Predictive Markers of Functional Outcome in Subtypes of Ischemic Stroke
https://doi.org/10.15360/1813-9779-2025-5-2579
Abstract
The aim of the study was to identify potential predictors of functional outcome (FO) in patients with subtypes of ischemic stroke (IS) who did not receive reperfusion therapy.
Materials and methods. A prospective study included 229 patients with ischemic stroke divided . into three groups based on the IS subtype: Group 1 — 84 patients with cardioembolic IS; Group 2 — 65 patients with atherothrombotic IS; Group 3 — 80 patients with lacunar IS. Changes in the modified Rankin Scale (mRS) scores were considered as FO criteria calculated as the difference between the scores on admission and on the 21st day after IS onset — ∆mRS. In order to optimize the performance of the machine learning (ML) model, a binary FO approach was chosen for assessment on the 21st day after IS onset: mRS ≥ 3 scores corresponded to an unfavorable non-lethal outcome, and mRS = 0–2 scores corresponded to a favorable FO. We analyzed the interrelation with FO (correlation coefficient, r) and the predictive ability (ML (decision tree), information gain, i. g.) of 29 parameters, including demographic features; comorbidities; instrumental examination findings; NIHSS, BI, CDR scores; serum concentrations of cytokines on the 2nd day of hospital stay.
Results. The following significant (P<0.0001) predictors of unfavorable non-lethal FO were identified: female sex (i. g. = 0.346), recurrent IS (i. g = 0.248), diabetes mellitus (i. g. = 0.442), and CXCL2 concentration (i.g. = 0.306) in Group 1; WMHs severity (i. g. = 0.206), diabetes mellitus (i. g. = 0.340), content of CCL2 (i. g. = 0.116), CCL3 (i. g. = 0.202) and CCL23 (i. g. = 0.101) in Group 2; age (i. g. = 0.106), 2nd –3rd degree obesity (i. g. = 0.150), WMHs severity (i. g. = 0.300), CXCL5 content (i. g. = 0.143) and MIF (i. g. = 0.145) in Group 3. Concentrations of CCL25 (i. g. = 0.108) and IL-6 (i. g. = 0.401) were found as predictors of favorable FO (P<0.0001) in Group 1; 1st degree obesity (i. g. = 0.118) and TNF-α concentration (i. g. = 0.211) in Group 2; arterial hypertension (AH) (i. g. = 0.113) and 1st degree obesity in Group 3.
Conclusion. Study results made evident the variances in combination of factors affecting FO, depending on IS pathogenetic subtype. Despite undoubtful value of the data obtained, further research is needed to expand the potentiality in predicting acute IS outcome and confirm the relevance of identified markers.
About the Authors
Anastasia M. TynterovaRussian Federation
14 Aleksandr Nevsky Str., 236041 Kaliningrad
Ekaterina M. Moiseeva
Russian Federation
14 Aleksandr Nevsky Str., 236041 Kaliningrad
Matvey S. Khoymov
Russian Federation
14 Aleksandr Nevsky Str., 236041 Kaliningrad
Natalya N. Shusharina
Russian Federation
14 Aleksandr Nevsky Str., 236041 Kaliningrad
References
1. Savello A. V., Voznyuk I. A., Babichev K. N., Kandyba D. V., Shenderov S. V., Vlasenko S. V., Saraev G. B. A prognosis scale for functional outcome at discharge after endovascular thrombectomy in the carotid artery territory. S.S. Korsakov Journal of Neurology and Psychiatry. 2021; 121 (6): 34–39. (in Russ.). DOI: 10.17116/jnevro202112106134.
2. Silkin V. V., Ershov V. I., Burdakov V. V., Biryukova T. V., Bredikhin A.Yu., Lozinskaya T.Yu. Mathematical modeling of severe ischemic stroke with multiple organ failure: a retrospective observational study. Annals of Critical Care. 2023; 1: 91–100. (in Russ.). DOI: 10.21320/1818-474X-2023-1-91-100.
3. Manchi M. R., Venkatachalam A. M., Atem F. D., Stone S., Mathews A. A., Abraham A. M., Chavez A. A., et al. Effect of inpatient rehabilitation facility care on ninety day modified Rankin score in ischemic stroke patients. J Stroke Cerebrovasc Dis. 2023 Jun; 32 (6): 107109. DOI: 10.1016/j.jstrokecerebrovasdis.2023.107109. PMID: 37031503.
4. Guzek Z., Dziubek W., Stefańska M., Kowalska J. Evaluation of the functional outcome and mobility of patients after stroke depending on their cognitive state. Sci Rep. 2024 Jan 17; 14 (1): 1515. DOI: 10.1038/s41598-024-52236-8. PMID: 38233519.
