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Section 3 - Prognosis of Transient Ischemic Attack and Stroke

Published online by Cambridge University Press:  01 August 2018

Gary K. K. Lau
Affiliation:
University of Oxford
Sarah T. Pendlebury
Affiliation:
University of Oxford
Peter M. Rothwell
Affiliation:
University of Oxford
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Transient Ischemic Attack and Stroke
Diagnosis, Investigation and Treatment
, pp. 213 - 264
Publisher: Cambridge University Press
Print publication year: 2018

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References

References

Altman, DG (2001). Systematic reviews of evaluations of prognostic variables. British Medical Journal 323:224228Google Scholar
Altman, DG, Royston, P (2000). What do we mean by validating a prognostic model? Statistics in Medicine 19:453473Google Scholar
Altman, DG, Royston, P (2007). Evaluating the performance of prognostic models. In Treating Individuals: From Randomized Trials to Personalised Medicine, Rothwell, PM (ed.), pp. 213–30. London: ElsevierGoogle Scholar
Babyak, MA (2004). What you see may not be what you get: A brief, nontechnical introduction to overfitting in regression-type models. Psychosomatic Medicine 66:411421Google Scholar
Boissel, JP, Collet, JP, Lievre, M et al. (1993). An effect model for the assessment of drug benefit: Example of antiarrhythmic drugs in postmyocardial infarction patients. Journal of Cardiovascular Pharmacology 22:356363Google Scholar
Burton, A, Altman, DG (2004). Missing covariate data within cancer prognostic studies: A review of current reporting and proposed guidelines. British Journal of Cancer 91:48CrossRefGoogle ScholarPubMed
Christensen, E (1987). Multivariate survival analysis using Cox’s regression model. Hepatology 7:13461358Google Scholar
Clark, TG, Altman, DG (2003). Developing a prognostic model in the presence of missing data: An ovarian cancer case study. Journal of Clinical Epidemiology 56:2837Google Scholar
Collins, GS, Mallett, S, Omar, O et al. (2011). Developing risk prediction models for type 2 diabetes: A systematic review of methodology and reporting. BMC Medicine 9:103Google Scholar
Collins, GS, Omar, O, Shanyinde, M et al. (2013). A systematic review finds prediction models for chronic kidney disease were poorly reported and often developed using inappropriate methods. Journal of Clinical Epidemiology 66:268277CrossRefGoogle ScholarPubMed
Collins, GS, Reitsma, JB, Altman, DG et al. (2015). Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD statement. Annals of Internal Medicine 162:600Google Scholar
Concato, J, Feinstein, AR, Holford, TR (1993). The risk of determining risk with multivariable models. Annals of Internal Medicine 118:201210CrossRefGoogle ScholarPubMed
Coste, J, Fermanian, J, Venot, A (1995). Methodological and statistical problems in the construction of composite measurement scales: A survey of six medical and epidemiological journals. Statistics in Medicine 14:331345CrossRefGoogle Scholar
Counsell, C, Dennis, M (2001). Systematic review of prognostic models in patients with acute stroke. Cerebrovascular Diseases 12:159170Google Scholar
Dahlof, B, Lindholm, LH, Hansson, L et al. (1991). Morbidity and mortality in the Swedish trial in old patients with hypertension (STOP-hypertension). Lancet 338:12811285Google Scholar
Feinstein, AR (1996). Multivariable Analysis: An Introduction. New Haven, CT: Yale University PressGoogle Scholar
Friberg, L, Rosenqvist, M, Lip, GY (2012). Evaluation of risk stratification schemes for ischemic stroke and bleeding in 182678 patients with atrial fibrillation: The Swedish Atrial Fibrillation cohort study. European Heart Journal 33:15001510CrossRefGoogle Scholar
Gage, BF, van Walraven, C, Pearce, LA et al. (2004). Selecting patients with atrial fibrillation for anticoagulation. Stroke risk stratification in patients taking aspirin. Circulation 110:22872292CrossRefGoogle ScholarPubMed
Giles, MF, Rothwell, PM (2007). Risk of stroke early after transient ischaemic attack: A systematic review and meta-analysis. Lancet Neurology 6:10631072Google Scholar
Grover, SA, Lowensteyn, I, Esrey, KL et al. (1995). Do doctors accurately assess coronary risk in their patients? Preliminary results of the coronary health assessment study. British Medical Journal 310:975978Google Scholar
Hackett, ML, Anderson, CS (2005). Predictors of depression after stroke: A systematic review of observational studies. Stroke 36:22962301Google Scholar
Harrell, FE Jr., Lee, KL, Califf, RM et al. (1984). Regression modelling strategies for improved prognostic prediction. Statistics in Medicine 3:143152CrossRefGoogle ScholarPubMed
