Prognostic factors for recovery of motor dysfunction following ischemic stroke

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Abstract

The problem of searching for the prognostic factors for recovery of motor dysfunction following stroke is very relevant because of the high prevalence of acute cerebrovascular events. The severe disabling sequelae of stroke are associated with the enormous economic burden all over the world, which is aggravated by the lack of customized approaches to rehabilitation with allowance for the clinical data and neuroplastic features of the brain of each individual patient. Although modern diagnostic tools, including neuroimaging, have been introduced, many potential predictors of recovery of functions lost following a cerebrovascular accident still remain to be elucidated or refined. The best-studied prognostic factors for recovery of the functions lost following ischemic stroke are reviewed in this article.

About the authors

Yury D. Barkhatov

Research Center of Neurology

Author for correspondence.
Email: yuri-mozg110889@yandex.ru
Russian Federation, Moscow

Albert S. Kadykov

Research Center of Neurology

Email: yuri-mozg110889@yandex.ru
ORCID iD: 0000-0001-7491-7215

D. Sci. (Med.), Professor, senior researcher, 3rd Neurological department

Russian Federation, Moscow

References

  1. Suslina Z.A., Varakin Yu.Ya. Klinicheskoe rukovodstvo po ranney diagnostike, lecheniyu i profilaktike sosudistykh zabolevaniy golovnogo mozga [Clinical guideline to early diagnostics, treatment and prevention of cerebrovascular diseases]. Moscow. MEDpress-inform, 2015. 440 p. (in Russ.).
  2. Piradov M.A., Tanashyan M.M., Krotenkova M.V. et al. [State-of-the-art neuroimaging techniques]. Annals of Сlinical and Experimental Neurology. 2015; 9(4): 13-20 (in Russ.).
  3. Kadykov A. S. Reabilitatsiya posle insul'ta. [Rehabilitation after stroke]. Moscow. Miklosh, 2003. 176 p. (in Russ.).
  4. Johnson B.H., Bonafede M.M., Watson C. Short- and longer-term healthcare resource utilization and costs associated with acute ischemic stroke. Clinicoecon. Outcomes Res. 2016; 8: 53-61. PMID: 26966382. doi: 10.2147/CEOR. S95662.
  5. Barrett K.M., Ding Y.H., Wagner, D.P. et al. Change in diffusion-weighted imaging infarct volume predicts neurologic outcome at 90 days. Results of the acute stroke accurate prediction (ASAP) trial serial imaging substudy. Stroke. 2009; 40: 2422-2427. PMID: 19443798. doi: 10.1161/STROKEAHA.109.548933.
  6. Menezes N.M., Ay H., Zhu M.W. et al. The real estate factor quantifying the impact of infarct location on stroke severity. Stroke. 2007; 38: 194-197. PMID: 17122428. doi: 10.1161/01.STR.0000251792.76080.45.
  7. Vogt G., Laage R., Shuaib A., Schneider A. Initial lesion volume is an independent predictor of clinical stroke outcome at day 90: an analysis of the Virtual International Stroke Trials Archive (VISTA) database. Stroke. 2012; 43 (5): 1266-1272. PMID: 22403046. doi: 10.1161/STROKEAHA.111.646570.
  8. Cheng B., Forkert N.D., Zavaglia M. et al. Influence of stroke infarct location on functional outcome measured by the modified Rankin scale. Stroke. 2014; 45 (6): 1695-1702. PMID: 24781084. doi: 10.1161/STROKEAHA.114.005152.
  9. Lo R., Gitelman D., Levy R. et al. Identification of critical areas for motor function recovery in chronic stroke subjects using voxel-based lesion symptom mapping. NeuroImage. 2010; 49: 9–18. PMID: 19716427. doi: 10.1016/j.neuroimage. 2009.08.044.
