Interobserver agreement in the trial of org 10172 in acute stroke treatment classification of stroke based on retrospective medical record review

TOAST stroke subtype classification in clinical practice: implications for the Get With The Guidelines-Stroke nationwide registry

Introduction

The TOAST (Trial of ORG 10172 in Acute Stroke Treatment) is the most commonly used ischemic stroke subtype classification system worldwide and a required field in the US National Get With The Guidelines-Stroke (GWTG-Stroke) registry. However, stroke diagnostics have advanced substantially since the TOAST classification was designed 30 years ago, potentially making it difficult to apply reliably.

Methods

In this prospective diagnostic accuracy study, we analyzed consecutive ischemic stroke patients admitted to a Comprehensive Stroke Center between July-October 2021. Clinical practice TOAST classification diagnoses rendered by the stroke team in the electronic medical record (EMR) at discharge were retrieved from GWTG-Stroke registry and compared to a reference ("gold") standard diagnosis derived from agreement between two expert raters after review of the EMR and patient imaging.

Results

Among 49 patients; age was 72.3 years (±12.1), 53% female, and presenting NIHSS median 3 (IQR 1-11). Work-up included: brain imaging in 100%; cardiac rhythm assessment in 100%; cervical/cerebral vessel imaging in 98%; TTE ± TEE in 92%; and TCD emboli evaluation in 51%. Reference standard diagnoses were: LAA-6%, SVD-14%, CE-39%, OTH-10%, UND-M (more than one cause)-20%, and UND-C (cryptogenic)-10%. GWTG-Stroke TOAST diagnoses agreed with reference standard diagnoses in 30/49 (61%). Among the 6 subtype diagnoses, specificity was generally high (84.8%-97.7%), but sensitivity suboptimal for LAA (33%), OTH (60%), UND-M (10%), and UND-C (20%). Positive predictive value was suboptimal for 5 of the 6 subtypes: LAA (13%), SVD (58%), OTH (75%), UND-M (50%), and UND-C (50%).

Discussion

Clinical practice TOAST classification subtype diagnoses entered into the GWTG-Stroke registry were accurate in only 61% of patients, a performance rate that, if similarly present at other centers, would hamper the ability of the national registry to provide dependable insights into subtype-related care. Development of an updated ischemic stroke subtype classification system, with algorithmic logic embedded in electronic medical records, is desirable.

Hospital-Level Variability in Reporting of Ischemic Stroke Subtypes and Supporting Diagnostic Evaluation in GWTG-Stroke Registry

BACKGROUND

Secondary prevention of ischemic stroke (IS) requires adequate diagnostic evaluation to identify the likely etiologic subtype. We describe hospital-level variability in diagnostic testing and IS subtyping in a large nationwide registry.

METHODS AND RESULTS

We used the GWTG-Stroke (Get With The Guidelines-Stroke) registry to identify patients hospitalized with a diagnosis of acute IS at 1906 hospitals between January 1, 2016, and September 30, 2017. We compared the documentation rates and presence of risk factors, diagnostic testing, achievement/quality measures, and outcomes between patients with and without reported IS subtype. Recording of diagnostic evaluation was optional in all IS subtypes except cryptogenic, where it was required. Of 607 563 patients with IS, etiologic IS subtype was documented in 57.4% and missing in 42.6%. Both the rate of missing stroke pathogenesis and the proportion of cryptogenic strokes were highly variable across hospitals. Patients missing stroke pathogenesis less frequently had documentation of risk factors, evidence-based interventions, or discharge to home. The reported rates of major diagnostic testing, including echocardiography, carotid and intracranial vascular imaging, and short-term cardiac monitoring were <50% in patients with documented IS pathogenesis, although these variables were missing in >40% of patients. Long-term cardiac rhythm monitoring was rarely reported, even in cryptogenic stroke.

CONCLUSIONS

Reporting of IS etiologic subtype and supporting diagnostic testing was low overall, with high rates of missing optional data. Improvement in the capture of these data elements is needed to identify opportunities for quality improvement in the diagnostic evaluation and secondary prevention of stroke.

Endovascular thrombectomy in young patients with stroke

BACKGROUND

Endovascular treatment (ET) is standard of care in patients with acute ischemic stroke due to large vessel occlusion, but data on ET in young patients remain limited.

AIM

We aim to compare outcomes for young stroke patients undergoing ET in a matched cohort.