Harrell, FE Jr., Lee, KL, Mark, DB (1996). Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Statistics in Medicine 15:3613873.0.CO;2-4>CrossRefGoogle ScholarPubMed
Hart, RG (2007). Antithrombotic therapy to prevent stroke in patients with atrial fibrillation. In Treating Individuals: From Randomized Trials to Personalised Medicine, Rothwell, PM (ed.) pp. 265278. London: ElsevierGoogle Scholar
Hayden, JA, Côté, P, Bombardier, C (2006). Evaluation of the quality of prognosis studies in systematic reviews. Annals of Internal Medicine 144:427437CrossRefGoogle ScholarPubMed
Henderson, R, Keiding, N (2005). Individual survival time prediction using statistical models. Journal of Medical Ethics 31:703706CrossRefGoogle ScholarPubMed
Hodges, JR, Warlow, CP (1990a). Syndromes of transient amnesia: Towards a classification. A study of 153 cases. Journal of Neurology, Neurosurgery Psychiatry 53:834843CrossRefGoogle ScholarPubMed
Hodges, JR, Warlow, CP (1990b). The aetiology of transient global amnesia. A case–control study of 114 cases with prospective follow-up. Brain 113:639657CrossRefGoogle ScholarPubMed
International Study of Unruptured Intracranial Aneurysms Investigators (1998). Unruptured intracranial aneurysms: Risks of rupture and risks of surgical intervention. New England Journal of Medicine 1998 339:17251733Google Scholar
Jacob, M, Lewsey, JD, Sharpin, C et al. (2005). Systematic review and validation of prognostic models in liver transplantation. Liver Transplantation 11:814825Google Scholar
Johnston, SC, Rothwell, PM, Nguyen-Huynh, MN et al. (2007). Validation and refinement of scores to predict very early stroke risk after transient ischaemic attack. Lancet 369:283292Google Scholar
Justice, AC, Covinsky, KE, Berlin, JA (1999). Assessing the generalizability of prognostic information. Annals of Internal Medicine 130:515524Google Scholar
Kernan, WN, Feinstein, AR, Brass, LM (1991). A methodological appraisal of research on prognosis after transient ischemic attacks. Stroke 22:11081116Google Scholar
Kim, LG, Johnson, TL, Marson, AG for the MRC MESS Study Group (2006). Prediction of risk of seizure recurrence after a single seizure and early epilepsy: Further results from the MESS trial. Lancet Neurology 5:317322Google Scholar
Laupacis, A, Boysen, G, Connolly, S et al. (1994). Risk factors for stroke and efficacy of antithrombotic therapy in atrial fibrillation. Analysis of pooled data from five randomised controlled trials. Archives of Internal Medicine 154:14491457Google Scholar
Laupacis, A, Sekar, N, Stiell, IG (1997). Clinical prediction rules. A review and suggested modifications of methodological standards. Journal of the American Medical Association 277:488494Google Scholar
Lewis, S (2007). Regression analysis. Practical Neurology 7:259264Google Scholar
Li, W, Boissel, JP, Girard, P et al. (1998). Identification and prediction of responders to a therapy: A model and its preliminary application to actual data. Journal of Epidemiology and Biostatistics 3:189197Google Scholar
Lip, GY, Nieuwlaat, R, Pisters, R et al. (2010). Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: The euro heart survey on atrial fibrillation. Chest 137:263272Google Scholar
Mackillop, WJ, Quirt, CF (1997). Measuring the accuracy of prognostic judgments in oncology. Journal of Clinical Epidemiology 50:2129CrossRefGoogle ScholarPubMed
Mallett, S, Royston, P, Dutton, S et al. (2010). Reporting methods in studies developing prognostic models in cancer: A review. BMC Medicine 8:20CrossRefGoogle ScholarPubMed
Medical Research Council Working Party (1985). MRC trial of treatment of mild hypertension: Principal results. British Medical Journal 291:97104CrossRefGoogle Scholar
Morrow, J, Russell, A, Guthrie, E et al. (2006). Malformation risks of antiepileptic drugs in pregnancy: A prospective study from the UK Epilepsy and Pregnancy Register. Journal of Neurology, Neurosurgery Psychiatry 77:193198Google Scholar
Pagliaro, L, D’Amico, G, Soronson, TIA et al. (1992). Prevention of bleeding in cirrhosis. Annals of Internal Medicine 117:5970CrossRefGoogle ScholarPubMed
Reilly, BM, Evans, AT (2006). Translating clinical research into clinical practice: Impact of using prediction rules to make decisions. Annals of Internal Medicine 144:201209Google Scholar
Rothwell, PM (2003). Incidence, risk factors and prognosis of stroke and TIA: The need for high-quality, large-scale epidemiological studies and meta-analyses. Cerebrovascular Diseases 16(Suppl 3):210Google Scholar