  10. Riley J. D., Le V., Der-Yeghiaian L. et al. Anatomy of stroke injury predicts gains from therapy. Stroke. 2011; 42(2): 421-426. PMID: 21164128. doi: 10.1161/STROKEAHA.110.599340.
  11. Schiemanck S.K., Kwakkel G., Post M.W. et al. Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information? Stroke. 2006; 37 (4): 1050-1054. PMID: 16497980. doi: 10.1161/01. STR.0000206462.09410.6f.
  12. Zhu L.L., Lindenberg R., Alexander M.P., Schlaug G. Lesion load of the corticospinal tract predicts motor impairment in chronic stroke. Stroke. 2010; 41 (5): 910-915. PMID: 20378864. doi: 10.1161/STROKEAHA.109.577023.
  13. Binkofski F., Seitz R.J., Hacklander T. et al. Recovery of motor functions following hemiparetic stroke: a clinical and magnetic resonance-morphometric study. Cerebrovasc. Dis. 2001; 11 (3): 273-81. PMID: 11306779. DOI: 47650.
  14. Hand P.J., Wardlaw J.M., Rivers C.S. et al. MR diffusion-weighted imaging and outcome prediction after ischemic stroke. Neurology. 2006; 66 (8): 1159-1163. PMID: 16525124. doi: 10.1212/01.wnl.0000202524.43850.81.
  15. Menezes N.M., Ay H., Zhu M.W. et al. The real estate factor quantifying the impact of infarct location on stroke severity. Stroke. 2007; 38: 194-197. PMID: 17122428. doi: 10.1161/01.STR.0000251792.76080.45.
  16. Puig J., Pedraza S., Blasco G., et al. Acute damage to the posterior limb of the internal capsule on diffusion tensor tractography as an early imaging predictor of motor outcome after stroke. Am. J. Neuroradiol. 2011; 32 (5): 857-863. PMID: 21474629. doi: 10.3174/ajnr.A2400.
  17. Kelly P.J., Furie K.L., Shafqat S. et al. Functional recovery following rehabilitation after hemorrhagic and ischemic stroke. Arch. Phys. Med. Rehabil. 2003; 84: 968–972. PMID: 12881818.
  18. Kugler C., Altenhoner T., Lochner P., Ferbert A. Does age influence early recovery from ischemic stroke? A study from the Hessian Stroke Data Bank.J. Neurol. 2003; 250: 676–681. PMID: 12796828. doi: 10.1007/s00415-003-1054-8.
  19. Glymour M.M., Berkman L.F., Ertel K.A., et al. Lesion characteristics, NIH stroke scale, and functional recovery after stroke. Am. J. Phys. Med. Rehabil. 2007; 86 (9): 725-733. PMID: 17709996. doi: 10.1097/PHM.0b013e31813e0a32.
  20. Johnston K.C., Wagner D.P., Haley E.C. et al. Combined clinical and imaging information as an early stroke outcome measure. Stroke. 2002; 33 (2): 466-472. PMID: 11823654.21. Turhan N., Atalay A., Muderrisoglu H. Predictors of functional outcome infirst-ever ischemic stroke: a special interest to ischemic subtypes, comorbidity and age. NeuroRehabilitation. 2009; 24 (4): 321-326. PMID: 19597269. doi: 10.3233/NRE-2009-0485.
  21. Farr T.D., Wegener S. Use of magnetic resonance imaging to predict outcome after stroke: a review of experimental and clinical evidence. J. Cereb. Blood Flow Metab. 2010; 30 (4): 703-717. PMID: 20087362. doi: 10.1038/jcbfm.2010.5.
  22. Kim Y.S., Park S.S., Lee S.H. Reduced severity of strokes in patients with silent brain infarctions. European Journal of Neurology 2011, 18: 962–971. PMID: 21159068. doi: 10.1111/j.1468-1331.2010.03282.x.
  23. Meyer S., Verheyden G., Brinkmann N. et al. Functional and motor outcome 5 years after stroke is equivalent to outcome at 2 months: follow-up of the collaborative evaluation of rehabilitation in stroke across Europe. Stroke. 2015; 46 (6): 1613-9. PMID: 25953370. doi: 10.1161/STROKEAHA.115.009421.
