Modeling of in hospital mortality determinants in myocardial infarction patients, with and without stroke: A national study in Iran
Ali Ahmadi1, Arsalan Khaledifar2, Koorosh Etemad3
1 Department of Epidemiology and Biostatistics, School of Health, Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran
2 Department of Cardiology, School of Medicine, Modeling in Health Research Center, Hajar Hospital, Shahrekord University of Medical Sciences, Shahrekord, Iran
3 Department of Epidemiology, School of Public Health, Environmental and Occupational Hazards Control Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
|Date of Web Publication||28-Jan-2016|
Department of Epidemiology, School of Public Health, Environmental and Occupational Hazards Control Research Center, Shahid Beheshti University of Medical Sciences, Tehran
Source of Support: None, Conflict of Interest: None
Background: The data and determinants of mortality due to stroke in myocardial infarction (MI) patients are unknown. This study was conducted to evaluate the differences in risk factors for hospital mortality among MI patients with and without stroke history. Materials and Methods: This study was a retrospective, cohort study; 20,750 new patients with MI from April, 2012 to March, 2013 were followed up and their data were analyzed according to having or not having the stroke history. Stroke and MI were defined based on the World Health Organization's definition. The data were analyzed by logistic regression in STATA software. Results: Of the 20,750 studied patients, 4293 had stroke history. The prevalence of stroke in the studied population was derived 20.96% (confidence interval [CI] 95%: 20.13-21.24). Of the patients, 2537 (59.1%) had ST-elevation MI (STEMI). Mortality ratio in patients with and without stroke was obtained 18.8% and 10.3%, respectively. The prevalence of risk factors in MI patients with and without a stroke is various. The adjusted odds ratio of mortality in patients with stroke history was derived 7.02 (95% CI: 5.42-9) for chest pain resistant to treatment, 2.39 (95% CI: 1.97-2.9) for STEMI, 3.02 (95% CI: 2.5-3.64) for lack of thrombolytic therapy, 2.2 (95% CI: 1.66-2.91) for heart failure, and 2.17 (95% CI: 1.6-2.9) for ventricular tachycardia. Conclusion: With regards to the factors associated with mortality in this study, it is particularly necessary to control the mortality in MI patients with stroke history. More emphasis should be placed on the MI patients with the previous stroke over those without in the interventions developed for prevention and treatment, and for the prevention of avoidable mortalities.
Keywords: Mortality, myocardial infarction, risk factor, stroke
|How to cite this article:|
Ahmadi A, Khaledifar A, Etemad K. Modeling of in hospital mortality determinants in myocardial infarction patients, with and without stroke: A national study in Iran. J Res Med Sci 2016;21:74
|How to cite this URL:|
Ahmadi A, Khaledifar A, Etemad K. Modeling of in hospital mortality determinants in myocardial infarction patients, with and without stroke: A national study in Iran. J Res Med Sci [serial online] 2016 [cited 2020 Feb 17];21:74. Available from: http://www.jmsjournal.net/text.asp?2016/21/1/74/189687
| Introduction|| |
Stroke, after myocardial infarction (MI), is the second leading reason for mortality in Iran as with many countries worldwide. ,, The epidemiology of stroke has already been investigated in the American, European, African, and Asian countries. ,,,,,,, No comprehensive study has yet investigated the epidemiology of stroke, particularly in MI patients, in Iran, one of the largest countries in Southwest Asia. Stroke and MI share many risk factors, most prevalent of which are smoking, dyslipidemia, type 2 diabetes, and hypertension. ,, Coronary heart disease is highly preventable in stroke patients. 
