open access

Vol 55, No 2 (2021)
Research Paper
Submitted: 2020-10-17
Accepted: 2020-12-14
Published online: 2021-01-25
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Prevalence of cognitive impairment in acute ischaemic stroke and use of Alberta Stroke Programme Early CT Score (ASPECTS) for early prediction of post-stroke cognitive impairment

Ahmed Esmael1, Mohammed Elsherief1, Khaled Eltoukhy1
·
Pubmed: 33507530
·
Neurol Neurochir Pol 2021;55(2):179-185.
Affiliations
  1. Neurology Department, Faculty of Medicine, Mansoura University, 35516 mansoura, Egypt

open access

Vol 55, No 2 (2021)
Research papers
Submitted: 2020-10-17
Accepted: 2020-12-14
Published online: 2021-01-25

Abstract

Aim of the study. This study aims to assess the prevalence of post-stroke cognitive impairment, and to evaluate the correlation of ASPECTS with impaired cognition. Materials and methods. 150 patients presenting with acute middle cerebral artery territory ischaemic stroke were included in this study. Risk factors of ischaemic stroke and the initial NIHSS were determined. An initial and a follow-up non-contrast CT brain were carried out after seven days which were assessed by ASPECTS. The prevalence of cognitive impairment was determined by MoCA during the follow up of patients after three months. Correlations of ASPECTS, NIHSS and MoCA were done by Spearman correlation. Multivariate logistic regression analysis was carried out for the independent variables of cognitive impairment. Results. The prevalence of post-stroke cognitive impairment in this study, according to the threshold for cognitive impairment with a MoCA score of 25 or less, was 25.3% (38 patients). Significant positive correlations between ASPECTS and total MoCA test domains were found (r = 0.73 and P = 0.002). Logistic regression analysis demonstrated that the independent factors associated with cognitive impairment were older age, certain domains of the MoCA test like executive functions, memory, attention, language, NIHSS, HTN, and ASPECTS. Conclusions and clinical implications. There is a prevalence of cognitive impairment in about 25% of patients after three months of follow-up in cases with acute ischaemic stroke. ASPECTS is directly correlated with cognitive impairment, and may be considered as a biomarker of post-stroke cognitive impairment.

Abstract

Aim of the study. This study aims to assess the prevalence of post-stroke cognitive impairment, and to evaluate the correlation of ASPECTS with impaired cognition. Materials and methods. 150 patients presenting with acute middle cerebral artery territory ischaemic stroke were included in this study. Risk factors of ischaemic stroke and the initial NIHSS were determined. An initial and a follow-up non-contrast CT brain were carried out after seven days which were assessed by ASPECTS. The prevalence of cognitive impairment was determined by MoCA during the follow up of patients after three months. Correlations of ASPECTS, NIHSS and MoCA were done by Spearman correlation. Multivariate logistic regression analysis was carried out for the independent variables of cognitive impairment. Results. The prevalence of post-stroke cognitive impairment in this study, according to the threshold for cognitive impairment with a MoCA score of 25 or less, was 25.3% (38 patients). Significant positive correlations between ASPECTS and total MoCA test domains were found (r = 0.73 and P = 0.002). Logistic regression analysis demonstrated that the independent factors associated with cognitive impairment were older age, certain domains of the MoCA test like executive functions, memory, attention, language, NIHSS, HTN, and ASPECTS. Conclusions and clinical implications. There is a prevalence of cognitive impairment in about 25% of patients after three months of follow-up in cases with acute ischaemic stroke. ASPECTS is directly correlated with cognitive impairment, and may be considered as a biomarker of post-stroke cognitive impairment.

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Keywords

stroke, Alberta Stroke Programme Early CT Score, National Institutes of Health Stroke Scale, cognitive impairment

About this article
Title

Prevalence of cognitive impairment in acute ischaemic stroke and use of Alberta Stroke Programme Early CT Score (ASPECTS) for early prediction of post-stroke cognitive impairment

Journal

Neurologia i Neurochirurgia Polska

Issue

Vol 55, No 2 (2021)

Article type

Research Paper

Pages

179-185

Published online

2021-01-25

Page views

2053

Article views/downloads

936

DOI

10.5603/PJNNS.a2021.0006

Pubmed

33507530

Bibliographic record

Neurol Neurochir Pol 2021;55(2):179-185.