  24. Alexander L.D., Black S. E., Gao F. et al. Correlating lesion size and location to deficits after ischemic stroke: the influence of accounting for altered peri-necrotic
  25. tissue and incidental silent infarcts. Behavioral and brain functions. 2010; 6:6. PMID: 20205779. doi: 10.1186/1744-9081-6-6.
  26. Nijboer T.C.W., Kollen B.J., Kwakkel G. The impact of recovery of visuo-spatial neglect on motor recovery of the upper paretic limb after stroke. PLoS ONE. 2014; 9 (6): e100584. PMID: 24950224. doi: 10.1371/journal. pone.0100584.
  27. Lansberg M.G., O’Brien M. W., Tong D. C. et al. Evolution of cerebral infarct volume assessed by diffusion-weighted magnetic resonance imaging. Arch. Neurol. 2001; 58 (4): 613-617. PMID: 11295992.
  28. De Freitas G. R., De H. Christoph D., Bogousslavsky J. Topographic classification of ischemic stroke. Handb. Clin. Neurol. 2009; 93: 425–452. PMID: 18804663. doi: 10.1016/S0072-9752(08)93022-0.
  29. Zopf R., Fruhmann Berger M., Klose U., Karnath H.O. Perfusion imaging of the right perisylvian neural network in acute spatial neglect. Front. Hum. Neurosc. 2009; 3 (3): 15. PMID: 19680470. doi: 10.3389/neuro. 09.015.2009.
  30. Maxton C., Dineen R.A., Padamsey R.C. et al. Don’t neglect “neglect”— an update on post stroke neglect. Int. J. Clin. Pract. 2013; 67: 369–378. PMID: 23521329. doi: 10.1111/ijcp.12058.
  31. Punt T.D., Riddoch M.J. Motor neglect: implications for movement and rehabilitation following stroke. Disabil. Rehabil. 2006; 28: 857–864. PMID: 16777773. doi: 10.1080/09638280500535025.
  32. Dobrynina L.A., Kremneva E.I., Konovalov R.N., Kadykov A.S. [Functional reorganization of the sensorimotor cortex in chronic hemispheric ischemic stroke patients with different severity of motor deficit]. Annals of Clinical and Experimental Neurology. 2012; 3 (6): 4-13. (in Russ.).
  33. Cao Y. D’Olhaberriague L., Vikingstad E.M. et al. Pilot study of functional MRI to assess cerebral activation of motor function after poststroke hemiparesis. Stroke. 1998; 29 (1): 112-122. PMID: 9445338.
  34. Cramer S.C., Crafton K.R. Somatotopy and movement representation sites following cortical stroke. Exp. Brain Res. 2006; 168 (1-2): 25-32. PMID: 16096783. doi: 10.1007/s00221-005-0082-2.
  35. Hanlon C.A., Buffington A.L., McKeown M.J. New brain networks are active after right MCA stroke when moving the ipsilesional arm. Neurology. 2005; 64 (1): 114-20. PMID: 15642913. doi: 10.1212/01.WNL.0000148726.45458.A9.
  36. Stinear C. M., Barber P.A., Smale P.R. et al. Functional potential in chronic stroke patients depends on corticospinal tract integrity. Brain. 2007; 130 (1): 170-80. PMID: 17148468. doi: 10.1093/brain/awl333.
  37. Ward N.S. Functional reorganization of the cerebral motor system after stroke. Curr. Opin. Neurol. 2004; 17 (6): 725-30. PMID: 15542982.
  38. Zemke A.C., Heagerty P.J., Lee C., Cramer S.C. Motor cortex organization after stroke is related to side of stroke and level of recovery. Stroke. 2003; 34 (5): e23-8. PMID: 12677024. doi: 10.1161/01.STR.0000065827.35634.5E.