The risk factors for stroke and MI, especially smoking, hypertension, and dyslipidemia are highly prevalent in Iran, as well. ,, According to projections, stroke continues to be the second leading cause of mortality worldwide till 2030.  Urbanism, increased life expectancy, reduction in childbirth, aging and elderly population, epidemiological changes, socioeconomic status, geographical conditions, and lifestyles such as poor diet, stress, and low mobility are the main causes of the burden of noncommunicable diseases, particularly stroke. ,
Because the determinants of stroke in different communities are various, ,, we require knowledge about the risk factors and determinants of mortality in a community for effective planning and selection of appropriate strategies for the prevention and management of stroke and heart attack as the most important causes of death. ,
Since no comprehensive study has yet been investigated the status and mortality determinants of stroke in MI patients in Iran, this study is conducted to determine and compare the determinants of mortality due to stroke in MI patients.
| Materials and methods|| |
In this retrospective cohort study, the data obtained from the MI Registry of Iran's Cardiovascular Diseases Surveillance System were analyzed. Around 20,750 hospitalized patients with MI with a new presentation (hospitalized in 540 hospitals) between April, 2012 and March, 2013 were enrolled. All the patients' data were entered into a computerized retrospective observational data bank. The study was approved by the Management Center of Noncommunicable Diseases and the Department of Cardiovascular Diseases Prevention of Iran's Ministry of Health and Medical Education (approval no. 305/837). The research followed the principles of the Declaration of Helsinki; the researchers did not conduct any interventions on the patients, and an Institutional Review Board approved this research. The study protocol was approved by an Independent Scientific Review Committee (at Shahid Beheshti University Medical of Sciences) (no. 1392-1-85-12129). Inclusion criteria were determined according to the World Health Organization (WHO) and World Heart Federation definition of MI diagnosis per the International Classification of Diseases-10 codes I21 and I22. 
Patients with MI history or no definite diagnosis by a cardiologist were excluded from the study. The data on age, gender, education, ischemic heart disease symptoms, hospital stay duration, smoking, dyslipidemia, hypertension, type 2 diabetes, heart failure, and family history of cardiovascular diseases were gathered. Stroke history was defined based on the WHOs definition "rapidly developing signs of focal (or global) disturbance of cerebral function lasting >24 h (unless interrupted by surgery or death), with no apparent nonvascular cause." Therefore, patients with transient cerebral ischemia or stroke events were excluded if they had blood disease or brain tumors. Moreover, patients with secondary strokes caused by trauma, acute hemorrhagic stroke, or transient ischemic attack were excluded. , After a definite diagnosis of MI by a cardiologist, the data on the left bundle branch block, right bundle branch block, atrial fibrillation, ventricular and atrial tachycardia, type and site of MI, and use of therapeutic regimens such as coronary artery bypass grafting, percutaneous coronary intervention, and thrombolytic therapy were recorded.
The cohort of patients was defined by the date at MI diagnosis, hospital stay, and follow-up till discharge or death (outcome). Hospital mortality due to MI was considered a dependent variable. Odds ratio (OR) of mortality for clinical and demographic risk factors were calculated by logistic regression. OR of mortality was calculated as the crude and adjusted ratio for patients with and without stroke by simple and multiple logistic regression models. First, univariate analysis was conducted. To control confounders, we entered the significant or approximately significant variables into a multiple regression model. For data analysis, Chi-square, t-test, and regression model in Stata software (Stata Corp. 2011, Stata Statistical Software: Release 14, College Station, TX: Stata Corp LP, USA) were used and P < 0.05 was considered the level of significance.
| Results|| |
Of the 20,750 studied patients with MI, 4293 had a stroke history. The prevalence of stroke in the studied population was derived 20.96% (confidence interval CI 95%: 20.13-21.24). Mean standard deviation age at MI incidence was 64.38 (12.9) years in patients with stroke history and 60.37 (13.3) years in patients without, with a significant difference (P < 0.001). Half of the patients with stroke history had 30-64-year-old. About 43.6% of them had 65-84-year-old and 5.4% 85-106. About 64.8% of these patients were male, 52.8% of them were illiterate, and only 4.9% had an academic education. The prevalence of smoking was derived 23.9% in them. The prevalence of diabetes, hypertension, hypercholesterolemia, and heart failure was obtained 30%, 56.5%, 27.3%, and 8.1% in patients with stroke history and 20.1%, 30%, 15.4%, and 8% in patients without stroke history, respectively. The ratio of cardiovascular surgery, percutaneous coronary intervention, and thrombolytic therapy was obtained 6.4%, 5.8%, and 41.1% in the former group and 1.6%, 7.1%, and 45.3% in the latter, respectively. The demographic characteristics and individual risk factors in patients with and without stroke are shown in [Table 1].
