Clinical Sciences. Prediction of Cardioembolic, Arterial, and Lacunar Causes of Cryptogenic Stroke by Gene Expression and Infarct Location

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1 Clinical Sciences Prediction of Cardioembolic, Arterial, and Lacunar Causes of Cryptogenic Stroke by Gene Expression and Infarct Location Glen C. Jickling, MD, MAS; Boryana Stamova, PhD; Bradley P. Ander, PhD; Xinhua Zhan, MD, PhD; Dazhi Liu, PhD; Shara-Mae Sison, BS; Piero Verro, MD; Frank R Sharp, MD Background and Purpose The cause of ischemic stroke remains unclear, or cryptogenic, in as many as 35% of patients with stroke. Not knowing the cause of stroke restricts optimal implementation of prevention therapy and limits stroke research. We demonstrate how gene expression profiles in blood can be used in conjunction with a measure of infarct location on neuroimaging to predict a probable cause in cryptogenic stroke. Methods The cause of cryptogenic stroke was predicted using previously described profiles of differentially expressed genes characteristic of patients with cardioembolic, arterial, and lacunar stroke. RNA was isolated from peripheral blood of 131 cryptogenic strokes and compared with profiles derived from 149 strokes of known cause. Each sample was run on Affymetrix U133 Plus 2.0 microarrays. Cause of cryptogenic stroke was predicted using gene expression in blood and infarct location. Results Cryptogenic strokes were predicted to be 58% cardioembolic, 18% arterial, 12% lacunar, and 12% unclear etiology. Cryptogenic stroke of predicted cardioembolic etiology had more prior myocardial infarction and higher CHA 2 DS 2 -VASc scores compared with stroke of predicted arterial etiology. Predicted lacunar strokes had higher systolic and diastolic blood pressures and lower National Institutes of Health Stroke Scale compared with predicted arterial and cardioembolic strokes. Cryptogenic strokes of unclear predicted etiology were less likely to have a prior transient ischemic attack or ischemic stroke. Conclusions Gene expression in conjunction with a measure of infarct location can predict a probable cause in cryptogenic strokes. Predicted groups require further evaluation to determine whether relevant clinical, imaging, or therapeutic differences exist for each group. (Stroke. 2012;43: ) Key Words: cryptogenic stroke diagnosis gene expression ischemic stroke The cause of stroke remains unclear, or cryptogenic, in as many as 35% of ischemic strokes despite careful clinical evaluation and diagnostic imaging. 1,2 This corresponds to cryptogenic strokes per year (32 per hour) in the United States alone. Knowing the cause of stroke is essential to optimally implement prevention therapy. Given the 2-year mortality rate of cryptogenic strokes is 39%, there remains a significant need to prevent cardiovascular disease in this subtype of stroke. 3 Accurate determination of stroke cause is also an important component in patient prognosis and in studies of stroke epidemiology, genetics, and therapeutics. Thus, additional approaches to determine the cause of cryptogenic strokes are required. When predicting the cause of cryptogenic stroke, stratification by infarct location can aid prediction. Cryptogenic small deep infarcts (SDIs) occurring in the regions of the penetrating arteries require lacunar, arterial, and cardiac disease all to be considered as a potential cause of stroke. 4 However, in cryptogenic non-sdis, only arterial and cardiac disease need to be considered as a potential cause of stroke. Other less common causes may contribute to either of these groups. Thus, infarct location can reduce the number of potential causes of stroke that need to be considered in the non-sdi group, which simplifies prediction models of cryptogenic stroke cause. We recently described a gene expression profile to distinguish cardioembolic from arterial stroke and a separate gene expression profile to distinguish lacunar from nonlacunar stroke. 4,5 In patients with cryptogenic stroke, these profiles may predict a probable cause to guide diagnostic and therapeutic studies. The profiles are based on differential inflammatory and prothrombotic states present in subtypes of stroke. In this study, we describe the integration of the 2 gene expression profiles with a measure of infarct location on Received December 20, 2011; accepted April 10, From the Department of Neurology and MIND Institute, University of California at Davis, Sacramento, CA. The online-only Data Supplement is available at Correspondence to Glen C. Jickling, MD, MAS, University of California at Davis, MIND Institute, th Street, Sacramento, CA gcjickling@ucdavis.edu 2012 American Heart Association, Inc. Stroke is available at DOI: /STROKEAHA