  39. Di Lazzaro V., Profice P., Pilato F. et al. Motor cortex plasticity predicts recovery in acute stroke. Cerebral Cortex. 2010; 20 (7): 1523-1528. PMID: 19805417. doi: 10.1093/cercor/bhp216.
  40. Fridman E.A., Hanakawa T., Chung M. et al. Reorganization of the human ipsilesional premotor cortex after stroke. Brain. 2004; 127 (4): 747-758. PMID: 14749291. doi: 10.1093/brain/awh082.
  41. Marshall R.S., Perera G.M., Lazar R.M. et al. Evolution of cortical activation during recovery from corticospinal tract infarction. Stroke. 2000; 31 (3): 656-661. PMID: 10700500.
  42. Wang L., Yu C., Chen H. et al. Dynamic functional reorganization of the motor execution network after stroke. Brain. 2010; 133 (4): 1224-1238. PMID: 20354002. doi: 10.1093/brain/awq043.
  43. James G.A., Lu Z.L., Van Meter J.W. et al. Changes in resting state effective connectivity in the motor network following rehabilitation of upper extremity poststroke paresis. Topics in Stroke Rehabilitation. 2009; 16 (4): 270-281. PMID: 19740732. doi: 10.1310/tsr1604-270.
  44. Park C.H., Chang W.H., Ohn S.H. et al. Longitudinal changes of resting-state functional connectivity during motor recovery after stroke. Stroke. 2011; 42 (5): 1357-1362. PMID: 21441147. doi: 10.1161/STROKEAHA.110.596155.
  45. Murase N., Duque J., Mazzocchio R., Cohen, L.G. Influence of interhemispheric interactions on motor function in chronic stroke. Ann. Neurol. 2004; 55 (3): 400-409. PMID: 14991818. doi: 10.1002/ana.10848.
  46. Dijkhuizen R.M., Singhal A.B., Mandeville J.B. et al. Correlation between brain reorganization, ischemic damage, and neurologic status after transient fo-cal cerebral ischemia in rats: a functional magnetic resonance imaging study. J. Neurosc. 2003; 23 (2): 510-517. PMID: 12533611.
  47. Saur D., Lange R., Baumgaertner A. et al. Dynamics of language reorganization after stroke. Brain. 2006; 129 (6): 1371-1384. PMID: 16638796. doi: 10.1093/brain/awl090.
  48. Grau A.J., Weimar C., Buggle F. et al. Risk factors, outcome, and treatment in subtypes of ischemic stroke: the German stroke data bank. Stroke. 2001; 32: 2559–2566. PMID: 11692017.
  49. Rehme A.K., Fink G.R., von Cramon D.Y., Grefkes C. The role of the contralesional motor cortex for motor recovery in the early days after stroke assessed with longitudinal FMRI. Cereb. Cortex. 2011; 21 (4): 756-768. PMID: 20801897. doi: 10.1093/cercor/bhq140.
  50. Bonakdarpour B., Parrish T.B., Thompson C.K. Hemodynamic response function in patients with stroke-induced aphasia: implications for fMRI data analysis. Neuroimage. 2007; 36 (2): 322-31. PMID: 17467297. DOI: 10.1016/j.
  51. neuroimage.2007.02.035.
  52. Dobrynina L.A. [Functional MRI study: passive motor paradigm in the assessment of sensorimotor system]. Annals of Сlinical and Experimental Neurology. 2011; 5(3): 53-61. (in Russ.).
  53. Dobrynina L.A., Konovalov R.N., Kremneva E.I., Kadykov A.S. [MRI in the assessment of motor function restoration in patients with chronic supratentorial infarction]. Annals of Сlinical and Experimental Neurology 2012; 6(2): 4-10. (in Russ.).
  54. Bigourdan A., Munsch F., Coupe P. et al. Early fiber number ratio is a surrogate of corticospinal tract integrity and predicts motor recovery after stroke. Stroke. 2016; 47 (4): 1053-9. PMID: 26979863. doi: 10.1161/STROKEAHA. 115.011576.