|Table 1: Demographic and medical history of myocardial infarction patients with and without stroke|
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Within 1 year of study, 18.8% of the stroke patients deceased. The mortality ratio in all patients was derived 12.1%. Of the 4293 patients with stroke, 2537 (59.1%) had ST-elevation MI (STEMI). Mortality ratio was obtained 18.8% in patients stroke history and 10.3% in the without. The clinical characteristics and risk factors in the patients according to the type of hospital diagnosis and therapeutic measures are shown in [Table 2]. The ratio of cardiovascular surgery, percutaneous coronary intervention, and thrombolytic therapy was obtained, respectively, 6.4%, 5.8%, and 41.1%. By logistic regression, the mortality-associated factors were different in the MI patients with and without stroke history. The OR of the studied factors is shown in [Table 3]. The adjusted OR of mortality in patients with stroke history was derived 7.02 (95% CI: 5.42-9) for chest pain resistant to treatment, 2.39 (95% CI: 1.97-2.9) for STEMI, 3.02 (95% CI: 2.5-3.64) for lack of thrombolytic therapy, 2.2 (95% CI: 1.66-2.91) for heart failure, and 2.17 (95% CI: 1.6-2.9) for ventricular tachycardia. Considering other potential covariates and the confounders of hospital mortality in patients with stroke, we obtained the highest adjusted OR of hospital mortality in patients with stroke for chest pain resistant to treatment followed by lack of thrombolytic therapy and STEMI.
|Table 2: Prevalence of clinical risk factors in myocardial infarction patients with and without stroke|
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|Table 3: Risk factors for hospital mortality in myocardial infarction patients with and without stroke|
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| Discussion|| |
In this study, the risk factors in the MI patients with and without stroke history were investigated and compared for the first time in Iran. In reliable, electronic databases such as PubMed and Scopus, we found no study to model and compare the characteristics of the two groups of patients as with our study. Our study indicated that the pattern of determinants of hospital MI mortality with and without a stroke is various. The mean age at incidence in our study is similar to a study in Singapore comparing the risk factors for stroke in Chinese, Indian, and Malaysian ethnic populations. The study in Singapore reported the mean age of stroke patients to be 64.1 years. In the study of Singapore, hypertension and hypercholesterolemia were found to be the most prevalent risk factors. The prevalence of hypertension was obtained 83.2%, 85%, and 84.1% in Chinese, Malaysian, and Indian ethnics, respectively, which is twice higher than the prevalence of hypertension in the patients in Iran. , Moreover, the prevalence of smoking was obtained 11.8%, 20%, and 15.9% in Chinese, Malaysian, and Indian ethnics in Singapore, respectively. The prevalence of smoking was obtained approximately 24% in our study, which is higher than that reported by the study of Singapore. In the study of Singapore, the prevalence of diabetes was reported to be 67.5% in Malaysian ethnics and 39.8% in Chinese ethnics while it was 27.9% in the patients of our study. Within 1 year of study, hospital mortality was obtained 9.1%, 3.4%, and 2.5% in Indian, Chinese, and Malaysian ethnics, respectively. The corresponding figure was obtained 32% in the patients of our study. This inconsistency can be explained by the difference in lifestyles, life expectancy, and the incidence of stroke risk factors. Another explanation can be related to access to therapeutic and hospital services to prevent mortality due to stroke. However, it is noteworthy that the sample size in the study of Singapore seems unsatisfactorily small, which might be another reason for the inconsistency of the findings. 