Rothwell, PM, Mehta, Z, Howard, SC et al. (2005). From subgroups to individuals: General principles and the example of carotid endartectomy. Lancet 365:256265Google Scholar
Royston, P, Sauerbrei, W (2004). A new measure of prognostic separation in survival data. Statistics in Medicine 23:723748CrossRefGoogle ScholarPubMed
Royston, P, Altman, DG, Sauerbrei, W (2006). Dichotomizing continuous predictors in multiple regression: A bad idea. Statistics in Medicine 25:127141Google Scholar
Sackett, DL, Whelan, G (1980). Cancer risk in ulcerative colitis: Scientific requirements for the study of prognosis. Gastroenterology 78:16321635Google Scholar
Sanmuganathan, PS, Ghahramani, P, Jackson, PR et al. (2001). Aspirin for primary prevention of coronary heart disease: Safety and absolute benefit related to coronary risk derived from meta-analysis of randomised trials. Heart 85:265271CrossRefGoogle ScholarPubMed
Schafer, JL, Graham, JW (2002). Missing data: Our view of the state of the art. Psychological Methods 7:147177Google Scholar
Schmoor, C, Sauerbrei, W, Schumacher, M (2000). Sample size considerations for the evaluation of prognostic factors in survival analysis. Statistics in Medicine 19:4414523.0.CO;2-N>CrossRefGoogle ScholarPubMed
Schumacher, M, Hollander, N, Sauerbrei, W (1997). Resampling and cross-validation techniques: a tool to reduce bias caused by model building? Statistics in Medicine 16:281328273.0.CO;2-Z>CrossRefGoogle ScholarPubMed
Stevens, DL, Matthews, WB (1973). Cryptogenic drop attacks: An affliction of women. British Medical Journal 1:439442Google Scholar
Stroke Prevention in Atrial Fibrillation Investigators (1995). Risk factors for thromboembolism during aspirin therapy in patients with atrial fibrillation: The Stroke Prevention in Atrial Fibrillation study. Journal of Stroke and Cerebrovascular Diseases 1995; 5:147157Google Scholar
Sun, GW, Shook, TL, Kay, GL (1996). Inappropriate use of bivariable analysis to screen risk factors for use in multivariable analysis. Journal of Clinical Epidemiology. 49:907916Google Scholar
Vach, W (1997). Some issues in estimating the effect of prognostic factors from incomplete covariate data. Statistics in Medicine 16:5772Google Scholar
van Houwelingen, HC, Thorogood, J (1995). Construction, validation and updating of a prognostic model for kidney graft survival. Statistics in Medicine 14:19992008Google Scholar
van Koningsveld, R, Steyerberg, EW, Hughes, RA et al. (2007). A clinical prognostic scoring system for Guillain–Barré syndrome. Lancet Neurology 6:589594CrossRefGoogle ScholarPubMed
Verweij, PJ, van Houwelingen, HC (1993). Cross-validation in survival analysis. Statistics in Medicine 12:23052314CrossRefGoogle ScholarPubMed
Walgaard, C, Lingsma, HF, Ruts, L et al. (2011). Early recognition of poor prognosis in Guillain-Barré syndrome. Neurology 76:968975Google Scholar
West of Scotland Coronary Prevention Group (1996). West of Scotland Coronary Prevention Study: Identification of high-risk groups and comparison with other cardiovascular intervention trials. Lancet 348:13391342Google Scholar
Wyatt, JC, Altman, DG (1995). Commentary. Prognostic models: Clinically useful or quickly forgotten? British Medical Journal 311:15391541Google Scholar
Yusuf, S, Zucker, D, Peduzzi, P et al. (1994). Effect of coronary artery bypass graft surgery on survival: Overview of 10-year results from randomised trials by the Coronary Artery Bypass Graft Surgery Trialists’ Collaboration. Lancet 344:563570Google Scholar

References

Ay, H, Koroshetz, WJ, Benner, T et al. (2005). Transient ischemic attack with infarction: A unique syndrome? Annals of Neurology 57:679686Google Scholar
Benavente, O, Eliasziw, M, Streifler, JY et al. (2001). For the NASCET Collaborators: Prognosis after transient monocular blindness associated with carotid artery stenosis. New England Journal of Medicine 345:10841090CrossRefGoogle Scholar
Bray, JE, Coughlan, K, Bladin, C (2007). Can the ABCD score be dichotomised to identify high-risk patients with transient ischaemic attack in the emergency department?, Emergency Medicine Journal 24:9295Google Scholar
Calvet, D, Lamy, C, Touzé, E et al. (2007). Management and outcome of patients with transient ischemic attack admitted to a stroke unit, Cerebrovascular Diseases 24:8085Google Scholar
Caplan, LR (1996). Posterior Circulation Disease: Clinical Findings, Diagnosis and Management, pp. 2021. Boston, MA: Blackwell Science.Google Scholar
Correia, M, Silva, MR, Magalhaes, R, Guimaraes, L, Silva, MC (2006). Transient ischemic attacks in rural and urban northern Portugal: Incidence and short-term prognosis. Stroke 37:5055Google Scholar
