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Pre-procedural predictive factors of symptomatic intracranial hemorrhage after thrombectomy in stroke

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Abstract

Objective

Symptomatic intracerebral hemorrhage (sICH) is a common complication of acute ischemic stroke (AIS) associated with limited treatments and poor outcomes. We aimed to identify predictive factors of sICH in patients with AIS following mechanical thrombectomy (MT) in a real-world setting.

Methods

Patients with large vessel occlusion of the anterior circulation treated with MT were consecutively included in a prospective monocentric cohort. Clinical, biological, and radiological parameters were collected to identify pre-procedural predictors for sICH.

Results

637 patients were included in our study. Magnetic resonance imaging was performed on most patients (86.7%). sICH occurred in 55 patients (8.6%). 428 patients (67.2%) were treated with intravenous thrombolysis. After multivariate analysis, prior use of antiplatelet therapies (odd ratio (OR) 1.84, 95% confidence interval (CI) 1.01–3.32), high C-reactive protein (OR per standard deviation (SD) increase 1.28, 95% 1.01–1.63), elevated mean arterial blood pressure (OR per 10 mmHg increase 1.22, 95% CI 1.03–1.44), hyperglycemia (OR per one SD-log increase 1.38, 95% CI 1.02–1.87), and low ASPECTS (OR per 1-point decrease 1.42, 95% CI 1.12–1.80) were found to be independent predictive factors of sICH. The pre-procedural predictors did not change when the absence of successful recanalization was considered as a covariate. Patients with strokes of unknown onset time were not especially vulnerable for sICH.

Conclusion

sICH after MT was associated with several pre-procedural risk factors: prior use of antiplatelet therapies, high C-reactive protein and hyperglycemia at baseline, elevated mean arterial blood pressure, and low ASPECTS.

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References

  1. Sussman ES, Connolly ES (2013) Hemorrhagic transformation: a review of the rate of hemorrhage in the major clinical trials of acute ischemic stroke. Front Neurol 4:69. https://doi.org/10.3389/fneur.2013.00069

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Goyal M, Menon BK, van Zwam WH et al (2016) Endovascular thrombectomy after large-vessel ischaemic stroke: a meta-analysis of individual patient data from five randomised trials. Lancet 387:1723–1731. https://doi.org/10.1016/S0140-6736(16)00163-X

    Article  PubMed  Google Scholar 

  3. Hao Y, Yang D, Wang H et al (2017) Predictors for symptomatic intracranial hemorrhage after endovascular treatment of acute ischemic stroke. Stroke 48:1203–1209. https://doi.org/10.1161/STROKEAHA.116.016368

    Article  PubMed  Google Scholar 

  4. Montalvo M, Mistry E, Chang AD et al (2019) (2019) Predicting symptomatic intracranial haemorrhage after mechanical thrombectomy: the TAG score. J Neurol Neurosurg Psychiatry 2:321184. https://doi.org/10.1136/jnnp-2019-321184

    Article  Google Scholar 

  5. Neuberger U, Kickingereder P, Schönenberger S et al (2019) Risk factors of intracranial hemorrhage after mechanical thrombectomy of anterior circulation ischemic stroke. Neuroradiology 61:461–469. https://doi.org/10.1007/s00234-019-02180-6

    Article  PubMed  Google Scholar 

  6. Kaesmacher J, Kaesmacher M, Maegerlein C et al (2017) Hemorrhagic transformations after thrombectomy: risk factors and clinical relevance. Cerebrov Dis 43:294–304. https://doi.org/10.1159/000460265

    Article  CAS  Google Scholar 

  7. Boisseau W, Fahed R, Lapergue B et al (2019) Predictors of parenchymal hematoma after mechanical thrombectomy: a multicenter study. Stroke. https://doi.org/10.1161/STROKEAHA.118.024512

    Article  PubMed  Google Scholar 

  8. Sugiura Y, Yamagami H, Sakai N, Yoshimura S (2017) Predictors of symptomatic intracranial hemorrhage after endovascular therapy in acute ischemic stroke with large vessel occlusion. J Stroke Cerebrov Dis 26:766–771. https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.10.015

    Article  Google Scholar 

  9. Wahlgren N, Ahmed N, Dávalos A et al (2007) Thrombolysis with alteplase for acute ischaemic stroke in the safe implementation of thrombolysis in stroke-monitoring study (SITS-MOST): an observational study. Lancet 369:275–282. https://doi.org/10.1016/S0140-6736(07)60149-4

    Article  CAS  PubMed  Google Scholar 

  10. Thomalla G, Simonsen CZ, Boutitie F et al (2018) MRI-Guided thrombolysis for stroke with unknown time of onset. N Engl J Med 379:611–622. https://doi.org/10.1056/NEJMoa1804355