5. Gardener H., Romano L. A., Smith E. E., Campo-Bustillo I., Khan Y., Tai S., Riley N., et al. Functional status at 30 and 90 days after mild ischaemic stroke. Stroke Vasc Neurol. 2022 Apr 26; 7 (5): 375–380. DOI: 10.1136/svn-2021-001333. PMID: 35474180.
6. Novikova L. B., Akopyan A. P., Latypova R. F. Evaluation of the outcome in ischemic stroke acute period. Annals of Clinical and Experimental Neurology. 2022; 16 (4): 5–11. (In Russ.) DOI: 10.54101/ACEN.2022.4.1.
7. Pawluk H., Woźniak A, Grześk G., Kołodziejska R., Kozakiewicz M., Kopkowska E., Grzechowiak E., Kozera G. The Role of Selected Pro-Inflammatory Cytokines in Pathogenesis of Ischemic Stroke. Clin Interv Aging. 2020 Mar 23; 15: 469–484. DOI: 10.2147/CIA.S233909. PMID: 32273689.
8. Klimiec-Moskal E., Koceniak P., Weglarczyk K., Slowik A., Siedlar M., Dziedzic T. Circulating chemokines and short- and long-term outcomes after ischemic stroke. Mol Neurobiol. 2025 Jan; 62 (1): 421–428. DOI: 10.1007/s12035-024-04279-1. PMID: 38861234.
9. Golubev A. M. Models of Ischemic Stroke (Review). General Reanimatology. 2020; 16 (1): 59–72. (In Russ.) DOI: 10.15360/1813-9779-2020-1-59-72.
10. Poomalai G., Prabhakar S., Sirala Jagadesh N. Functional Ability and Health Problems of Stroke Survivors: An Explorative Study. Cureus. 2023 Jan 4; 15 (1): e33375. DOI: 10.7759/cureus.33375. PMID: 36751244.
11. Hu Y., Jiang X., Li Y., Yang C., Ma M., Fang J., He L. Endovascular treatment with or without intravenous thrombolysis for acute ischemic stroke due to tandem occlusion: a systematic review and meta-analysis. J Am Heart Assoc. 2024 Sep 3; 13 (17): e034829. DOI: 10.1161/JAHA.124.034829. PMID: 39206729.
12. Maksimova M. Yu., Gulevskaya T. S. Lacunar stroke. S. S. Korsakov Journal of Neurology and Psychiatry. 2019; 119 (8 vyp. 2): 13–27. (In Russ.). DOI: 10.17116/jnevro201911908213.
13. Lau L. H., Lew J., Borschmann K., Thijs V., Ekinci E. I. Prevalence of diabetes and its effects on stroke outcomes: A meta-analysis and literature review. J Diabetes Investig. 2019 May; 10 (3): 780–792. DOI: 10.1111/jdi.12932. PMID: 30220102.
14. Voronina V. P., Zagrebelnyi A. V., Lukina Yu.V., Kutishenko N. P., Dmitrieva N. A., Lerman O. V., Lukyanov M. M., et al. Features of cerebral stroke course in patients with diabetes mellitus according to the REGION-M register. Cardiovascular Therapy and Prevention. 2019; 18 (5): 60–65 (In Russ.). DOI: 10.15829/1728-8800-2019-5-60-65.
15. Miwa K., Nakai M., Yoshimura S., Sasahara Y., Wada S., Koge J., Ishigami A., et al. Clinical impact of body mass index on outcomes of ischemic and hemorrhagic strokes. Int J Stroke. 2024 Oct; 19 (8): 907–915. DOI: 10.1177/17474930241249370. PMID: 38651751.
16. Zakharycheva T. A., Shirokova A. S., Polyakov A. G., Yaitskaya E. O., Chekurina S. L. Lacunary stroke. Clinical cases. Regional blood circulation and microcirculation. 2022; 21 (4): 94–101. (In Russ.). DOI: 10.24884/1682-6655-2022-21-4-94-101.
17. Miklisanskaya S. V., Mazur N. A., Solomasova L. V., Chigineva V. V. The «obesity paradox» and its degree of proof. Therapeutic Archive. 2020; 92 (4): 84–90. (In Russ.) DOI: 10.26442/00403660.2020.04.000421.
18. Antonova K. V., Tanashyan M. M., Raskurazhev A. A., Spryshkov N. E., Panina A. A., Lagoda O. V., Ametov A. S., et al. Obesity and the nervous system. Obesity and metabolism. 2024; 21 (1): 68–78. DOI: 10.14341/omet13019.