Coull, AJ, Lovett, JK, Rothwell, PM for the Oxford Vascular Study (2004). Population based study of early risk of stroke after transient ischaemic attack or minor stroke: Implications for public education and organisation of services. British Medical Journal 328:326Google Scholar
Coutts, SB, Simon, JE, Eliasziw, M et al. (2005). Triaging transient ischemic attack and minor stroke patients using acute magnetic resonance imaging. Annals of Neurology 57:848854Google Scholar
Cucchiara, BL, Messe, SR, Taylor, RA et al. (2006). Is the ABCD score useful for risk stratification of patients with acute transient ischemic attack? Stroke 37:17101714Google Scholar
Davalos, A, Matias-Guiu, J, Torrent, O et al. (1988). Computed tomography in reversible ischaemic attacks: Clinical and prognostic correlations in a prospective study. Journal of Neurology 235:155158Google Scholar
Dennis, M, Bamford, J, Sandercock, P et al. (1990). Computed tomography in patients with transient ischaemic attacks: When is a transient ischaemic attack not a transient ischaemic attack but a stroke? Journal of Neurology 237:257261CrossRefGoogle Scholar
Douglas, CD, Johnston, CM, Elkins, J et al. (2003). Head computed tomography findings predict short-term stroke risk after transient ischemic attack. Stroke 34:28942899Google Scholar
Dutch TIA Trial Study Group (1993). Predictors of major vascular events in patients with a transient ischemic attack or nondisabling stroke: The Dutch TIA Trial Study Group. Stroke 24:527531CrossRefGoogle Scholar
Evans, GW, Howard, G, Murros, KE et al. (1991). Cerebral infarction verified by cranial computed tomography and prognosis for survival following transient ischemic attack. Stroke 22:431436Google Scholar
Fairhead, JF, Rothwell, PM (2005). The need for urgency in identification and treatment of symptomatic carotid stenosis is already established. Cerebrovascular Diseases 19:355358Google Scholar
Flossman, E, Rothwell, PM (2003). Prognosis of vertebrobasilar transient ischaemic attack and minor ischaemic stroke. Brain 126:19401954Google Scholar
Flossman, E, Touze, E, Giles, MF et al. (2006). The early risk of stroke after vertebrobasilar TIA is higher than after carotid TIA. Cerebrovascular Diseases 21(Suppl 4):6Google Scholar
Giles, MF, Rothwell, PM (2007). Risk of stroke early after transient ischaemic attack: A systematic review and meta-analysis. Lancet Neurology 6:10631072Google Scholar
Giles, MF, Rothwell, PM (2008). Systematic review and pooled analysis of published and unpublished validations of the ABCD and ABCD2 transient ischemic attack risk scores. Stroke 41:667673Google Scholar
Gladstone, DJ, Kapral, MK, Fang, J Laupacis, A, Tu, JV (2004). Management and outcomes of transient ischaemic attacks in Ontario. Canadian Medical Association Journal CMAJ 1707:10991104Google Scholar
Gubitz, G, Sandercock, P (2000). Prevention of ischaemic stroke. British Medical Journal 321:14551459Google Scholar
Gubitz, G, Phillips, S, Dwyer, V (1999). What is the cost of admitting patients with transient ischaemic attacks to hospital? Cerebrovascular Diseases 9:210214Google Scholar
Gulli, G, Marquardt, L, Rothwell, PM et al. (2013). Stroke risk after posterior circulation stroke/transient ischemic attack and its relationship to site of vertebrobasilar stenosis: Pooled data analysis from prospective studies. Stroke 44:598604CrossRefGoogle ScholarPubMed
Hankey, GJ, Slattery, JM, Warlow, CP (1991). The prognosis of hospital-referred transient ischaemic attacks. Journal of Neurology, Neurosurgery Psychiatry 54:793802Google Scholar
Hill, MD, Yiannakoulias, N, Jeerakathil, T et al. (2004). The high risk of stroke immediately after transient ischemic attack. A population-based study. Neurology 62:20152020Google Scholar
Johnston, SC, Gress, DR, Browner, WS et al. (2000). Short-term prognosis after emergency department diagnosis of TIA. Journal of the American Medical Association 284:29012906Google Scholar
Johnston, SC, Rothwell, PM, Nguyen-Huynh, MN et al. (2007). Validation and refinement of scores to predict very early stroke risk after transient ischaemic attack. Lancet 369:283292Google Scholar
Kelly, PJ, Albers, GW, Chatzikonstantinou, A et al. (2016). Validation and comparison of imaging-based scores for prediction of early stroke risk after transient ischemic attack: A pooled analysis of individual-patient data from cohort studies. Lancet Neurology 15:12381247CrossRefGoogle ScholarPubMed
Kleindorfer, D, Panagos, P, Pancioli, A et al. (2005). Incidence and short-term prognosis of transient ischemic attack in a population-based study, Stroke 36:720723Google Scholar