    Article  PubMed  Google Scholar 

  11. Hacke W, Kaste M, Bluhmki E et al (2008) Thrombolysis with alteplase 3 to 4.5 hours after acute ischemic stroke. N Engl J Med 359:1317–1329. https://doi.org/10.1056/NEJMoa0804656

    Article  CAS  PubMed  Google Scholar 

  12. Barber PA, Demchuk AM, Zhang J, Buchan AM (2000) Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score. Lancet 355:1670–1674

    Article  CAS  Google Scholar 

  13. Barber PA, Hill MD, Eliasziw M et al (2005) Imaging of the brain in acute ischaemic stroke: comparison of computed tomography and magnetic resonance diffusion-weighted imaging. J Neurol Neurosurg Psychiatry 76:1528–1533. https://doi.org/10.1136/jnnp.2004.059261

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Fazekas F, Chawluk J, Alavi A et al (1987) MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. Am J Roentgenol 149:351–356. https://doi.org/10.2214/ajr.149.2.351

    Article  CAS  Google Scholar 

  15. Adams HP, Bendixen BH, Kappelle LJ et al (1993) 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 24:35–41

    Article  Google Scholar 

  16. Heinze G (2006) A comparative investigation of methods for logistic regression with separated or nearly separated data. Stat Med 25:4216–4226. https://doi.org/10.1002/sim.2687

    Article  PubMed  Google Scholar 

  17. Harrell FE, Lee KL, Mark DB (1996) Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 15:361–387. https://doi.org/10.1002/(SICI)1097-0258(19960229)15:4%3c361::AID-SIM168%3e3.0.CO;2-4

    Article  PubMed  Google Scholar 

  18. Allison PD (1998) Multiple Regression: A Primer, 1st edn. Pine Forge Press, Thousand Oaks, Calif

    Google Scholar 

  19. Nagelkerke NJD (1991) A note on a general definition of the coefficient of determination. Biometrika 78:691–692. https://doi.org/10.1093/biomet/78.3.691

    Article  Google Scholar 

  20. Rubin D (1987) Multivariate imputation for nonresponse in surveys. J. Wiley and Sons, New York

    Book  Google Scholar 

  21. Anadani M, Orabi MY, Alawieh A et al (2019) Blood pressure and outcome after mechanical thrombectomy with successful revascularization. Stroke 50:2448–2454. https://doi.org/10.1161/STROKEAHA.118.024687

    Article  PubMed  Google Scholar 

  22. Zhang X, Xie Y, Wang H et al (2020) Symptomatic intracranial hemorrhage after mechanical thrombectomy in chinese ischemic stroke patients: the ASIAN score. Stroke 51:2690–2696. https://doi.org/10.1161/STROKEAHA.120.030173

    Article  CAS  PubMed  Google Scholar 

  23. Cappellari M, Mangiafico S, Saia V et al (2019) IER-SICH nomogram to predict symptomatic intracerebral hemorrhage after thrombectomy for stroke. Stroke 50:909–916. https://doi.org/10.1161/STROKEAHA.118.023316

    Article  PubMed  Google Scholar 

  24. Rocco A, Ringleb PA, Grittner U et al (2015) Follow-up C-reactive protein level is more strongly associated with outcome in stroke patients than admission levels. Neurol Sci 36:2235–2241. https://doi.org/10.1007/s10072-015-2342-7

    Article  PubMed  Google Scholar 

  25. Di Napoli M, Slevin M, Popa-Wagner A et al (2018) Monomeric C-reactive protein and cerebral hemorrhage: from bench to bedside. Front Immunol 9:1921. https://doi.org/10.3389/fimmu.2018.01921

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Boisseau W, Desilles J-P, Fahed R et al (2019) Neutrophil count predicts poor outcome despite recanalization after endovascular therapy. Neurology 93:e467–e475. https://doi.org/10.1212/WNL.0000000000007859

    Article  CAS  PubMed  Google Scholar 

  27. Pedersen KM, Çolak Y, Ellervik C et al (2019) Smoking and increased white and red blood cells. Arterioscler Thromb Vasc Biol 39:965–977. https://doi.org/10.1161/ATVBAHA.118.312338

    Article  CAS  PubMed  Google Scholar 

  28. Desilles J-P, Syvannarath V, Di Meglio L et al (2018) Downstream microvascular thrombosis in cortical venules is an early response to proximal cerebral arterial occlusion. J Am Heart Assoc. https://doi.org/10.1161/JAHA.117.007804