2 Jickling et al Cryptogenic Stroke Prediction 2037 Figure 1. Flow diagram for the prediction of cryptogenic stroke by infarct location and gene expression profiles. Cryptogenic strokes were divided into small deep infarcts (SDIs) and non- SDIs by location of infarct on neuroimaging. Cryptogenic SDIs were predicted to be lacunar or nonlacunar stroke using a 41-gene profile. SDIs of predicted nonlacunar stroke were then predicted to be arterial or cardioembolic stroke using a 40-gene profile. Cryptogenic non-sdis were predicted to be arterial or cardioembolic stroke using the 40-gene profile. neuroimaging to predict the probable cause of cryptogenic stroke. Methods Study Patients Patients with acute ischemic stroke were enrolled from the University of California Davis and as part of the Combined Approach to Lysis Utilizing Eptifibatide and rtpa in Acute Ischemic Stroke (CLEAR) trial at the University of Cincinnati as previously described 6 (NCT at Clinical-Trials.gov). The Institutional Review Board at each site approved the study protocol and written informed consent was obtained from each patient. Patients with ischemic stroke were 18 years of age, had acute ischemia on neuroimaging, and new neurological deficits persisting 24 hours. All patients had standardized clinical evaluations. Blood samples were drawn into PAXgene tubes (PreAnalytiX, Hilden, Germany) within 72 hours of stroke onset. A total of 131 cryptogenic stroke samples were analyzed using gene expression profiles derived from 149 strokes of known cause (79 cardioembolic, 40 arterial, 30 lacunar). The cause of stroke was determined by 2 board-certified stroke neurologists based on medical history, blood tests, neuroimaging, Doppler, vascular angiography, electrocardiography, echocardiogram, and 24- to 48-hour cardiac monitoring. Strokes of arterial, cardioembolic, and lacunar etiology that were used to derive the expression profiles have been previously described. 4,5 In brief, arterial strokes were patients with stenosis 50% in an intracranial or extracranial vessel referable to the infarct without other cause of stroke. Cardioembolic stokes included patients with atrial fibrillation, acute myocardial infarction, valvular heart disease, or marked ventricular hypokinesis without other cause of stroke. Patients with atrial myxoma or endocarditis were excluded. Lacunar strokes had a lacunar syndrome with a corresponding infarct 15 mm in largest diameter in a region of the penetrating arteries without other cause of stroke. Cryptogenic strokes were patients with no determined etiology despite extensive evaluation or patients with 2 potential causes of stroke so that a final diagnosis was not possible. Strokes with incomplete evaluation were excluded from study. Cryptogenic strokes were divided based on infarct location into 2 groups, SDI and non-sdi (Figure 1). Infarct location was identified by restricted diffusion on MRI or hypodensity on CT. Subjects without imaging evidence of infarction were excluded from study. Cryptogenic SDI had strokes in the regions of the penetrating arteries with infarcts 15 mm in diameter and/or 2 potential causes of stroke. Regions of the penetrating arteries included the basal ganglia, internal capsule, thalamus, corona radiata, and pons. Cryptogenic non-sdis were strokes not in the regions of the penetrating arteries (mainly cortical), in which lacunar stroke would not be considered a cause of stroke. Sample Processing Blood was collected by venipuncture into PAXgene tubes (Pre- AnalytiX). Samples were stored frozen and then processed at the same time to minimize technical variation. Total RNA was isolated according to protocol (PAXgene blood RNA kit; Pre-AnalytiX) and analyzed for quality using Agilent 2100 Bioanalyzer and quantity by Nano-drop. Reverse transcription, amplification, and sample labeling were carried out using Nugen s Ovation Whole Blood reagents (Nugen Technologies, San Carlos, CA). Each RNA sample was hybridized to Affymetrix Genome U133 Plus 2 