Keywords

stroke
Alberta Stroke Programme Early CT Score
National Institutes of Health Stroke Scale
cognitive impairment

Authors

Ahmed Esmael
Mohammed Elsherief
Khaled Eltoukhy

References (44)
  1. GBD 2016 Neurology Collaborators, GBD 2016 Stroke Collaborators. Global, regional, and national burden of stroke, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019; 18(5): 439–458.
  2. Kalaria RN, Akinyemi R, Ihara M. Stroke injury, cognitive impairment and vascular dementia. Biochim Biophys Acta. 2016; 1862(5): 915–925.
  3. Jacova C, Pearce LA, Roldan AM, et al. Cognitive impairment in lacunar strokes: the SPS3 trial. Ann Neurol. 2012; 72(3): 351–362.
  4. Nakling AE, Aarsland D, Næss H, et al. Cognitive Deficits in Chronic Stroke Patients: Neuropsychological Assessment, Depression, and Self-Reports. Dement Geriatr Cogn Dis Extra. 2017; 7(2): 283–296.
  5. Schaapsmeerders P, Tuladhar AM, Arntz RM, et al. Long-term cognitive impairment after first-ever ischemic stroke in young adults. Stroke. 2013; 44(6): 1621–1628.
  6. Nys GMS, van Zandvoort MJE, de Kort PLM, et al. Restrictions of the Mini-Mental State Examination in acute stroke. Arch Clin Neuropsychol. 2005; 20(5): 623–629.
  7. Pendlebury ST, Cuthbertson FC, Welch SJV, et al. Underestimation of cognitive impairment by Mini-Mental State Examination versus the Montreal Cognitive Assessment in patients with transient ischemic attack and stroke: a population-based study. Stroke. 2010; 41(6): 1290–1293.
  8. Bour A, Rasquin S, Boreas A, et al. How predictive is the MMSE for cognitive performance after stroke? J Neurol. 2010; 257(4): 630–637.
  9. Fanning JP, Wong AA, Fraser JF. The epidemiology of silent brain infarction: a systematic review of population-based cohorts. BMC Med. 2014; 12: 119.
  10. Hsieh YC, Seshadri S, Chung WT, et al. Formosa Stroke Genetic Consortium (FSGC). Association between genetic variant on chromosome 12p13 and stroke survival and recurrence: a one year prospective study in Taiwan. J Biomed Sci. 2012; 19: 1.
  11. Riverol M, López OL. Biomarkers in Alzheimer's disease. Front Neurol. 2011; 2: 46.
  12. Schröder J, Thomalla G. A Critical Review of Alberta Stroke Program Early CT Score for Evaluation of Acute Stroke Imaging. Front Neurol. 2016; 7: 245.
  13. Pexman JH, Barber PA, Hill MD, et al. Use of the Alberta Stroke Program Early CT Score (ASPECTS) for assessing CT scans in patients with acute stroke. AJNR Am J Neuroradiol. 2001; 22(8): 1534–1542.
  14. Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005; 53(4): 695–699.
  15. Tan Jp, Li N, Gao J, et al. Optimal cutoff scores for dementia and mild cognitive impairment of the Montreal Cognitive Assessment among elderly and oldest-old Chinese population. J Alzheimers Dis. 2015; 43(4): 1403–1412.
  16. Potocnik J, Ovcar Stante K, Rakusa M. The validity of the Montreal cognitive assessment (MoCA) for the screening of vascular cognitive impairment after ischemic stroke. Acta Neurol Belg. 2020; 120(3): 681–685.
  17. Sun JH, Tan L, Yu JT. Post-stroke cognitive impairment: epidemiology, mechanisms and management. Ann Transl Med. 2014; 2(8): 80.
  18. Etherton MR, Barreto AD, Schwamm LH, et al. Neuroimaging Paradigms to Identify Patients for Reperfusion Therapy in Stroke of Unknown Onset. Front Neurol. 2018; 9: 327.
  19. Ryu CW, Shin HS, Park S, et al. Alberta Stroke Program Early CT Score in the Prognostication after Endovascular Treatment for Ischemic Stroke: A Meta-analysis. Neurointervention. 2017; 12(1): 20–30.
  20. Sundaram VK, Goldstein J, Wheelwright D, et al. Automated ASPECTS in Acute Ischemic Stroke: A Comparative Analysis with CT Perfusion. AJNR Am J Neuroradiol. 2019; 40(12): 2033–2038.
  21. Sachdev PS, Brodaty H, Valenzuela MJ, et al. Clinical determinants of dementia and mild cognitive impairment following ischaemic stroke: the Sydney Stroke Study. Dement Geriatr Cogn Disord. 2006; 21(5-6): 275–283.