Kolominsky-Rabas, PL, Weber, M, Gefeller, O, Neundoerfer, B, Heuschmann, PU (2001). Epidemiology of ischemic stroke subtypes according to TOAST criteria: Incidence, recurrence, and long-term survival in ischemic stroke subtypes: A population-based study. Stroke 32:27352740Google Scholar
Latchaw, RE, Yonas, H, Hunter, GJ et al. (2003). Guidelines and recommendations for perfusion imaging in cerebral ischemia: A scientific statement for healthcare professionals by the Writing Group on Perfusion Imaging, from the Council on Cardiovascular Radiology of the American Heart Association. Stroke 34:10841104Google Scholar
Lavallée, PC, Mesegaur, E, Abboud, F et al. (2007). A transient ischaemic attack clinic with round-the-clock access (SOS-TIA): Feasibility and effects. Lancet Neurology 6:953960Google Scholar
Lovett, JK, Dennis, MS, Sandercock, PA et al. (2003). Very early risk of stroke after a first transient ischemic attack. Stroke 34:e138e140Google Scholar
Lovett, JK, Coull, AJ, Rothwell, PM (2004a). Early risk of recurrence by subtype of ischemic stroke in population-based incidence studies. Neurology 62:569573CrossRefGoogle ScholarPubMed
Lovett, JK, Gallagher, PJ, Hands, LJ et al. (2004b). Histological correlates of carotid plaque surface morphology on lumen contrast imaging. Circulation 110:21902197Google Scholar
Markus, HS, van der Worp, HB, Rothwell, PM (2013). Posterior circulation ischemic stroke and transient ischemic attack: Diagnosis, investigation, and secondary prevention. Lancet Neurology 12:989998Google Scholar
Marquardt, L, Kuker, W, Chandratheva, A et al. (2009). Incidence and prognosis of ≥50% symptomatic vertebral or basilar artery stenosis: Prospective population-based study. Brain 132:982988Google Scholar
Merwick, A, Albers, GW, Amarenco, P et al. (2010). Addition of brain and carotid imaging to the ABCD2 score to identify patients at early risk of stroke after transient ischemic attack: A multicenter observational study. Lancet Neurology 9:10601069Google Scholar
Mohr, JP, Gautier, JC, Pessin, MS (1992). Internal carotid artery disease. In Stroke, Barnett, HJM Mohr, JP Stein, BM Yatsu, FM (eds.), p. 311. New York, NY: Churchill LivingstoneGoogle Scholar
Molloy, J, Markus, HS (1999). Asymptomatic embolization predicts stroke and TIA risk in patients with carotid artery stenosis. Stroke 30:14401443Google Scholar
National Institute for Health and Clinical Excellence (2017). Stroke and Transient Ischemic Attack in Over 16s: Diagnosis and Initial Management. London: NICEGoogle Scholar
Paul, NL, Simoni, M, Chandratheva, A et al. (2012). Population-based study of capsular warning syndrome and prognosis after early recurrent TIA. Neurology 79:13561362Google Scholar
Petty, GW, Brown, R-DJ, Whisnant, JP et al. (2000). Ischemic stroke subtypes: A population-based study of functional outcome, survival, and recurrence. Stroke 31:10621068Google Scholar
Prabhakaran, S, Chong, JY, Sacco, RL (2007). Impact of abnormal diffusion-weighted imaging results on short-term outcome following transient ischemic attack. Archives of Neurology 64:11051109Google Scholar
Purroy, F, Montaner, J, Rovira, A et al. (2004). Higher risk of further vascular events among transient ischaemic attack patients with diffusion-weighted imaging acute lesions. Stroke 35:23132319Google Scholar
Purroy, F, Molina, CA, Montaner, J, Alvarez-Sabin, J (2007). Absence of usefulness of ABCD score in the early risk of stroke of transient ischemic attack patients. Stroke 38:855856Google Scholar
Rantner, B, Pavelka, M, Posch, L (2005). Carotid endarterectomy after ischemic stroke: Is there a justification for delayed surgery? European Journal of Vascular Endovascular Surgery 30:3640Google Scholar
Redgrave, JN, Schulz, UG, Briley, D et al. (2007a). Presence of acute ischemic lesions on diffusion-weighted imaging is associated with clinical predictors of early risk of stroke after transient ischemic attack. Cerebrovascular Diseases 24:8690Google Scholar
Redgrave, JN, Coutts, SB, Schulz, UG et al. (2007b). Systemic review of associations between the presence of acute ischemic lesions on diffusion-weighted imaging and clinical predictors of early stroke risk after transient ischemic attack. Stroke 38:14821488Google Scholar
Rothwell, PM (2003). Incidence, risk factors and prognosis of stroke and transient ischaemic attack: The need for high-quality large-scale epidemiological studies. Cerebrovascular Diseases 16(Suppl 3):210Google Scholar
Rothwell, PM, Warlow, CP (2005). Timing of TIAs preceding stroke: Time window for prevention is very short. Neurology 64:817820Google Scholar
