Hostname: page-component-745bb68f8f-grxwn Total loading time: 0 Render date: 2025-01-14T04:36:50.809Z Has data issue: false hasContentIssue false
  • English
  • Français

Pre-Stroke Frailty Is Independently Associated With Post-Stroke Cognition: A Cross-Sectional Study

Published online by Cambridge University Press:  01 March 2019

Martin Taylor-Rowan Open the ORCID record for Martin Taylor-Rowan [Opens in a new window] ,
Ruth Keir ,
Gillian Cuthbertson ,
Robert Shaw ,
Bogna Drozdowska ,
Emma Elliott ,
Jonathan Evans ,
David Stott  and
Terence J. Quinn
Martin Taylor-Rowan*
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Ruth Keir
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Gillian Cuthbertson
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Robert Shaw
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Bogna Drozdowska
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Emma Elliott
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Jonathan Evans
Affiliation:
Institute of Health and Wellbeing, University of Glasgow, UK
David Stott
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
Terence J. Quinn
Affiliation:
Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
*
Correspondence and reprint requests to: Martin Taylor-Rowan, Institute of Cardiovascular and Medical Sciences, University of Glasgow, 8-16 Alexandra Parad, New Lister Building, Glasgow Royal Infirmary, Glasgow, UK G4 0SF. E-mail: m.taylor-rowan.1@research.gla.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

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)