A review article reported that the age at stroke incidence was 68.6 years in men and 72.9 years in women, and the incidence and prevalence of stroke were higher in men than women. Although the age of incidence in our study is younger than the age reported in this review article, the gender differences in our study and this review article are consistent. , The prevalence of stroke in our study was 20.96% higher than Japanese patients. A nationwide multicenter cooperative cohort study of Japanese patients with MI and stroke reported stroke history (14.7%) to be more frequent than MI history (2.6%) in patients with stroke, whereas stroke history (6.6%) was less frequent than MI history (7.6%) in patients with MI.  The mean age at MI incidence in our study is lower than a study in Australia that reported the mean age of patients with stroke was 78.6 years. The difference in lifestyle, life expectancy, and patterns of risk factors for noncommunicable diseases as well as the larger elderly population of Australia can be some reasons for the discrepancy in the mean age at the incidence of stroke. In a study in Nigeria, the prevalence of hypertension and dyslipidemia was reported to be 69.4% and 21.1%, respectively. The difference in the population and environment of the study may be the main reasons for the inconsistency of the findings.  In a study in Australia and Europe (Finland, Norway, Belgium, France, Germany, the Netherlands, Switzerland, Italy, Greece, and Hungary), 3944 patients with stroke were studied, and smoking, dyslipidemia, and hypertension were reported to be the most prevalent (48.7%, 45.8%, and 35.9%, respectively) risk factors for stroke, which are, except hypertension, higher than our study. The prevalence of diabetes and heart failure in the study in Europe was obtained 6.5-11.1% and 3.8-4.2%, respectively,  which is lower than the corresponding figures in our study. The study in Europe has recommended that adoption of a primary strategy to avoid a stroke in young adolescents and the intervention aimed to change and/or decrease the highly prevalent risk factors that can be mitigated is an important principle of the stroke control. In Brazil, the risk factors for stroke were studied, and the prevalence of hypertension, diabetes, and stroke history was reported to be 29.9%, 9.1%, and 2.1%, respectively, which are lower than the present study.  In a study in Japan, 1389 incidence of stroke were registered from 1988 to 2004. The mean age at incidence was 73.3 years in men and 76.8 years in women. Moreover, the prevalence of hypertension, diabetes, dyslipidemia, smoking, and heart attack was 55%, 19.3%, 17.9%, 25.9%, and 6.9%, respectively.  In another study in Japan, the fatality rate due to stroke was obtained 14.9% and 15.7% in men and women, respectively. Since life expectancy is much higher in Japan than Iran and the mean age at stroke incidence is expected to be younger in Iran than Japan, the determinants of hospital mortality in our study are similar to a study reporting that MI history, diabetes, gender, and age are the most common determinants of outcome in intracerebral hemorrhage patients.  Interestingly, the prevalence of risk factors in the MI patients without stroke in Iran and Japan is similar. The prevalence of manageable risk factors is being controlled in patients with stroke and MI and was obtained lower compared to other studies. In a review article, the fatality rate of stroke within a month after the onset of the disease was reported to be 17% in Japan, 33% in Italy, and 22.9% overall. The fatality of stroke has been derived 32.1%, which is higher than Italy. The difference may be explained by the access to better therapeutic services in hospitals and health-care facilities in Italy compared with Iran. In a study in Iran, losing the golden time to start thrombolytic therapy, lack of beds in the Intensive Care Units, and failure to afford the facilities and services were some of the obstacles to initiating the treatment in stroke and MI patients.  In Iran, MI patients with stroke history appear to control and mitigate the risk factors themselves. , Our study is the first report in Iran and indicated that the pattern of determinants of hospital MI mortality with and without a stroke is various. Therefore, adopting an appropriate strategy for the treatment and prevention of death in the two groups of the patients requires close attention to the characteristics of each group of the patients. In addition, our study demonstrated that the risk factors including hypertension, diabetes, smoking, dyslipidemia, and heart failure were more prevalent in MI patients with stroke history than those without. MI patients without stroke history appear to control and mitigate the risk factors themselves. Therefore, it is recommended to give greater priority to the MI patients with the previous stroke over those without in Iran for training, healthcare, and control of the risk factors such as hypertension, diabetes, and smoking to enhance the cost-effectiveness of the interventions for prevention and treatment and to prevent avoidable mortalities. As no similar study was found to make a closer comparison between our and others' findings, similar studies in other countries are needed to confirm the present study findings.