  55. Lindenberg R., Renga V., Zhu L.L. et al. Structural integrity of corticospinal motor fibers predicts motor impairment in chronic stroke. Neurology. 2010; 74 (4): 280-7. PMID: 20101033. doi: 10.1212/WNL.0b013e3181ccc6d9.
  56. Auriat A.M., Borich M.R., Snow N.J. et al. Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke. Neuroimage Clin. 2015; 7: 771-81. PMID: 25844329. DOI: 10.1016/j. nicl.2015.03.007.
  57. Jang S.H. Prediction of motor outcome for hemiparetic stroke patients using diffusion tensor imaging: A review. NeuroRehabilitation. 2010; 27 (4): 367-372. PMID: 21160127. doi: 10.3233/NRE-2010-0621.
  58. Lindenberg R., Zhu L.L., Ruber T., Schlaug G. Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging. Hum. Brain Mapp. 2012; 33 (5): 1040-51. PMID: 21538700. doi: 10.1002/hbm.21266.
  59. Radlinska B., Ghinani S., Leppert et al. Diffusion tensor imaging, permanent pyramidal tract damage, and outcome in subcortical stroke. Neurology. 2010; 75 (12): 1048-1054. PMID: 20855848. doi: 10.1212/WNL.0b013e-3181f39aa0.
  60. Globas C., Lam J. M., Zhang W. et al. Mesencephalic corticospinal atrophy predicts baseline deficit but not response to unilateral or bilateral arm training in chronic stroke. Neurorehabil. Neural. Repair. 2011; 25 (1): 81-87. PMID: 20947492. doi: 10.1177/1545968310382001.
  61. Jo J.Y., Lee A., Kim M.S. et al. Prediction of motor recovery using quantitative parameters of motor evoked potential in patients with stroke. Ann. Rehabil. Med. 2016; 40 (5): 806-815. PMID: 27847710. doi: 10.5535/arm.2016.40.5.806.
  62. Choi T.W., Jang S.G., Yang S.N., Pyun S.B. Factors affecting the motor evoked potential responsiveness and parameters in patients with supratentorial stroke. Ann. Rehabil. Med. 2014; 38: 19-28. PMID: 24639922. DOI: 10.5535/ arm.2014.38.1.19.
  63. Kim G.W., Won Y.H., Park S.H. et al. Can motor evoked potentials be an objective parameter to assess extremity function at the acute or subacute stroke stage? Ann. Rehabil. Med. 2015; 39: 253-61. PMID: 25932422. DOI: 10.5535/ arm.2015.39.2.253.
  64. Nascimbeni A., Gaffuri A., Imazio P. Motor evoked potentials: prognostic value in motor recovery after stroke. Funct. Neurol. 2006; 21: 199-203. PMID: 17367579.
  65. Rapisarda G., Bastings E., de Noordhout A.M. et al. Can motor recovery in stroke patients be predicted by early transcranial magnetic stimulation? Stroke.1996; 27: 2191-6. PMID: 8969779.
  66. Hendricks H.T., Pasman J.W., van Limbeek J., Zwarts M.J. Motor evoked potentials in predicting recovery from upper extremity paralysis after acute stroke. Cerebrovasc. Dis. 2003; 16: 265-71. PMID: 12865615. DOI: 71126.
  67. Lee S.Y., Lim J.Y., Kang E.K. et al. Prediction of good functional recovery after stroke based on combined motor and somatosensory evoked potential findings. J. Rehabil. Med. 2010; 42: 16-20. PMID: 20111839. doi: 10.2340/16501977-0475.
  68. Pennisi G., Rapisarda G., Bella R. et al. Absence of response to early transcranial magnetic stimulation in ischemic stroke patients: prognostic value for hand motor recovery. Stroke 1999; 30: 2666-70. PMID: 10582994.