GeneChips and scanned according to protocol (Affymetrix, Santa Clara, CA). Raw expression values were preprocessed using robust multichip averaging, mean-centering standardization, and log 2 transformation for prediction analyses (Partek Genomics Suite 6.4; Partek Inc, St Louis, MO). Gene Profiles The profiles used to predict cause in cryptogenic stroke have been described previously. A 41-gene list was identified to distinguish patients with lacunar stroke from nonlacunar stroke 5 (online-only Data Supplement Table I). In addition, a 40-gene list was identified to distinguish patients with cardioembolic stroke from patients with arterial stroke 4 (Figure 1; online-only Data Supplement Table II). These gene profiles were derived from patients with known cardioembolic, arterial, and lacunar causes of stroke. Prediction of Cryptogenic Stroke Prediction analyses were performed using linear discriminant analysis (Partek Genomics Suite 6.4) and nearest shrunken centroid (Prediction Analysis of Microarrays) algorithms and principal components analysis (Partek Genomics Suite 6.4; Figure 2). 7 Patients with known cause of stroke were used to develop prediction models to distinguish cardioembolic from arterial causes of stroke 4 and to distinguish lacunar from nonlacunar causes of stroke. 5 These models were applied to groups of patients with cryptogenic stroke to predict the cause of stroke (Figure 1). The prediction models assign a probability of belonging to a type of stroke based on the pattern of gene expression. For example, cryptogenic strokes with a pattern of gene expression similar to patients with known cardioembolic stroke are predicted to be cardioembolic stroke. This prediction is performed to determine which cryptogenic strokes are most likely cardioembolic, arterial, or lacunar. Prediction of cryptogenic strokes was performed using gene expression in conjunction with infarct location. Cryptogenic SDIs in regions of the penetrating arteries were first predicted to be of either lacunar or nonlacunar etiology using the 41-gene profile (Figure 1; online-only Data (Supplement Table I). Cryptogenic SDIs of predicted nonlacunar etiology were then predicted to be of cardioembolic or arterial etiology using the 40-gene profile. Cryptogenic non-sdis (mostly cortical infarcts) were predicted to be of cardioembolic or arterial etiology using the 40-gene profile (online-only Data Supplement Table II). The 41-gene profile was not used to predict this group because lacunar stroke is not a consideration in patients with non-sdi. A predicted diagnosis of stroke cause required an average predicted probability of 75%. Subjects not meeting these criteria remained of unclear cause. Statistical Analyses Differences in demographic and clinical data between predicted stroke groups were analyzed using 2 or Fisher exact test, Kruskal-Wallis, or analysis of variance as appropriate (Stata 10.1, College Station, TX). Data are presented as mean SD for continuous variables and median with interquartile range for ordinal variables.

3 2038 Stroke August 2012 Figure 2. Principal components analysis (PCA) of cryptogenic strokes using the genes predictive of stroke cause. A, PCA of non-sdi cryptogenic strokes predicted to be arterial or cardioembolic stroke using the 40-gene profile. B, PCA of SDI cryptogenic strokes predicted to be lacunar or nonlacunar stroke using the 41-gene profile. C, PCA of the cryptogenic SDI predicted to be nonlacunar stroke in B, predicted to be arterial or cardioembolic stroke using the 40-gene profile. SDI indicates small deep infarct. Results Cryptogenic Strokes The demographic and clinical features of the 131 patients with cryptogenic stroke are summarized in Table 1. The average age was 63.9 years (SD 14.8) and 54.2% were male. Cryptogenic strokes were of diverse race and ethnicity with 74% white, 16% black, 6.1% Hispanic, and 3.9% of other race. Hypertension was present in 62.6%, hyperlipidemia in 25.2%, and diabetes in 18.3%. 