Limitations of the study
In this study only the MI patients who died in hospital were investigated. Hence, the findings can be generalized only to hospitalized patients. In addition, tissue plasminogen activator thrombolytic therapy was not considered in MI patients with the previous stroke. We did not gather any treatment information about these patients before MI. Because no similar study, to the best of our knowledge, was found to compare our and others' findings more closely, similar studies in other countries should be conducted to give more definite explanations.
| Conclusion|| |
We used a large-scale database in Iran. Our study demonstrated that the risk factors including hypertension, diabetes, smoking, dyslipidemia, and heart failure were more prevalent in the MI patients with a stroke history than those without. In fact, the MI patients without stroke history appear to control and mitigate the risk factors themselves. Chest pain resistant to treatment gave the highest adjusted OR of hospital mortality in patients with stroke followed by no thrombolytic therapy and STEMI. It is recommended to give greater priority to the MI patients with the previous stroke over those without in Iran for training, healthcare, and control of the risk factors as well as to enhance the cost-effectiveness of the interventions for prevention and treatment.
We gratefully thank the cardiologists and neurologists, colleagues, executors, and advisors of Iran's MI Registry Program, particularly Dr. Samavat and Dr. Hojabri. Moreover, the faculty members of Department of Epidemiology of Shahid Beheshti University of Medical Sciences, especially Dr. Soori and Dr. Mehrabi, are sincerely acknowledged for their assistance in conducting this study to access the data (Grant No. 1392-1-85-12129). We also are thankful to Deputy of Research and Technology of Shahrekord University of Medical Sciences for funding my research (Grant No. 1806).
Financial support and sponsorship
Conflicts of interest
The authors have no conflicts of interest.
| Authors Contributors|| |
AA, AK and KE contributed to the design of the research protocol and supervised its implementation. AA and KE analysed the data and AA, AK and KE drafted the article. All of the authors approved the final version of of the manuscript before publishing and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All of the authors reviewed drafts of the article and contributed to the conceptual framework.
| References|| |
Ahmadi A, Soori H, Mehrabi Y, Etemad K, Samavat T, Khaledifar A. Incidence of acute myocardial infarction in Islamic Republic of Iran: A study using national registry data in 2012. East Mediterr Health J 2015;21:5-12.
Ahmadi A, Soori H, Mehrabi Y, Etemad K. Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry. J Res Med Sci 2015;20:434-9.
Ahmadi A, Soori H, Mobasheri M, Etemad K , Khaledifar A. Heart failure, the outcomes, predictive and related factors in Iran. Journal of Mazandaran University of Medical Sciencesi 2014;24:180-8. .
Wang Y, Lichtman JH, Dharmarajan K, Masoudi FA, Ross JS, Dodson JA, et al.
National trends in stroke after acute myocardial infarction among medicare patients in the United States: 1999 to 2010. Am Heart J 2015;169:78-85.e4.
Cheng CL, Chien HC, Lee CH, Lin SJ, Yang YH. Validity of in-hospital mortality data among patients with acute myocardial infarction or stroke in National Health Insurance Research Database in Taiwan. Int J Cardiol 2015;201:96-101.
Smajlovic D. Strokes in young adults: Epidemiology and prevention. Vasc Health Risk Manag 2015;11:157-64.
Ng WY, Tan GS, Ong PG, Cheng CY, Cheung CY, Wong DW, et al.
Incidence of myocardial infarction, stroke, and death in patients with age-related macular degeneration treated with intravitreal anti-vascular endothelial growth factor therapy. Am J Ophthalmol 2015;159:557-64.e1.
Lekoubou A, Nkoke C, Dzudie A, Kengne AP. Stroke admission and case-fatality in an urban medical unit in sub-Saharan Africa: A fourteen year trend study from 1999 to 2012. J Neurol Sci 2015;350:24-32.
Ahmadi-Ahangar A, Sheikh Z, Khani A, Taheri ST. Sex-differences in the incidence of stroke: Should we change our traditional belief? Clin Neurol Neurosurg 2015;131:77.
Sun XG, Wang YL, Zhang N, Wang T, Liu YH, Jin X, et al.
Incidence and trends of stroke and its subtypes in Changsha, China from 2005 to 2011. J Clin Neurosci 2014;21:436-40.
Liang Y, Liu R, Du S, Qiu C. Trends in incidence of hypertension in Chinese adults, 1991-2009: The China Health and Nutrition Survey. Int J Cardiol 2014;175:96-101.
Valenza MC, Baranchuk A, Valenza-Demet G, Muñoz-Casaubon T, Martin-Navajas JA, Healey J. Prevalence of risk factors for atrial fibrillation and stroke among 1210 patients with sleep disordered breathing. Int J Cardiol 2014;174:73-6.
von Sarnowski B, Putaala J, Grittner U, Gaertner B, Schminke U, Curtze S, et al.