Keywords

StrokeFrailtyCognitionRiskEtiologyCerebrovascular
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 25 , Issue 5 , May 2019 , pp. 501 - 506
Copyright
Copyright © The International Neuropsychological Society 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Bamford, J., Sandercock, P., Dennis, M., Burn, J., & Warlow, C. (1991). Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet, 337, 1521–1526.CrossRefGoogle ScholarPubMed
Brodaty, H., Pond, D., Kemp, N.M., Luscombe, G., Harding, L., Berman, K., & Huppert, F.A. (2002). The GPCOG: A new screening test for dementia designed for general practice. JAGS, 50(3), 530–534.CrossRefGoogle ScholarPubMed
Brott, T., Adams, H.P. Jr., Olinger, C.P., Marler, J.R., Barsan, W.G., Biller, J., Spilker, J., Holleran, R., Eberle, R. & Hertzberg, V. (1989). Measurements of acute cerebral infarction: A clinical examination scale. Stroke, 20(7), 864–870.CrossRefGoogle ScholarPubMed
Desmond, D.W., Moroney, J.T., Paik, M.C., Sano, M., Mohr, J.P., Aboumatar, S., Tseng, C.L., Chan, S., Williams, J.B., Remien, R.H., Hauser, W.A. & Stern, Y. (2000). Frequency and clinical determinants of dementia after ischemic stroke. Neurology, 54(5), 1124–1131.CrossRefGoogle ScholarPubMed
Faul, F., Erdfelder, E., Lang, A.G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191.CrossRefGoogle ScholarPubMed
Fried, L.P., Tangen, C.M., Walston, J., Newman, A.B., Hirsch, C., Gottdiener, J.Seeman, T., Tracy, R., Kop, W.J., Burke, G., & McBurnie, M.A.; Cardiovascular Health Study Collaborative Research Group. (2001). Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: Evidence for a phenotype. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 56(3), 146–156.CrossRefGoogle ScholarPubMed
Jefferson, A.L., Massaro, J.M., Wolf, P.A., Seshadri, S., Au, R., Vasan, R.S., Larson, M.G., Meigs, J.B., Keaney, J.F., Jr, Lipinska, I., Kathiresan, S., Benjamin, E.J. & DeCarli, C. (2007). Inflammatory biomarkers are associated with total brain volume: The Framingham Heart Study. Neurology, 68(13), 1032–1038.CrossRefGoogle ScholarPubMed
Jokinen, H., Melkas, S., Ylikoski, R., Pohjasvaara, T., Kaste, M., Erkinjuntti, T., & Hietanen, M. (2015). Post‐stroke cognitive impairment is common even after successful clinical recovery. European Journal of Neurology, 22(9), 1288–1294.CrossRefGoogle ScholarPubMed
Kasner, S.E., Chalela, J.A., Luciano, J.M., Cucchiara, B.L., Raps, E.C., McGarvey, M.L., Conroy, M.B., Conroy, M.B., Localio A.R. (1999). Reliability and validity of estimating the NIH stroke scale score from medical records. Stroke, 30(8), 1534–1537.CrossRefGoogle ScholarPubMed
Kojima, G., Taniguchi, Y., Iliffe, S., Walters, K. (2016). Frailty as a predictor of Alzheimer disease, vascular dementia, and all dementia among community-dwelling older people: A systematic review and meta-analysis. Journal of the American Medical Directors Association, 17(10), 881–888.CrossRefGoogle ScholarPubMed
Leys, D., Henon, H., Mackowiak-Cordoliani, M.A., Pasquier, F. (2005). Post-stroke dementia. Lancet Neurology, 4(11), 752–759.CrossRefGoogle Scholar
Makin, S.D., Turpin, S., Dennis, M.S., & Wardlaw, J.M. (2013). Cognitive impairment after lacunar stroke: Systematic review and meta-analysis of incidence, prevalence and comparison with other stroke subtypes. Journal of Neurology Neurosurgery and Psychiatry, 84(8), 893–900.CrossRefGoogle ScholarPubMed
Mitnitski, A., Fallah, N., & Rockwood, K. (2011). A multistate model of cognitive dynamics in relation to frailty in older adults. Annals of Epidemiology, 21(7), 507–516.CrossRefGoogle ScholarPubMed
Nasreddine, Z.S., Phillips, N.A., Bédirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J.L.& Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699.Google Scholar
Pendlebury, S.T. & Rothwell, P.M. (2009). Prevalence, incidence, and factors associated with pre-stroke and post-stroke dementia: A systematic review and meta-analysis. Lancet Neurology, 8(11), 1006–1018.CrossRefGoogle ScholarPubMed
Quinlan, N., Marcantonio, E.R., Inouye, S.K., Gill, T.M., Kamholz, B., & Rudolph, J.L. (2011). Vulnerability: The crossroads of frailty and delirium. Journal of the American Geriatrics Society, 59(Suppl 2), S262–S268.CrossRefGoogle ScholarPubMed
Robertson, D.A., Savva, G.M., & Kenny, R.A. (2013). Frailty and cognitive impairment—A review of the evidence and causal mechanisms. Ageing Research Reviews, 12, 840–851.CrossRefGoogle ScholarPubMed
Robertson, I.H., Ridgeway, V., Greenfield, E., & Parr, A. (1997). Motor recovery after stroke depends on intact sustained attention: A 2-year follow-up study. Neuropsychology, 11(2), 290.CrossRefGoogle ScholarPubMed
Rockwood, K., Andrew, M., & Mitniski, A. (2007). A comparison of two approaches to measuring frailty in elderly people. The Journals of Gerontology, Series A, Biological Sciences and Medical Sciences, 62(7), 738–743.CrossRefGoogle ScholarPubMed
Rockwood, K. & Mitnitski, A. (2012). How might deficit accumulation give rise to frailty? The Journal of Frailty and Aging, 1(1), 8–12.Google ScholarPubMed
Rockwood, K., Mitnitski, A.B., & Macknight, C. (2002). Some mathematical models of frailty and their clinical implications. Reviews in Clinical Gerontology, 12, 109–117.CrossRefGoogle Scholar
Riley, R.D., Sauerbrei, W., & Altman, D.G. (2009). Prognostic markers in cancer: The evolution of evidence from single studies to meta-analysis, and beyond. British Journal of Cancer, 100(8), 1219–1229.CrossRefGoogle ScholarPubMed
Searle, S.D., Mitniski, A., Gahbauer, E.A., Gill, T.M., & Rockwood, K. (2008). A standard procedure for creating a frailty index. BioMed Central Geriatrics, 8, 24.Google ScholarPubMed
Skidmore, E.R., Whyte, E.M., Holm, M.B., Becker, J.T., Butters, M.A., Dew, M.A., Munin, M.C. & Lenze, E.J. (2010). Cognitive and affective predictors of rehabilitation participation after stroke. Archives of Physical Medicine and Rehabilitation, 91(2), 203–207.CrossRefGoogle ScholarPubMed
Solfrizzi, V., Scafato, E., Frisardi, V., Seripa, D., Logroscino, G., Maggi, S., Imbimbo, B.P., Galluzzo, L., Baldereschi, M., Gandin, C., Di Carlo, A., Inzitari, D., Crepaldi, G., Pilotto, A. & Panza, F.; Italian Longitudinal Study on Aging Working Group. (2013). Frailty syndrome and the risk of vascular dementia: The Italian Longitudinal Study on Aging. Alzheimer’s and Dementia, 9(2), 113–122.CrossRefGoogle ScholarPubMed
Song, X., Mitnitski, A., & Rockwood, K. (2014). Age-related deficit accumulation and the risk of late-life dementia. Alzheimer’s Research and Therapy, 6(5-8), 54.CrossRefGoogle ScholarPubMed
Soong, J., Poots, A.J., Scott, S., Donald, K., Woodcock, T., Lovett, D., & Bell, D. (2015). Quantifying the prevalence of frailty in English hospitals. BMJ Open, 5, e008456.CrossRefGoogle ScholarPubMed
Stern, Y. (2002). What is cognitive reserve? Theory and research application of the reserve concept. Journal of the International Neuropsychological Society, 8, 448–460.CrossRefGoogle ScholarPubMed
Sun, J.H., Tan, L., & Yu, J.T. (2014). Post-stroke cognitive impairment: Epidemiology, mechanisms and management. Annals of Translational Medicine, 2, 80.Google ScholarPubMed
Theou, O., Brothers, T., Mitniski, A., & Rockwood, K. (2013). Operationalization of frailty using eight commonly used scales and comparison of their ability to predict all-cause mortality. Journal of the American Geriatric Society, 61, 1537–1551.CrossRefGoogle ScholarPubMed
Verloo, H., Goulet, C., Morin, D., & von Gunten, A. (2016). Association between frailty and delirium in older adult patients discharged from hospital. Clinical Interventions in Aging, 18(11), 55–63.CrossRefGoogle Scholar
von Elm, E., Altman, D.G., Egger, M., Pocock, S.J., Gotzsche, P.C., & Vandenbroucke, J.P. (2007). Strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. BMJ, 335, 806.CrossRefGoogle Scholar
Williams, L.S., Yilmaz, E.Y., & Lopez-Yunez, A.M. (2000). Retrospective assessment of initial stroke severity with the National Institutes of Health Stroke Scale. Stroke, 31(4), 858–862.CrossRefGoogle Scholar
Supplementary material: File

Taylor-Rowan et al. supplementary material

Taylor-Rowan et al. supplementary material 1

Download Taylor-Rowan et al. supplementary material(File)
File 93.8 KB