21.4% had prior stroke or transient ischemic attack, 15.3% had prior myocardial infarction, and 3.1% had atrial fibrillation. The median National Institutes of Health Stroke Scale on admission was 10.6 (interquartile range, ). There were 32 (24.4%) SDI and 99 (75.6%) non-sdi. The demographics of the patients with cryptogenic stroke were similar to strokes of known etiology used to derive the gene expression profiles. The Table 1. Characteristics of the 131 Cryptogenic Stroke Subjects Studied Characteristic Value Age, y (SD) 63.9 (14.8) Male, no. (%) 71 (54.2%) Hypertension, no. (%) 82 (62.6%) Systolic BP, mm Hg (SD) (36.0) Diastolic BP, mm Hg (SD) 86.8 (18.7) Diabetes, no. (%) 24 (18.3%) Body mass index, kg/m 2 (SD) 28.7 (4.5) Hyperlipidemia, no. (%) 33 (25.2%) Current smoking, no. (%) 44 (33.6%) Atrial fibrillation, no. (%) 4 (3.1%) Prior myocardial infarction, no. (%) 20 (15.3%) Congestive heart failure, no. (%) 6 (4.6%) Prior stroke or TIA, no. (%) 28 (21.4%) NIHSS on admission (IQR) 10.6 (6 16) BP indicates blood pressure; TIA, transient ischemic attack; NIHSS, National Institutes of Health Stroke Scale; IQR, interquartile range. average age for strokes of known etiology was 67.7 years (SD 10.4), 59.1% were male, 73.2% had hypertension, 31.5% had hyperlipidemia, and 30.2% had diabetes (online-only Data Supplement Table III). Cryptogenic Stroke Predicted by Gene Expression and Infarct Location Of the 32 SDI cryptogenic strokes, 11 (34.4%) were predicted to be cardioembolic, 4 (12.5%) to be arterial, 15 (46.9%) to be lacunar, and 2 (6.3%) remained of unclear etiology. Of the 99 non-sdi cryptogenic strokes, 65 (65.7%) were predicted to be cardioembolic, 20 (20.2%) to be arterial, and 14 (14.1%) remained of unclear etiology. Thus, when combined, the 131 cryptogenic strokes resulted in 76 (58.0%) subjects predicted to be cardioembolic, 24 (18.3%) to be arterial, and 15 (11.5%) to be lacunar (Figure 1). There remained 16 (12.2%) subjects in which the diagnostic probability was insufficient to assign a predicted class. Separation of cryptogenic stroke into predicted causes by gene expression profiles is shown by principal components analysis in Figure 2 (Partek Genomics Suite 6.4). 7 The characteristics of cryptogenic strokes divided by predicted etiology is shown in Table 2. Groups were similar in gender, hypertension, diabetes, and hyperlipidemia. Cryptogenic strokes of predicted cardioembolic etiology had more prior myocardial infarction and higher CHA 2 DS 2 -VASc scores compared with cryptogenic strokes of predicted arterial etiology. Cryptogenic strokes of predicted lacunar etiology had higher systolic and diastolic blood pressures and a lower National Institutes of Health Stroke Scale compared with cryptogenic strokes predicted to be arterial or cardioembolic. Cryptogenic strokes that remained of unclear etiology had less history of stroke or transient ischemic attack. Discussion We describe the use of RNA expression profiles in blood in conjunction with infarct location to identify probable cardioembolic, arterial, and lacunar causes of cryptogenic stroke. The predicted causes of cryptogenic stroke require further

4 Jickling et al Cryptogenic Stroke Prediction 2039 Table 2. Characteristics of Cryptogenic Strokes Divided by Their Predicted Etiology Based on Gene Expression Profiles and Infarct Location Cardioembolic (n 76) Arterial (n 24) Lacunar (n 15) Unclear (n 16) P Value Age, y (SD) 65.2 (16.5) 61.1 (11.5) 62.9 (13.7) 61.1 (11.5) 0.05 Male, no. (%) 35 (46.1%) 15 (62.5%) 9 (60.0%) 12 (75.0%) 0.13 Hypertension, no. (%) 46 (60.6%) 17 (70.8%) 12 (80.0%) 7 (43.8%) 0.1 Systolic BP, mm Hg (SD) (37.9) (38.1) (37.3) (17.6) 0.05 Diastolic BP, mm Hg (SD) 85.5 (16.9) 81.0 (21.2) 97.9 (21.3) 90.1 (17.6) 0.05 Diabetes, no. (%) 12 (15.8%) 6 (25.0%) 5 (33.3%) 1 (6.3%) 0.15 Body mass index, kg/m 2 (SD) 28.5 (3.9) 29.0 (2.7) 28.4 (5.1) 31.6 (9.3) 0.61 Hyperlipidemia, no. (%) 19 (25.0%) 4 (16.7%) 6 (40%) 4 (25.0%) 0.35 Current smoking, no. (%) 21 (27.6%) 10 (41.7%) 6 (40.0%) 7 (43.8%) 0.58 Atrial fibrillation, no. (%) 3 (3.9%) 0 1 (6.7%) Prior myocardial infarction, no. (%) 17 (22.4%) (18.8%) 0.02 Congestive heart failure, no. (%) 6 (7.9%) CHA 2 DS 2 -VASc (IQR) 3.1 (2 4) 2.0 (1 2.7) 2.8 ( ) 1.6 (0 3) 0.05 Prior stroke or TIA, no. (%) 21 (27.6%) 3 (12.5%) 4 (26.7%) NIHSS on admission (IQR) 9.6 (6 11.5) 12.1 (6 19) 3.3 (2 3.5) 16.6 (12 23) 0.05 Cryptogenic strokes were predicted to be of cardioembolic, arterial, or lacunar etiology. Strokes of unclear predicted cause were subjects in which the diagnostic probability was insufficient to assign a predicted class. BP indicates blood pressure; IQR, interquartile range; TIA, transient ischemic attack; NIHSS, National Institutes of Health Stroke Scale. study to determine whether relevant epidemiological or therapeutic differences exist for each group. The described approach to determine a probable cause of cryptogenic stroke represents an important step to better classify a patient group that accounts for as many as one third of ischemic strokes. Cardioembolic stroke was the predicted cause in 58% of cryptogenic strokes studied. This is consistent with previous studies indicating cardioembolism is a contributor to cryptogenic stroke Indeed, paroxysmal atrial fibrillation not detected on initial investigations can later be identified in 10% to 25% of cryptogenic strokes with prolonged cardiac monitoring. 