Predictors of one-year survival after ischaemic stroke

Predicting the outcome of ischaemic stroke (IS) is a complex task, as mortality and disability depend on many factors, including age, gender, type and severity of stroke, and comorbidities. Survival rates also vary between countries depending on genetic characteristics and differences in the organisation of healthcare systems.

Objective: to search for predictors of one-year survival after IS in a sample of patients from the Perm region.

Material and methods. The study included 254 patients who had suffered an IS. Seventy-five parameters obtained during routine clinical examination were analysed, including information on the subtype and severity of the stroke, the size and location of the lesion, neurological disorders, comorbidities, and other factors. Relevant features were selected using the WEKA programme, and the selected features were used in a predictive model based on logistic regression.

Results. The following factors have been identified as significant predictors of annual survival in patients who have undergone IS (the sign of the coefficient reflects the relative contribution of the factor to the model and its positive or negative effect): age (-0.02), degree of neurological deficit on the NIHSS scale at discharge (-0.06), haemoglobin level (0.01), infarction in the anterior choroidal artery basin (0.74), recurrent stroke within the following year (-0.02) and cardioembolic stroke subtype (-0.32). The accuracy of the logistic model was 84% with 10-fold cross-validation.

Conclusion. In the model predicting one-year survival after IS, other factors have been identified in addition to age, which is usually associated with a less favourable prognosis. Further multicentre studies are needed to confirm the reliability of the proposed model.

1. Donkor ES. Stroke in the 21st Century: A Snapshot of the Burden, Epidemiology, and Quality of Life. Stroke Res Treat. 2018 Nov 27;2018:3238165. doi: 10.1155/2018/3238165

2. Wang W, Rudd AG, Wang Y, et al. Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study. BMC Neurol. 2022 May; 22(1):195. doi: 10.1186/s12883-022-02722-1

3. Sha L, Xu T, Ge X, et al. Predictors of death within 6 months of stroke onset: A model with Barthel index, platelet/lymphocyte ratio and serum albumin. Nursing Open. 2021 May; 8(3):1380-92. doi: 10.1002/nop2.754

4. O'Donnell MJ. The PLAN Score: A Bedside Prediction Rule for Death and Severe Disability Following Acute Ischemic Stroke. Arch Intern Med. 2012 Nov; 172(20):1548. doi: 10.1001/2013.jamainternmed.30

5. Saposnik G, Kapral MK, Liu Y, et al. IScore: A Risk Score to Predict Death Early After Hospitalization for an Acute Ischemic Stroke. Circulation. 2011 Feb; 123(7):739-49. doi: 10.1161/CIRCULATIONAHA.110.983353

6. Williams GR, Jiang JG. Development of an Ischemic Stroke Survival Score. Stroke. 2000 Oct; 31(10):2414-20. doi: 10.1161/01.STR.31.10.2414

7. Anderson CS, Jamrozik KD, Broadhurst RJ, et al. Predicting survival for 1 year among different subtypes of stroke. Results from the Perth Community Stroke Study. Stroke. 1994 Oct; 25(10):1935-44. doi: 10.1161/01.STR.25.10.1935

8. Solberg OG, Dahl M, Mowinckel P, et al. Derivation and validation of a simple risk score for predicting 1-year mortality in stroke. J Neurol. 2007 Oct; 254(10):1376-83. doi: 10.1007/s00415-007-0555-2

9. Wang Y, Lim LL-Y, Heller RF, et al. A prediction model of 1-year mortality for acute ischemic stroke patients. Arch Phys Med Rehabil. 2003 Jul; 84(7):1006-11. doi: 10.1016/S0003-9993(03)00032-7

10. Huang Y, Douiri A, Fahey M. A Dynamic Model for Predicting Survival up to 1 Year After Ischemic Stroke. J Stroke Cerebrovasc Dis. 2020 Oct; 29(10):105133. doi: 10.1016/j.jstrokecere-brovasdis.2020.105133

11. Szlachetka WA, Pana TA, Mamas MA, et al. Predicting 10-year stroke mortality: development and validation of a nomogram. Acta Neurol Belg. 2022 Jun; 122(3):685-93. doi: 10.1007/s13760-021-01752-9

12. Yusuf S, Reddy S, Ounpuu S, et al. Global Burden of Cardiovascular Diseases. Circulation. 2001 Nov;104(22):2746-53. doi: 10.1161/hc4601.099487

13. Chiu M, Austin PC, Manuel DG, et al. Comparison of cardiovascular risk profiles among ethnic groups using population health surveys between 1996 and 2007. Canadian Med Assoc J. 2010 May; 182(8):E301-10. doi: 10.1503/cmaj.091676

14. Tu JV, Chu A, Rezai MR, et al. Incidence of Major Cardiovascular Events in Immigrants to Ontario, Canada: The CANHEART Immigrant Study. Circulation. 2015 Oct;132(16):1549-59. doi: 10.1161/CIRCULATIONAHA.115.015345

15. Wang L, Zhao C, Xia Q, et al. Association between 12p13 SNP rs11833579 and ischemic stroke in Asian population: An updated meta-analysis. J Neurol Sci. 2014 Oct; 345(1-2):198-201. doi: 10.1016/j.jns.2014.07.047