  69. Song Z., Dang L., Zhou Y. et al. Why do stroke patients with negative motor evoked potential show poor limb motor function recovery? Neural. Regen. Res. 2013; 8: 2713-24. PMID: 25206582. doi: 10.3969/j.issn.1673-5374.2013.29.003.
  70. Rossini P.M., Burke D., Chen R. et al. Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: basic principles and procedures for routine clinical and research application. Clin. Neurophysiol.2015; 126: 1071-107. PMID: 25797650. doi: 10.1016/j.clinph.2015.02.001.
  71. Hallett M., Chen R., Ziemann U., Cohen L.G. Reorganization in motor cortex in amputees and in normal volunteers after ischemic limb deafferentation. Electroencephalogr. Clin Neurophysiol Suppl 1999; 51: 183-7. PMID: 10590950.
  72. Nardone R., Tezzon F. Inhibitory and excitatory circuits of cerebral cortex after ischaemic stroke: prognostic value of the transcranial magnetic stimulation. Electromyogr. Clin. Neurophysiol. 2002; 42: 131-6. PMID: 11977426.
  73. Gale S.D., Pearson C.M. Neuroimaging predictors of stroke outcome: implications for neurorehabilitation. NeuroRehabilitation. 2012; 31 (3): 331-44. PMID: 23001879. doi: 10.3233/NRE-2012-0800.
  74. Doyle K.P. Simon R.P., Stenzel-Poore, M.P. Mechanisms of ischemic brain damage. Neuropharmacology. 2008; 55(3): 310-318. PMID: 18308346. doi: 10.1016/j.neuropharm.2008.01.005.
  75. Inoue Y., Matsumura Y., Fukuda T. et al. MR imaging of Wallerian degeneration in the brainstem: temporal relationships. Am. J. Neuroradiol. 1990; 11 (5): 897-902. PMID: 2120993.
  76. Kuhn M. J., Mikulis D. J., Ayoub D. M. et al. Wallerian degeneration after cerebral infarction: evaluation with sequential MR imaging. Radiology. 1989; 172 (1): 179-182. PMID: 2740501. doi: 10.1148/radiology.172.1.2740501.
  77. DeVetten G., Coutts S.B., Hill M.D. et al. Acute corticospinal tract Wallerian degeneration is associated with stroke outcome. Stroke. 2010; 41 (4): 751-756. PMID: 20203322. doi: 10.1161/STROKEAHA.109.573287.
  78. Thomalla G., Glauche V., Koch M. A. et al. Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke. NeuroImage. 2004; 22 (4): 1767-1774. PMID: 15275932. doi: 10.1016/j.neuroimage. 2004.03.041.
  79. Matsusue E., Sugihara S., Fujii S. et al. Wallerian degeneration of the corticospinal tracts: postmortem MR-pathologic correlations. Acta Radiologica. 2007; 48 (6): 690-694. PMID: 17611880. doi: 10.1080/02841850701342112.
  80. Schiemanck S.K., Kwakkel G., Post M.W. et al. Impact of internal capsule lesions on outcome of motor hand function at one year post-stroke. J. Rehabil. Med. 2008; 40: 96–101. PMID: 18509572. doi: 10.2340/16501977-0130.
  81. Copen W.A., Schaefer P.W., Wu O. MR perfusion imaging in acute ischemic stroke. Neuroimaging Clinics of North America. 2011; 21 (2): 259-283. PMID: 21640299. doi: 10.1016/j.nic.2011.02.007.
  82. Muir K.W., Buchan A., von Kummer R. et al. Imaging of acute stroke. Lancet. Neurol. 2006; 5 (9): 755-768. PMID: 16914404. doi: 10.1016/S1474-4422(06)70545-2.
  83. Krotenkova M.V., Suslin A.S., Tanashyan M.M. et al. [Diffusion-weighted MRI and MRI-perfusion in the acute period of ischemic stroke]. Annals of Clinical and Experimental Neurology. 2009; 3(3): 11-18. (in Russ.).