8,11 In our study, a higher CHA 2 DS 2 -VASc score in predicted cardioembolic subjects may support the presence of undetected paroxysmal atrial fibrillation. This requires further evaluation by prolonged cardiac recording. Patent foramen ovale may also contribute to cryptogenic stroke, although this remains controversial The prevalence of patent foramen ovale is increased in cryptogenic strokes compared with control subjects, 15,16 and trials of patent foramen ovale closure in cryptogenic stroke are ongoing. 17 Whether cryptogenic strokes of predicted cardioembolic etiology may derive greater benefit from patent foramen ovale closure may be of interest for future evaluation. Prior myocardial infarction was also identified to be more common in cryptogenic strokes of predicted cardioembolic etiology. Although the significance of this remains unclear, a prior myocardial infarction in cryptogenic stroke may be an indicator of underlying cardiac disease associated with stroke. Arterial disease was a predicted cause of cryptogenic stroke in 18.3% of subjects. Prior studies also suggest that arterial disease likely contributes to cryptogenic stroke, including arterial stenosis 50%, plaque ulceration, intracranial atherosclerosis, and aortic plaque. 10,18,19 Indeed, arterial stenosis 50% and the presence of arterial plaque are both considered in the Causative Classification for Ischemic Stroke and the Atherosclerosis, Small Vessel Disease, Cardiac Source, Other Cause (A-S-C-O) classification systems as features that increase the probability of arterial stroke. 20,21 Ulcerated plaques missed by current investigations may also account for some of the predicted arterial cryptogenic strokes, particularly given that two thirds of ulcerated carotid arteries occur with stenoses of 0% to 49%. 22 Further evaluation to determine whether such features are more common in cryptogenic strokes of predicted arterial etiology is required. Lacunar stroke was a predicted cause of cryptogenic stroke in 11.5% of subjects. Lacunar stroke differs from arterial and cardioembolic stroke in that the source of stroke is inferred by infarct size and location rather than directly identified. Thus, lacunar stroke is only a consideration when an infarct is located in the region of the penetrating arteries. These small deep infarcts are cryptogenic when an arterial and/or cardioembolic source of stroke is present or when the infarct is 15 mm in diameter. The prediction of cause by gene expression suggests that some small deep infarcts 15 mm in size, or with a coincidental arterial or cardiac source of stroke, are lacunar strokes. Evaluating these predicted causes will require follow-up. Subjects of predicted lacunar etiology would be expected to be more likely to have recurrent lacunar infarcts, whereas SDIs of predicted arterial or cardioembolic etiology would be expected to have recurrent infarcts in regions not supplied by deep penetrating arteries. In this study, 76% of cryptogenic strokes were predicted to be of either arterial or cardioembolic etiology. This is consistent with previous epidemiological studies indicating cryptogenic strokes have a long-term prognosis similar to that of arterial and cardioembolic stroke. The 2-year survival rate