Rothwell, PM, Giles, MF, Flossmann, E et al. (2005). A simple score (ABCD) to identify individuals at high early risk of stroke after transient ischaemic attack. Lancet 366:2936Google Scholar
Rothwell, PM, Giles, MF, Chandratheva, A on behalf of the Early use of Existing Preventive Strategies for Stroke (EXPRESS) Study (2007). Major reduction in risk of early recurrent stroke by urgent treatment of TIA and minor stroke: EXPRESS Study. Lancet 370:14321442Google Scholar
Sciolla, R, Melis, F for the SINPAC Group (2008). Rapid identification of high-risk transient ischemic attacks: Prospective validation of the ABCD score. Stroke 39:297302Google Scholar
Sivenius, J, Riekkinen, PJ, Smets, P et al. (1991). The European Stroke Prevention Study (ESPS): Results by arterial distribution. Annals of Neurology 29:596600Google Scholar
Song, B, Fang, H, Zhao, L et al. (2013). Validation of the ABCD3-I score to predict stroke risk after transient ischemic attack. Stroke 44:12441248Google Scholar
Sylaja, PN, Coutts, SB, Subramaniam, S for the VISION Study Group (2007). Acute ischemic lesions of varying ages predict risk of ischemic events in stroke/TIA patients. Neurology 68:415419Google Scholar
Tong, DC, Caplan, LR (2007). Determining future stroke risk using MRI: New data, new questions. Neurology 68:398399Google Scholar
Tsivgoulis, G, Spengos, K, Manta, P et al. (2006). Validation of the ABCD score in identifying individuals at high early risk of stroke after a transient ischemic attack: A hospital-based case series study. Stroke 37:28922897Google Scholar
Valton, L, Larrue, V, le Traon, AP (1998). Microembolic signals and risk of early recurrence in patients with stroke or transient ischemic attack. Stroke 29:21252128CrossRefGoogle ScholarPubMed
van Swieten, JC, Kappelle, LJ, Algra, A et al. (1992). Hypodensity of cerebral white matter in patients with transient ischaemic attack or minor stroke: Influence on the rate of subsequent stroke: Dutch TIA Study Group. Annals of Neurology 32:177183Google Scholar
Warlow, CP, Dennis, MS, van Gijn, J et al. (2001). Preventing recurrent stroke and other serious vascular events. In Stroke: A Practical Guide to Management, pp. 653722. Oxford: BlackwellGoogle Scholar
Whitehead, MA, McManus, J, McAlpine, C, Langhorne, P (2005). Early recurrence of cerebrovascular events after transient ischaemic attack. Stroke 36:1CrossRefGoogle ScholarPubMed
Wu, CM, McLaughlin, K, Lorenzetti, DL et al. (2007). Early risk of stroke after transient ischemic attack: A systematic review and meta-analysis. Archives of Internal Medicine 167:24172422Google Scholar

References

Alexandrov, AV, Black, SE, Ehrlich, LE et al. (1997). Predictors of hemorrhagic transformation occurring spontaneously and on anticoagulants in patients with acute ischemic stroke. Stroke 28:11981202Google Scholar
Álvarez-Sabín, J, Maisterra, O, Santamarina, E et al. (2013). Factors influencing hemorrhagic transformation in ischemic stroke. Lancet Neurology 12:689705Google Scholar
Bamford, J, Sandercock, PAG, Dennis, M et al. (1990). A prospective study of acute cerebrovascular disease in the community: The Oxfordshire Community Stroke Project 1981–86. 2. Incidence, case fatality rates and overall outcome at one year of cerebral infarction, primary intracerebral and subarachnoid haemorrhage. Journal of Neurology, Neurosurgery and Psychiatry 53:1622Google Scholar
Bamford, J, Sandercock, P, Dennis, M et al. (1991). Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet 337:15211526.Google Scholar
Berger, C, Fiorelli, M, Steiner, T et al. (2001). Hemorrhagic transformation of ischemic brain tissue: Asymptomatic or symptomatic? Stroke 32:13301335Google Scholar
Cleary, P, Shorvon, S, Tallis, R (2004). Late-onset seizures as a predictor of subsequent stroke. Lancet 363:11841186Google Scholar
Counsell, Dennis M (2001). Systematic review of prognostic models in patients with acute stroke. Cerebrovascular Diseases 12:159170Google Scholar
Counsell, C, Dennis, M, McDowall, M et al. (2002). Predicting outcome after acute and subacute stroke: Development and validation of new prognostic models. Stroke 33:10411047Google Scholar
Cuadrado, E, Ortega, L, Hernández-Guillamon, M et al. (2008). Tissue plasminogen activator (t-PA) promotes neutrophil degranulation and MMP-9 release. Journal of Leukocyte Biology 84:207214Google Scholar
Frank, JI, Schumm, LP, Wroblewski, K et al. (2014). Hemicraniectomy and durotomy upon deterioration from infarction-related swelling trial: Randomized pilot clinical trial. Stroke 45:781787Google Scholar
