claudene J George; Esther S Oh; David A Bennett; Jeremy D Walston; Peter M Abadir Journal: Front Neurosci Date: 2020-09-30 Impact factor: 4.677
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