Lifestyle risk factors for ischemic stroke and transient ischemic attack in young adults in the Stroke in Young Fabry Patients study. Stroke 2013;44:119-25.
Feigin VL, Lawes CM, Bennett DA, Anderson CS. Stroke epidemiology: A review of population-based studies of incidence, prevalence, and case-fatality in the late 20 th
century. Lancet Neurol 2003;2:43-53.
Nadeau SE, Rose DK, Dobkin B, Wu SS, Dai YE, Schofield R, et al.
Likelihood of myocardial infarction during stroke rehabilitation preceded by cardiovascular screening and an exercise tolerance test: The Locomotor Experience Applied Post-Stroke (LEAPS) trial. Int J Stroke 2014;9:1097-104.
Ahmadi A, Soori H, Sajjadi H. Modeling of in hospital mortality determinants in myocardial infarction patients, with and without type 2 diabetes, undergoing pharmaco-invasive strategy: The first national report using two approaches in Iran. Diabetes Res Clin Pract 2015;108:216-22.
Ahmadi A, Mobasheri M, Hashemi-Nazari SS, Baradaran A, Choobini ZM. Prevalence of hypertension and type 2 diabetes mellitus in patients with colorectal cancer and their median survival time: A cohort study. J Res Med Sci 2014;19:850-4.
Ahmadi A, Soori H, Sajjadi H, Nasri H, Mehrabi Y, Etemad K. Current status of the clinical epidemiology of myocardial infarction in men and women: A national cross-sectional study in Iran. Int J Prev Med 2015;6:14.
Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3:e442.
Fisher A, Martin J, Srikusalanukul W, Davis M. Trends in stroke survival incidence rates in older Australians in the new millennium and forecasts into the future. J Stroke Cerebrovasc Dis 2014;23:759-70.
Amarenco P, Abboud H, Labreuche J, Arauz A, Bryer A, Lavados PM, et al.
Impact of living and socioeconomic characteristics on cardiovascular risk in ischemic stroke patients. Int J Stroke 2014;9:1065-72.
Li M, Zhang Z, Chen Y. A comparison of stroke and coronary risks in Chinese and American. Int J Cardiol 2015;184:251-3.
Lich KH, Tian Y, Beadles CA, Williams LS, Bravata DM, Cheng EM, et al.
Strategic planning to reduce the burden of stroke among veterans: Using simulation modeling to inform decision making. Stroke 2014;45:2078-84.
Ahmadi A, Golshahi J, Khaledi-Far A, Soori H, Mehrabi Y, Etemed K. The pattern of in-hospital mortality of myocardial infarction and associated factors in Iran: A national study. J Isfahan Med Sch 2015;32:2174-83.
Asplund K, Tuomilehto J, Stegmayr B, Wester PO, Tunstall-Pedoe H. Diagnostic criteria and quality control of the registration of stroke events in the MONICA project. Acta Med Scand Suppl 1988;728:26-39.
Roy-O′Reilly M, McCullough LD. Sex differences in stroke: The contribution of coagulation. Exp Neurol 2014;259:16-27.
Appelros P, Stegmayr B, Terént A. Sex differences in stroke epidemiology: A systematic review. Stroke 2009;40:1082-90.
Uchiyama S, Shibata Y, Hirabayashi T, Mihara B, Hamashige N, Kitagawa K, et al.
Risk factor profiles of stroke, myocardial infarction, and atrial fibrillation: A Japanese Multicenter Cooperative Registry. J Stroke Cerebrovasc Dis 2010;19:190-7.
Copstein L, Fernandes JG, Bastos GA. Prevalence and risk factors for stroke in a population of Southern Brazil. Arq Neuropsiquiatr 2013;71:294-300.
Turin TC, Kita Y, Rumana N, Nakamura Y, Takashima N, Ichikawa M, et al.
Ischemic stroke subtypes in a Japanese population: Takashima Stroke Registry, 1988-2004. Stroke 2010;41:1871-6.
[Table 1], [Table 2], [Table 3]