16. Cheong M-Y, Bang O-S, Cha M-H, et al. Association of the Adiponectin Gene Variations with Risk of Ischemic Stroke in a Korean Population. Yonsei Med J. 2011;52(1):20. doi: 10.3349/ymj.2011.52.1.20

17. Sarfo FS, Akpa OM, Ovbiagele B, et al. Patient-level and system-level determinants of stroke fatality across 16 large hospitals in Ghana and Nigeria: a prospective cohort study. Lancet Global Health. 2023 Apr;11(4):e575-85. doi: 10.1016/S2214-109X(23)00038-4

18. Frank E, Hall M, Holmes G, et al. Weka: A machine learning workbench for data mining. In: Maimon O, Rokach L, eds. Data Mining and Knowledge Discovery Handbook. New York: Springer-Verlag; 2005. P. 1305-14.

19. Hall MA, Smith LA. Feature Subset Selection: A Correlation Based Filter Approach. In: 1997 International Conference on Neural Information Processing and Intelligent Information Systems. Berlin: Springer 1997. Available at: https://researchcommons.waikato.ac.nz/handle/10289/1515

20. Rothwell P, Coull A, Giles M, et al. Change in stroke incidence, mortality, case-fatality, severity, and risk factors in Oxfordshire, UK from 1981 to 2004 (Oxford Vascular Study). Lancet. 2004 Jun;363(9425):1925-33. doi: 10.1016/S0140-6736(04)16405-2

21. Adams HP, Bendixen BH, Kappelle LJ, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993 Jan;24(1):35-41. doi: 10.1161/01.STR.24.1.35

22. Stead LG, Gilmore RM, Bellolio MF, et al. Cardioembolic but Not Other Stroke Subtypes Predict Mortality Independent of Stroke Severity at Presentation. Stroke Res Treat. 2011;2011:1-5. doi: 10.4061/2011/281496

23. Dejong G, Vanraak L, Kessels F, et al. Stroke subtype and mortalitya follow-up study in 998 patients with a first cerebral infarct. J Clin Epidemiol. 2003 Mar;56(3):262-8. doi: 10.1016/S0895-4356(02)00572-3

24. Murat Sumer M, Erturk O. Ischemic stroke subtypes: risk factors, functional outcome and recurrence. Neurol Sci. 2002 Mar;22(6):449-54. doi: 10.1007/s100720200004

25. Guo Y, Zhang M, Su Y, et al. Analysis of Risk Factors for Poor Short-Term Outcomes in Acute Cardioembolic Stroke Patients without Reperfusion Therapy. Neuropsychiatr Dis Treat. 2021 Nov;17:3431-7. doi: 10.2147/NDT.S335274

26. Broman J, Fandler-Höfler S, Von Sarnowski B, et al. Long-term risk of recurrent vascular events and mortality in young stroke patients: Insights from a multi-center study. Euro J of Neurology. 2023 Sep;30(9):2675-83. doi: 10.1111/ene.15850

27. Aarnio K, Haapaniemi E, Melkas S, et al. Long-Term Mortality After First-Ever and Recurrent Stroke in Young Adults. Stroke. 2014 Sep;45(9):2670-6. doi: 10.1161/STROKEAHA.114.005648

28. Khanevski AN, Bjerkreim AT, Novotny V, et al. Recurrent ischemic stroke: Incidence, predictors, and impact on mortality. Acta Neurol Scand. 2019;140:3-8. doi: 10.1111/ane.13093

29. Kulesh AA, Demin DA, Vinogradov OI. Pathogenetic mechanisms of ischemic stroke: from verification to secondary prevention. Consilium Medicum. 2021 Nov;23(11):792-9. (In Russ.) doi: 10.26442/20751753.2021.11.201153

30. Yaghi S, Bernstein RA, Passman R, et al. Cryptogenic Stroke: Research and Practice. Circ Res. 2017 Feb;120(3):527-40. doi: 10.1161/CIRCRESAHA.116.308447

31. Barlas RS, Honney K, Loke YK, et al. Impact of Hemoglobin Levels and Anemia on Mortality in Acute Stroke: Analysis of UK Regional Registry Data, Systematic Review, and Meta-Analysis. JAHA. 2016 Aug;5(8):e003019. doi: 10.1161/JAHA.115.003019

32. Desai A, Oh D, Rao EM, et al. Impact of anemia on acute ischemic stroke outcomes: A systematic review of the literature. PLoS One. 2023 Jan;18(1):e0280025. doi: 10.1371/journal.pone.0280025

33. Zhang R, Xu Q, Wang A, et al. Hemoglobin Concentration and Clinical Outcomes After Acute Ischemic Stroke or Transient Ischemic Attack. JAHA. 2021 Dec;10(23):e022547. doi: 10.1161/JAHA.121.022547

34. Hupperts RMM, Lodder J, Heuts-van Raak EPM, et al. Infarcts in the anterior choroidal artery territory: Anatomical distribution, clinical syndromes, presumed pathogenesis and early outcome. Brain. 1994;117(4):825-34. doi: 10.1093/brain/117.4.825