  22. Claesson L, Lindén T, Skoog I, et al. Cognitive impairment after stroke - impact on activities of daily living and costs of care for elderly people. The Göteborg 70+ Stroke Study. Cerebrovasc Dis. 2005; 19(2): 102–109.
  23. Cao M, Ferrari M, Patella R, et al. Neuropsychological findings in young-adult stroke patients. Arch Clin Neuropsychol. 2007; 22(2): 133–142.
  24. Cengić L, Vuletić V, Karlić M, et al. Motor and cognitive impairment after stroke. Acta Clin Croat. 2011; 50(4): 463–467.
  25. Liman TG, Heuschmann PU, Endres M, et al. Changes in cognitive function over 3 years after first-ever stroke and predictors of cognitive impairment and long-term cognitive stability: the Erlangen Stroke Project. Dement Geriatr Cogn Disord. 2011; 31(4): 291–299.
  26. Douiri A, Rudd AG, Wolfe CDA. Prevalence of poststroke cognitive impairment: South London Stroke Register 1995-2010. Stroke. 2013; 44(1): 138–145.
  27. Knopman DS, Roberts RO, Geda YE, et al. Association of prior stroke with cognitive function and cognitive impairment: a population-based study. Arch Neurol. 2009; 66(5): 614–619.
  28. Bour A, Rasquin S, Boreas A, et al. How predictive is the MMSE for cognitive performance after stroke? J Neurol. 2010; 257(4): 630–637.
  29. Sundar U, Adwani S. Post-stroke cognitive impairment at 3 months. Ann Indian Acad Neurol. 2010; 13(1): 42–46.
  30. Boehme AK, Esenwa C, Elkind MSV. Stroke Risk Factors, Genetics, and Prevention. Circ Res. 2017; 120(3): 472–495.
  31. Habibi-Koolaee M, Shahmoradi L, Niakan Kalhori SR, et al. Prevalence of Stroke Risk Factors and Their Distribution Based on Stroke Subtypes in Gorgan: A Retrospective Hospital-Based Study-2015-2016. Neurol Res Int. 2018; 2018: 2709654.
  32. Kim JS. Unconventional, Yet Important, Risk Factors for Stroke. J Stroke. 2018; 20(1): 1.
  33. Bang OhY, Ovbiagele B, Kim JS. Nontraditional Risk Factors for Ischemic Stroke: An Update. Stroke. 2015; 46(12): 3571–3578.
  34. Kim YD, Jung YoH, Saposnik G. Traditional Risk Factors for Stroke in East Asia. J Stroke. 2016; 18(3): 273–285.
  35. Goldstein FC, Levey AI, Steenland NK. High blood pressure and cognitive decline in mild cognitive impairment. J Am Geriatr Soc. 2013; 61(1): 67–73.
  36. Sun JH, Tan L, Yu JT. Post-stroke cognitive impairment: epidemiology, mechanisms and management. Ann Transl Med. 2014; 2(8): 80.
  37. Swartz RH, Bayley M, Lanctôt KL, et al. Post-stroke depression, obstructive sleep apnea, and cognitive impairment: Rationale for, and barriers to, routine screening. Int J Stroke. 2016; 11(5): 509–518.
  38. Ovbiagele B, Saver JL, Sanossian N, et al. Predictors of cerebral microbleeds in acute ischemic stroke and TIA patients. Cerebrovasc Dis. 2006; 22(5-6): 378–383.
  39. Elkind MSV, Boehme AK, Smith CJ, et al. Infection as a Stroke Risk Factor and Determinant of Outcome After Stroke. Stroke. 2020; 51(10): 3156–3168.
  40. Kocatürk M, Kocatürk Ö. Assessment of relationship between C-reactive protein to albumin ratio and 90-day mortality in patients with acute ischaemic stroke. Neurol Neurochir Pol. 2019; 53(3): 205–211.
  41. Sivakumar L, Kate M, Jeerakathil T, et al. Serial montreal cognitive assessments demonstrate reversible cognitive impairment in patients with acute transient ischemic attack and minor stroke. Stroke. 2014; 45(6): 1709–1715.
  42. Chan E, Altendorff S, Healy C, et al. The test accuracy of the Montreal Cognitive Assessment (MoCA) by stroke lateralisation. J Neurol Sci. 2017; 373: 100–104.
  43. Sun JH, Tan L, Yu JT. Post-stroke cognitive impairment: epidemiology, mechanisms and management. Ann Transl Med. 2014; 2(8): 80.
  44. Wiśniewski A, Sikora J, Filipska K, et al. Assessment of the relationship between platelet reactivity, vascular risk factors and gender in cerebral ischaemia patients. Neurol Neurochir Pol. 2019; 53(4): 258–264.

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