  84. Latchaw R.E., Alberts M.J., Lev M.H. et al. Recommendations for imaging of acute ischemic stroke: a scientific statement from the American Heart Association. Stroke. 2009; 40 (11): 3646-3678. PMID: 19797189. DOI: 10.1161/ STROKEAHA.108.192616.
  85. Ablyakimov R.E., Anufriev P.L., Tanashyan M.M. [Pathogenic stroke subtypes and their diagnostic criteria in patients with ischemic heart disease and intracranial atherosclerosis: a clinical morphological study]. Annals of Clinical and Experimental Neurology. 2016; 10(4): 5-10. (in Russ.).
  86. Jackson C., Sudlow C. Are lacunar strokes really different? A systematic review of differences in risk factor profiles between lacunar and nonlacunar infarcts. Stroke. 2005; 36 (4): 891-901. PMID: 15761206. doi: 10.1161/01. STR.0000157949.34986.30.
  87. Moncayo J., Devuyst G., Van Melle G., Bogousslavsky J. Coexisting causes of ischemic stroke. Arch. Neurol. 2000; 57 (8): 1139-44. PMID: 10927793.
  88. Schulz U.G., Rothwell P.M. Differences in vascular risk factors between etiological subtypes of ischemic stroke: importance of population-based studies. Stroke. 2003; 34 (8): 2050-9. PMID: 12829866. doi: 10.1161/01. STR.0000079818.08343.8C.
  89. Di Tullio M.R., Zwas D.R., Sacco R.L. et al. Left ventricular mass and geometry and the risk of ischemic stroke. 2003; 34(10): 2380-4. PMID: 12958319.doi: 10.1161/01.STR.0000089680.77236.60.
  90. Giaquinto S., Ferrara I., Muschera R. et al. The effects of atrial fibrillation on functional recovery in post-stroke patients. Disabil. Rehabil. 2001; 23 (5): 204-8. PMID: 11336378.
  91. Karatas M., Dilek A., Erkan H. et al. Functional outcome in stroke patients with atrial fibrillation. Arch. Phys. Med. Rehabil. 2000; 81(8): 1025-9. PMID: 10943749.
  92. Tegos T.J., Kalodiki E., Sabetai M.M., Nicolaides A.N. Stroke: pathogenesis, investigations, and prognosis – part II of III. Angiology. 2000 Nov;51(11):885-94. PMID: 11103857.
  93. Bamford J., Sandercock P., Dennis M. et al. Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet. 1991; 337 (8756): 1521-6. PMID: 1675378.
  94. Lieberman D. Rehabilitation following stroke in patients aged 85 and above. J. Rehabil. Res. Dev. 2005; 42(1): 47-53. PMID: 15742249.
  95. Mead G.E., Shingler H., Farrell A. et al. Carotid disease in acute stroke. Age Ageing. 1998; 27(6): 677-82. PMID: 10408660.
  96. Roth E.J., Mueller K., Green D. Stroke rehabilitation outcome: impact of coronary artery disease. Stroke. 1988; 19 (1): 42-7. PMID: 3336900.
  97. Acciarresi M., Caso V., Venti M. et al. First-ever stroke and outcome in patients admitted to Perugia Stroke Unit: predictors for death, dependency, andrecurrence of stroke within the first three months. Clin. Exp. Hypertens. 2006; 28 (3-4): 287-94. PMID: 16833036.
  98. Boon A., Lodder J., Heuts-van Raak L., Kessels F. Silent brain infarcts in 755 consecutive patients with a first-ever supratentorial ischemic stroke. Relationship with index-stroke subtype, vascular risk factors, and mortality. Stroke 1994; 25: 2384–2390. PMID: 7974577.
  99. Di Carlo A., Lamassa M., Baldereschi M. et al. Risk factors and outcome of subtypes of ischemic stroke. Data from a multicenter multinational hospital-based registry. J. Neurol. Sci. 2006; 15; 244 (1-2): 143-50. PMID: 16530226. doi: 10.1016/j.jns.2006.01.016.