5 2040 Stroke August 2012 of cryptogenic stroke is 61%, which is closer to the survival rate of cardioembolic stroke at 55% and arterial stroke at 58% compared with lacunar stroke at 85%. 3 Additionally, cryptogenic strokes are more likely to have recurrent arterial or cardioembolic strokes. 23 Finally, outcome in cryptogenic stroke is closer to that of cardioembolic and arterial stroke than lacunar stroke. At 90 days, 35.8% of cryptogenic strokes have a modified Rankin Scale score 3, 24 compared with 56.8% of cardioembolic strokes, 32.4% of arterial strokes, and only 4.2% of lacunar strokes. 24 The Causative Classification for Ischemic Stroke and A-S-C-O classification systems demonstrate how additional clinical and imaging features can be used to further characterize stroke subtype. Likewise, genetic data may also provide additional information to characterize stroke subtype. We demonstrate how RNA expression profiles can predict a likely cause in cryptogenic stroke. A gene expression profile could be developed into a clinical assay similar to those developed for breast cancer and coronary artery disease. 25,26 The RNA results would provide an indication of whether a patient is likely of arterial, cardioembolic, or lacunar etiology, which could be interpreted along with other diagnostic information to determine stroke cause. This discovery type study has limitations. Although echocardiography was performed in all subjects, transesophageal echocardiography was not. Contrast-enhanced MR angiography was rarely performed in subjects, although MR angiography or CT angiography was performed on nearly all subjects. Evaluation for coagulopathy was performed in patients 50 years of age or in cases in which physicians deemed it appropriate. Studies with long-term follow-up are needed to document recurrent stroke with potentially identifiable cause and to monitor for arterial, cardioembolic, or small-vessel disease. Additionally, the relationship between gene expression prediction of cryptogenic stroke and other features associated with stroke cause require further study, including imaging criteria and features specified in the Causative Classification for Ischemic Stroke and A-S-C-O stroke classification systems. The profiles used to predict the cause of cryptogenic stroke were derived from a relatively small sample size. Although vascular risk factors, sex, race, and ethnicity were not found to be significantly different between groups, further development and evaluation of RNA predictors of stroke cause in larger cohorts is required to ensure adequate representation of a stroke population. Conclusions The high rates of recurrent stroke and mortality in cryptogenic stroke support the need to develop methods to diagnose this large group of patients. Identifying a cause of stroke is critical to implement prevention therapy and reduce stroke disability and mortality. We demonstrate a probable cause of cryptogenic stroke can be predicted based on the gene expression profile in conjunction with a measure of infarct location. Further study of predicted groups is required to determine whether relevant clinical, imaging, or therapeutic differences exist for each group. Acknowledgments We thank the investigators of the Specialized Programs of Translational Research in Acute Stroke (SPOTRIAS) Stroke Network involved in the CLEAR trial for supplying blood samples for analysis. We appreciate the support of the Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, the Genomics and Expression Resource at the MIND Institute, and the University of California at Davis Department of Neurology. Sources of Funding This study was supported by the National Institutes of Health (NS056302, Dr Sharp) and the American Heart Association (Dr Sharp). Dr Jickling receives support from the Canadian Institutes of Health Research and the American Heart Association. None. Disclosures References 1. Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, et al. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org in Acute Stroke Treatment. Stroke. 1993;24: Ionita CC, Xavier AR, Kirmani JF, Dash S, Divani AA, Qureshi AI. What proportion of stroke is not explained by classic risk factors? Prev Cardiol. 2005;8: Kolominsky-Rabas PL, Weber M, Gefeller O, Neundoerfer B, Heuschmann PU. Epidemiology of ischemic stroke subtypes according to toast criteria: incidence, recurrence, and long-term survival in ischemic stroke subtypes: a population-based study. Stroke. 2001;32: Jickling GC, Xu H, Stamova B, Ander BP, Zhan X, Tian Y, et al. Signatures of cardioembolic and large-vessel ischemic stroke. 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Study design of the CLOSURE I trial: a prospective, multicenter, randomized, controlled trial to evaluate the safety and efficacy of the Starflex

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