    Article  PubMed  PubMed Central  Google Scholar 

  29. Singer OC, Humpich MC, Fiehler J et al (2008) Risk for symptomatic intracerebral hemorrhage after thrombolysis assessed by diffusion-weighted magnetic resonance imaging. Ann Neurol 63:52–60. https://doi.org/10.1002/ana.21222

    Article  PubMed  Google Scholar 

  30. Strbian D, Engelter S, Michel P et al (2012) Symptomatic intracranial hemorrhage after stroke thrombolysis: the SEDAN score. Ann Neurol 71:634–641. https://doi.org/10.1002/ana.23546

    Article  PubMed  Google Scholar 

  31. Paciaroni M, Agnelli G, Corea F et al (2008) Early hemorrhagic transformation of brain infarction: rate, predictive factors, and influence on clinical outcome: results of a prospective multicenter study. Stroke 39:2249–2256. https://doi.org/10.1161/STROKEAHA.107.510321

    Article  PubMed  Google Scholar 

  32. Mazya M, Egido JA, Ford GA et al (2012) Predicting the risk of symptomatic intracerebral hemorrhage in ischemic stroke treated with intravenous alteplase: safe Implementation of Treatments in Stroke (SITS) symptomatic intracerebral hemorrhage risk score. Stroke 43:1524–1531. https://doi.org/10.1161/STROKEAHA.111.644815

    Article  CAS  PubMed  Google Scholar 

  33. Whiteley WN, Slot KB, Fernandes P et al (2012) Risk factors for intracranial hemorrhage in acute ischemic stroke patients treated with recombinant tissue plasminogen activator: a systematic review and meta-analysis of 55 studies. Stroke 43:2904–2909. https://doi.org/10.1161/STROKEAHA.112.665331

    Article  CAS  PubMed  Google Scholar 

  34. Nagaraja N, Tasneem N, Shaban A et al (2018) Cerebral microbleeds are an independent predictor of hemorrhagic transformation following intravenous alteplase administration in acute ischemic stroke. J Stroke Cerebrovasc Dis 27:1403–1411. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.12.044

    Article  PubMed  Google Scholar 

  35. Tsivgoulis G, Zand R, Katsanos AH et al (2016) Risk of symptomatic intracerebral hemorrhage after intravenous thrombolysis in patients with acute ischemic stroke and high cerebral microbleed burden: a meta-analysis. JAMA Neurol 73:675–683. https://doi.org/10.1001/jamaneurol.2016.0292

    Article  PubMed  Google Scholar 

  36. Choi K-H, Kim J-H, Kang K-W et al (2018) Impact of microbleeds on outcome following recanalization in patients with acute ischemic stroke. Stroke 5:118023084. https://doi.org/10.1161/STROKEAHA.118.023084

    Article  Google Scholar 

  37. Boulouis G, Bricout N, Benhassen W et al (2019) White matter hyperintensity burden in patients with ischemic stroke treated with thrombectomy. Neurology 93:e1498–e1506. https://doi.org/10.1212/WNL.0000000000008317

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. El Nawar R, Yeung J, Labreuche J et al (2019) MRI-based predictors of hemorrhagic transformation in patients with stroke treated by intravenous thrombolysis. Front Neurol 10:897. https://doi.org/10.3389/fneur.2019.00897

    Article  PubMed  PubMed Central  Google Scholar 

  39. Mönch S, Boeckh-Behrens T, Kreiser K et al (2019) Thrombocytopenia and declines in platelet counts: predictors of mortality and outcome after mechanical thrombectomy. J Neurol. https://doi.org/10.1007/s00415-019-09295-z

    Article  PubMed  Google Scholar 

  40. Nogueira RG, Jadhav AP, Haussen DC et al (2018) Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct. N Engl J Med 378:11–21. https://doi.org/10.1056/NEJMoa1706442

    Article  PubMed  Google Scholar 

  41. Jadhav AP, Aghaebrahim A, Jankowitz BT et al (2019) Benefit of endovascular thrombectomy by mode of onset: secondary analysis of the DAWN trial. Stroke 50:3141–3146. https://doi.org/10.1161/STROKEAHA.119.025795

    Article  PubMed  Google Scholar 

  42. Albers GW, Marks MP, Kemp S et al (2018) Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N Engl J Med 378:708–718. https://doi.org/10.1056/NEJMoa1713973

    Article  PubMed  PubMed Central  Google Scholar 

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Correspondence to Christian Denier.

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Venditti, L., Chassin, O., Ancelet, C. et al. Pre-procedural predictive factors of symptomatic intracranial hemorrhage after thrombectomy in stroke. J Neurol 268, 1867–1875 (2021). https://doi.org/10.1007/s00415-020-10364-x

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