Karepov, VG, Gur, AY, Bova, I et al. (2006). Stroke-in-evolution: Infarct-inherent mechanisms versus systemic causes. Cerebrovascular Diseases 21:4246Google Scholar
Khatri, P, Wechsler, LR, Broderick, JP (2007). Intracranial hemorrhage associated with revascularization therapies. Stroke 38:431440Google Scholar
Larrue, V, von Kummer, R, del Zoppo, G et al. (1997). Haemorrhagic transformation in acute ischemic stroke. Potential contributing factors in the European Cooperative Acute Stroke Study. Stroke 28:957960Google Scholar
Lovelock, CE, Molyneux, AJ, Rothwell, PM et al. (2007). Change in incidence and aetiology of intracerebral haemorrhage in Oxfordshire, UK, between 1981 and 2006: A population-based study. Lancet Neurology 6:487493Google Scholar
Pitkänen, A, Roivainen, R and Lukasiuk, K (2016). Development of epilepsy after ischemic stroke. Lancet Neurology 15:185197Google Scholar
Slivka, A, Levy, D, Lapinski, RH (1989). Risk associated with heparin withdrawal in ischaemic cerebrovascular disease. Journal of Neurology, Neurosurgery and Psychiatry 52:13321336Google Scholar
Whiteley, WN, Emberson, J, Lees, KR et al. (2016). Risk of intracerebral hemorrhage with alteplase after acute ischemic stroke: A secondary analysis of an individual patient data meta-analysis. Lancet Neurology 15:925933Google Scholar
Yang, MH, Lin, HY, Fu, J et al. (2015). Decompressive hemicraniectomy in patients with malignant middle cerebral artery infarct: A systematic review and meta-analysis. Surgeon 13:230230Google Scholar

References

Ariesen, MJ, Algra, A, Warlow, CP et al. (2006). Predictors of risk of intracerebral haemorrhage in patients with a history of TIA or minor ischaemic stroke. Journal of Neurology, Neurosurgery and Psychiatry 77:9294Google Scholar
Atrial Fibrillation Investigators (1994). Risk factors for stroke and efficacy of anti-thrombotic therapy in atrial fibrillation: analysis of pooled data from five randomized controlled trials. Archives of International Medicine 154:14491457Google Scholar
Brønnum-Hansen, H, Davidsen, M, Thorvaldsen, P et al. (2001). Long-term survival and causes of death after stroke. Stroke 32:21312136Google Scholar
Burn, J, Dennis, M, Bamford, J et al. (1994). Long-term risk of recurrent stroke after a first-ever stroke. The Oxfordshire Community Stroke Project. Stroke 25:333337CrossRefGoogle ScholarPubMed
Carolei, A, Candelise, L, Fiorelli, M et al. (1992). Long-term prognosis of transient ischemic attacks and reversible ischemic neurologic deficits: A hospital-based study. Cerebrovascular Diseases 2:266272Google Scholar
Clark, TG, Murphy, MFG, Rothwell, PM (2003). Long term risks of stroke, myocardial infarction, and vascular death in “low risk” patients with a non-recent transient ischaemic attack. Journal of Neurology, Neurosurgery and Psychiatry 74:577580Google Scholar
Dennis, MS, Bamford, JM, Sandercock, PAG et al. (1989). Incidence of transient ischemic attacks in Oxfordshire, England. Stroke 20:333339Google Scholar
Dennis, MS, Bamford, J, Sandercock, P et al. (1990). Prognosis of transient ischemic attacks in the Oxfordshire Community Stroke Project. Stroke 21:848853Google Scholar
Friberg, L, Rosenqvist, M, Lip, GY (2012). Evaluation of risk stratification schemes for ischemic stroke and bleeding in 182678 patients with atrial fibrillation: the Swedish Atrial Fibrillation cohort study. European Heart Journal 33:15001510Google Scholar
Gage, BF, Waterman, AD, Shannon, W et al. (2001). Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. Journal of the American Medical Association 285:28642870Google Scholar
Hankey, GJ (2003). Long term outcome after ischaemic stroke/transient ischaemic attack. Cerebrovascular Diseases 16(Suppl 1):1419Google Scholar
Hankey, GJ, Warlow, CP (1994). Major Problems in Neurology, Vol. 27: Transient Ischaemic Attacks of the Brain and Eye. London: SaundersGoogle Scholar
Hankey, GJ, Slattery, JM, Warlow, CP (1991). The prognosis of hospital-referred transient ischaemic attacks. Journal of Neurology, Neurosurgery and Psychiatry 54:793802Google Scholar
Hankey, GJ, Slattery, JM, Warlow, CP (1992). Transient ischaemic attacks: which patients are at high (and low) risk of serious vascular events? Journal of Neurology, Neurosurgery and Psychiatry 55:640652Google Scholar
Hankey, GJ, Jamrozik, K, Broadhurst, RJ et al. (2000). Five-year survival after first-ever stroke and related prognostic factors in the Perth Community Stroke Study. Stroke 31:20802086Google Scholar
Hartmann, A, Rundek, T, Mast, H et al. (2001). Mortality and causes of death after first ischemic stroke. Neurology 57:20002005Google Scholar