  100. Liu M., Domen K., Chino N. Comorbidity measures for stroke outcome research: a preliminary study. Arch. Phys. Med. Rehabil. 1997; 78 (2): 166-72. PMID: 9041898.
  101. Marengoni A., Cossi S., De Martinis M. et al. Adverse outcomes in older hospitalized patients: the role of multidimensional geriatric assessment. Aging. Clin. Exp. Res. 2003; 15 (1): 32-7. PMID: 12841416.
  102. Patrick L., Knoefel F., Gaskowski P., Rexroth D., Medical comorbidity and rehabilitation efficiency in geriatric inpatients. J. Am. Geriatr. Soc. 2001; 49 (11): 1471-7. PMID: 11890585.
  103. Sharma J.C., Fletcher S., Vassallo M., Ross I. Cardiovascular disease and outcome of acute stroke: influence of preexisting cardiac failure. Eur. J. Heart Fail. 2000; 2 (2): 145-50. PMID: 10856727.
  104. Pantoni L. Pathophysiology of age-related cerebral white matter changes. Cerebrovasc. Dis. 2002; 13 (2): 7–10. PMID: 11901236. DOI: 49143.
  105. Vermeer S.E., Longstreth W.T., Koudstaal P.J. Silent brain infarcts: a systematic review. Lancet. Neurol. 2007; 6: 611–619. PMID: 17582361. doi: 10.1016/S1474-4422(07)70170-9.
  106. Roob G., Schmidt R., Kapeller P. et al. MRI evidence of past cerebral microbleeds in a healthy elderly population. Neurology. 1999; 52: 991–994. PMID: 10102418.
  107. de Leeuw F. E., de Groot J. C., Oudkerk M. et al. Hypertension and cerebral white matter lesions in a prospective cohort study. Brain. 2002; 125: 765–772. PMID: 11912110.
  108. Vermeer S.E., Koudstaal P.J., Oudkerk M. et al. Prevalence and risk factors of silent brain infarcts in the population-based Rotterdam Scan Study. Stroke. 2002; 33: 21–25. PMID: 11779883.
  109. Kuller L.H., Longstreth W.T., Arnold A.M. et al. White matter hyperintensity on cranial magnetic resonance imaging: a predictor of stroke. Stroke. 2004; 35: 1821–1825. PMID: 15178824. doi: 10.1161/01.STR.0000132193.35955.69.
  110. Vermeer S.E., Prins N.D., den Heijer T. et al. Silent brain infarcts and the risk of dementia and cognitive decline. N. Engl. J. Med. 2003; 348: 1215–1222. PMID: 12660385. doi: 10.1056/NEJMoa022066.
  111. Steffens D.C., Helms M.J., Krishnan K.R., Burke G.L. Cerebrovascular disease and depression symptoms in the cardiovascular health study. Stroke .1999; 30: 2159–2166. PMID: 10512922.
  112. Adachi T., Kobayashi S., Yamaguchi S. Frequency and pathogenesis of silent subcortical brain infarction in acute first-ever ischemic stroke. Intern. Med. 2002; 41: 103–108. PMID: 11868595.
  113. Briley D.P., Haroon S., Sergent S.M., Thomas S. Does leukoaraiosis predict morbidity and mortality? Neurology. 2000; 54: 90–94. PMID: 10636131.
  114. Lee S.H., Kim B.J., Ryu W.S. et al. White matter lesions and poor outcome after intracerebral hemorrhage: a nationwide cohort study. Neurology. 2010; 74: 1502–1510. PMID: 20458066. doi: 10.1212/WNL.0b013e3181dd425a.
  115. Moncayo J., de Freitas G. R., Bogousslavsky J. et al. Do transient ischemic attacks have a neuroprotective effect? Neurology. 2000; 54: 2089–2094. PMID: 10851368.

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