19. Horn J. W., Feng T., Mørkedal B., Strand L. B., Horn J., Mukamal K., Janszky I. Obesity and Risk for First Ischemic Stroke Depends on Metabolic Syndrome: The HUNT Study. Stroke. 2021 Nov; 52 (11): 3555–3561. DOI: 10.1161/STROKEAHA.120.033016. PMID: 34281375.
20. Ruan H., Ran X., Li SS, Zhang Q. Dyslipidemia versus obesity as predictors of ischemic stroke prognosis: a multi-center study in China. Lipids Health Dis. 2024 Mar 9; 23 (1): 72. DOI: 10.1186/s12944-024-02061-9. PMID: 38461258.
21. Dahl S., Hjalmarsson C., Andersson B. Sex differences in risk factors, treatment, and prognosis in acute stroke. Womens Health (Lond). 2020 Jan–Dec; 16: 1745506520952039. DOI: 10.1177/1745506520952039. PMID: 32997605
22. Ko D., Rahman F., Schnabel R. B., Yin X., Benjamin E. J., Christophersen I. E. Atrial fibrillation in women: epidemiology, pathophysiology, presentation, and prognosis. Nat Rev Cardiol. 2016 Jun; 13 (6): 321–32. DOI: 10.1038/nrcardio.2016.45. PMID: 27053455.
23. Santamarнa M., López-Dequidt I., López-Loureiro I., Rodríguez-Pérez M., Hervella P., Sobrino T., Campos F. et al. Influence of Sex on Stroke Prognosis: A Demographic, Clinical, and Molecular Analysis. Front Neurol. 2019 Apr 17; 10: 388. DOI: 10.3389/fneur.2019.00388. PMID: 31057479.
24. Mkhitaryan E. A., Fateeva V. V. Age-Dependent Cerebral Microangiopathy Associated with Vascular Risk Factors: How to Recognize the Signs? Russian Journal of Geriatric Medicine. 2024; (1): 49–55. (In Russ.) DOI: 10.37586/2686-8636-1-2024-49-55.
25. Lu X., Wang Z., Ye D., Feng Y., Liu M., Xu Y., Wang M., et al. The Role of CXC Chemokines in Cardiovascular Diseases. Front Pharmacol. 2022 May 20; 12: 765768. DOI: 10.3389/fphar.2021.765768. PMID: 35668739.
26. Zhang Y. L., Cao H. J., Han X., Teng F., Chen C., Yang J., Yan X., et al. Chemokine Receptor C. X.CR-2 Initiates Atrial Fibrillation by Triggering Monocyte Mobilization in Mice. Hypertension. 2020 Aug; 76 (2): 381–392. DOI: 10.1161/HYPERTENSIONAHA.120.14698. PMID: 32639881.
27. Zhang R. M., McNerney K. P., Riek A. E., Bernal-Mizrachi C. Immunity and Hypertension. Acta Physiol. (Oxf) 2021; 231: e13487. DOI: 10.1111/apha.13487. PMID: 32359222.
28. Korbecki J., Maruszewska A., Bosiacki M., Chlubek D., Baranowska-Bosiacka I. The Potential Importance of CXCL1 in the Physiological State and in Noncancer Diseases of the Cardiovascular System, Respiratory System and Skin. Int J Mol Sci. 2022 Dec 22; 24 (1): 205. DOI: 10.3390/ijms24010205. PMID: 36613652.
29. Yan Y., Thakur M., van der Vorst E. P. C., Weber C., Döring Y. Targeting the chemokine network in atherosclerosis. Atherosclerosis. 2021 Aug; 330: 95–106. DOI: 10.1016/j.atherosclerosis.2021.06.912. PMID: 34247863.
30. Kim C. S., Kang J. H., Cho H. R., Blankenship T. N., Erickson K. L., Kawada T., Yu R. Potential involvement of CCL23 in atherosclerotic lesion formation/progression by the enhancement of chemotaxis, adhesion molecule expression, and MMP-2 release from monocytes. Inflamm Res. 2011 Sep; 60 (9): 889–95. DOI: 10.1007/s00011-011-0350-5. PMID: 21656154.
31. Tsioufis P., Theofilis P., Tsioufis K., Tousoulis D. The impact of cytokines in coronary atherosclerotic plaque: current therapeutic approaches. Int J Mol Sci. 2022 Dec 14; 23 (24): 15937. DOI: 10.3390/ijms232415937. PMID: 36555579.