Heyman, A, Wilkinson, WE, Hurwitz, BJ et al. (1984). Risk of ischemic heart disease in patients with TIA. Neurology 34:626630Google Scholar
Howard, G, Toole, JF, Frye-Pierson, J et al. (1987). Factors influencing the survival of 451 transient ischemic attack patients. Stroke 18:552557Google Scholar
Howard, G, Evans, GW, Rouse, JR III et al. (1994). A prospective re-evaluation of transient ischemic attacks as a risk factor for death and fatal or nonfatal cardiovascular events. Stroke 25:342345Google Scholar
Hughes, M, Lip, GY (2007). Guideline Development Group for the NICE national clinical guideline for management of atrial fibrillation in primary and secondary care. Risk factors for anticoagulation-related bleeding complications in patients with atrial fibrillation: A systematic review. Quarterly Journal of Medicine 100:599607Google Scholar
Joakimsen, O, Bonaa, KH, Mathiesen, EB et al. (2000). Prediction of mortality by ultrasound screening of a general population for carotid stenosis: The Tromso Study. Stroke 31:18711876Google Scholar
Kernan, WN, Feinstein, AR, Brass, LM (1991). A methodological appraisal of research on prognosis after transient ischemic attacks. Stroke 22:11081116Google Scholar
Kernan, WN, Viscoli, CM, Brass, LM et al. (2000). The Stroke Prognosis Instrument II (SPI II): A clinical prediction instrument for patients with transient ischaemia and non-disabling ischaemic stroke. Stroke 31:456462Google Scholar
Lip, GY, Nieuwlaat, R, Pisters, R et al. (2010a). Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: The Euro Heart Survey on Atrial Fibrillation. Chest 137:263272Google Scholar
Lip, GY, Frison, L, Halperin, JL et al. (2010b). Comparative validation of a novel risk score for predicting bleeding risk in anticoagulated patients with atrial fibrillation: The HAS-BLED (Hypertension, Abnormal Renal/Liver Function, Stroke, Bleeding History or Predisposition, Labile INR, Elderly, Drug/Alcohol Concomitantly) score. Journal of American College of Cardiology 57:173180Google Scholar
Mathur, KS, Kashyap, SK, Kumar, V (1963). Correlation of the extent and severity of atherosclerosis in the coronary and cerebral arteries. Circulation 27:929934Google Scholar
Petty, GW, Brown, RD Jr., Whisnant, JP et al. (2000). Ischemic stroke subtypes. A population-based study of functional outcome, survival and recurrence. Stroke 31:10621068Google Scholar
Pisters, R, Lane, DA, Nieuwlaat, R et al. (2010). A novel user-friendly score (HAS-BLED) to assess 1-year risk of major bleeding in patients with atrial fibrillation: The Euro Heart Survey. Chest 138:10931100Google Scholar
Ricci, S, Cantisani, AT, Righetti, E et al. (1998). Long term follow up of TIAs: The SEPIVAC Study. Neuroepidemiology 17:54Google Scholar
Scmidt, EV, Smirnov, VE, Ryabova, VS (1988). Results of the seven-year prospective study of stroke patients. Stroke 19:942949Google Scholar
Solberg, LA, McGarry, PA, Moossy, J et al. (1968). Severity of atherosclerosis in cerebral arteries, coronary arteries, and aortas. Annals of the New York Academy of Sciences 149:956973Google Scholar
Stroke Prevention in Atrial Fibrillation Investigators (1992a). Predictors of thromboembolism in atrial fibrillation, I: Clinical features of patients at risk. Annals of Internal Medicine 116:15Google Scholar
Stroke Prevention in Atrial Fibrillation Investigators (1992b). Predictors of thromboembolism in atrial fibrillation, II: Echocardiographic features of patients at risk. Annals of Internal Medicine 116:612Google Scholar
Stroke Prevention in Reversible Ischemia Trial (SPIRIT) Study Group (1997). A randomized trial of anticoagulants versus aspirin after cerebral ischemia of presumed arterial origin. Annals of Neurology 42:857865Google Scholar
Terent, A (1990). Survival after stroke and transient ischemic attacks during the 1970s and 1980s. Stroke 21:848853Google Scholar
Touzé, E, Varenne, O, Chatellier, G et al. (2005). Risk of myocardial infarction and vascular death after transient ischemic attack and ischemic stroke: a systematic review and meta-analysis. Stroke 36:27482755Google Scholar
van Latum, JC, Koudstaal, P, Venables, GS et al. (1995). Predictors of major vascular events in patients with a transient ischemic attack or minor ischemic stroke and with non-rheumatic atrial fibrillation. Stroke 26:801806Google Scholar
van Wijk, I, Kappelle, LJ, van Gijn, J et al. (2005) For the LILAC study group. Long-term survival and vascular event risk after transient ischaemic attack or minor stroke: a cohort study. Lancet 365:20982104Google Scholar

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