32. Wu X., Sun M., Yang Z., Lu C., Wang Q., Wang H., Deng C., Liu Y., Yang Y. The Roles of CCR9/CCL25 in Inflammation and Inflammation-Associated Diseases. Front Cell Dev Biol. 2021 Aug 19; 9: 686548. DOI: 10.3389/fcell.2021.686548. PMID: 34490243
33. Kummer K. K., Zeidler M., Kalpachidou T., Kress M. Role of IL-6 in the regulation of neuronal development, survival and function. Cytokine. 2021 Aug; 144: 155582. DOI: 10.1016/j.cyto.2021.155582. PMID: 34058569.
34. Xue Y., Zeng X., Tu W. J., Zhao J. Tumor Necrosis Factor-α: The Next Marker of Stroke. Dis Markers. 2022 Feb 27; 2022: 2395269. DOI: 10.1155/2022/2395269. PMID: 35265224.
35. Cao Q., Chen J., Zhang Z., Shu S., Qian Y., Yang L., Xu L., et al. Astrocytic CXCL5 hinders microglial phagocytosis of myelin debris and aggravates white matter injury in chronic cerebral ischemia. J Neuroinflammation. 2023 May 3; 20 (1): 105. DOI: 10.1186/s12974-023-02780-3. PMID: 37138312
36. Xiao G., Kumar R., Komuro Y., Burguet J., Kakarla V., Azizkhanian I., Sheth S. A., et al. IL-17/CXCL5 signaling within the oligovascular niche mediates human and mouse white matter injury. Cell Rep. 2022 Dec 20; 41 (12): 111848. DOI: 10.1016/j.celrep.2022.111848. PMID: 36543124
37. Chen C., Chang T. T., Chen J. W. Mechanistic role of CXCL5 in cardiovascular disease, diabetes mellitus, and kidney disease. Life Sci. 2023 Oct 1; 330: 122018. DOI: 10.1016/j.lfs.2023.122018. PMID: 37567498.
38. Chen C., Lin L. Y., Wu Y. W., Chen J. W., Chang T. T. CXCL5 inhibition improves kidney function by protecting renal tubular epithelial cells in diabetic kidney disease. Clin Immunol. 2024 Nov; 268: 110369. DOI: 10.1016/j.clim.2024.110369. PMID: 39326648.
39. Zhang Y., Yu Z., Ye N., Zhen X. Macrophage migration inhibitory factor (MIF) in CNS diseases: Functional regulation and potential therapeutic indication. Fundam Res. 2023 May 30; 4 (6): 1375–1388. DOI: 10.1016/j.fmre.2023.05.008. PMID: 39734533
40. Li Y. S., Chen W., Liu S., Zhang Y. Y., Li X. H. Serum macrophage migration inhibitory factor levels are associated with infarct volumes and long-term outcomes in patients with acute ischemic stroke. Int J Neurosci. 2017 Jun; 127 (6): 539–546. DOI: 10.1080/00207454.2016.1211648. PMID: 27402018.
41. Zhao J., Wang X., Yu M., Zhang S., Li Q., Liu H., Zhang J., et al. The relevance of serum macrophage migration inhibitory factor level and executive function in patients with white matter hyperintensity in cerebral small vessel disease. Brain Sci. 2023 Apr 5; 13 (4): 616. DOI: 10.3390/brainsci13040616. PMID: 37190581
42. Chen L., Li L., Cui D., Huang Y., Tong H., Zabihi H., Wang S., et al. Extracellular macrophage migration inhibitory factor (MIF) downregulates adipose hormone-sensitive lipase (HSL) and contributes to obesity. Mol Metab. 2024 Jan; 79: 101834. DOI: 10.1016/j.molmet.2023.101834. PMID: 37935315
43. Cui N., Li H., Dun Y., Ripley-Gonzalez J. W., You B., Li D., Liu Y., et al. Exercise inhibits JNK pathway activation and lipotoxicity via macrophage migration inhibitory factor in nonalcoholic fatty liver disease. Front Endocrinol (Lausanne). 2022 Sep 6; 13: 961231. DOI: 10.3389/fendo.2022.961231. PMID: 36147562
44. Cheng Q., McKeown S. J., Santos L., Santiago F. S., Khachigian L. M., Morand E. F., Hickey M. J. Macrophage migration inhibitory factor increases leukocyte-endothelial interactions in human endothelial cells via promotion of expression of adhesion molecules. J Immunol. 2010 Jul 15; 185 (2): 1238–47. DOI: 10.4049/jimmunol.0904104. PMID: 20554956.
Supplementary files
Review
For citations:
Tynterova A.M., Moiseeva E.M., Khoymov M.S., Shusharina N.N. Predictive Markers of Functional Outcome in Subtypes of Ischemic Stroke. General Reanimatology. (In Russ.) https://doi.org/10.15360/1813-9779-2025-5-2579