METHODS

We analyzed patients from an observational multicenter cohort with acute ischemic stroke and ET, the German Stroke Registry-Endovascular Treatment trial. Baseline characteristics, procedural parameters, and functional outcome at 90 days were compared between young (<50 years) and older (⩾50 years) patients with and without nearest-neighbor 1:1 propensity score matching.

RESULTS

Out of 6628 acute ischemic stroke patients treated with ET, 363 (5.5%) were young. Young patients differed with regard to prognostic outcome characteristics. Specifically, National Institutes of Health Stroke Scale (NIHSS) at admission was lower (median 13, interquartile range (IQR) 8-17 vs. 15, IQR 9-19, p < 0.001), and prestroke dependence was less frequent (2.9% vs. 12.2%, p < 0.001) than in older patients. Compared to a matched cohort of older patients, ET was faster (time from groin puncture to flow restoration, 35 vs. 45 min, p < 0.001) and intracranial hemorrhage was less frequent in young patients (10.0% vs. 25.9%, p < 0.001). Good functional outcome (modified Rankin Scale (mRS) 0-2) at 3 months was achieved more frequently in young patients (71.6% vs. 44.1%, p < 0.001), and overall mortality was lower (6.7% vs. 25.4%, p < 0.001). Among previously employed young patients (n = 177), 37.9% returned to work at 3-month follow-up, while 74.1% of the remaining patients were still undergoing rehabilitation.

CONCLUSION

Young stroke patients undergoing ET have better outcomes compared to older patients, even when matched for prestroke condition, comorbidities, and stroke severity. Hence, more liberal guidelines to perform ET for younger patients may have to be established by future studies.

Genetic Architecture of Stroke of Undetermined Source: Overlap with Known Stroke Etiologies and Associations with Modifiable Risk Factors

OBJECTIVE

Ischemic stroke etiology remains undetermined in 30% of cases. We explored the genetic architecture of stroke classified as undetermined to test if mechanisms and risk factors underlying large-artery atherosclerotic (LAAS), cardioembolic (CES), and small-vessel stroke (SVS) contribute to its pathogenesis.

METHODS

We analyzed genome-wide data from 16,851 ischemic stroke cases and 32,473 controls. Using polygenic risk scores for LAAS, CES, and SVS, we assessed the genetic overlap with stroke of undetermined source and used pairwise genomewide association study (GWAS-PW) to search for shared loci. We then applied Mendelian randomization (MR) to identify potentially causal risk factors of stroke of undetermined source.

RESULTS

Genetic risk for LAS, CES, and SVS was associated with stroke of undetermined source pointing to overlap in their genetic architecture. Pairwise analyses revealed 19 shared loci with LAAS, 2 with CES, and 5 with SVS that have been implicated in atherosclerosis-related phenotypes. Genetic liability to both carotid atherosclerosis and atrial fibrillation was associated with stroke of undetermined source, but the association with atrial fibrillation was attenuated after excluding cases with incomplete diagnostic workup. MR analyses showed effects of genetically determinants of blood pressure, diabetes, waist-to-hip ratio, inflammatory pathways (IL-6 signaling, MCP-1/CCL2 levels), and factor XI levels on stroke of undetermined source.

INTERPRETATION

Stroke of undetermined source shares genetic and vascular risk factors with other stroke subtypes, especially LAAS, thus highlighting the diagnostic limitations of current subtyping approaches. The potentially causal associations with carotid atherosclerosis and atherosclerotic risk factors might have implications for prevention strategies targeting these mechanisms. ANN NEUROL 2022;91:640-651.

Causative Classification of Ischemic Stroke by the Machine Learning Algorithm Random Forests

Background

Prognosis, recurrence rate, and secondary prevention strategies differ by different etiologies in acute ischemic stroke. However, identifying its cause is challenging.

Objective

This study aimed to develop a model to identify the cause of stroke using machine learning (ML) methods and test its accuracy.

Methods

We retrospectively reviewed the data of patients who had determined etiology defined by the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) from CASE-II (NCT04487340) to train and evaluate six ML models, namely, Random Forests (RF), Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), K-Nearest Neighbor (KNN), Ada Boosting, Gradient Boosting Machine (GBM), for the detection of cardioembolism (CE), large-artery atherosclerosis (LAA), and small-artery occlusion (SAO). Between October 2016 and April 2020, patients were enrolled consecutively for algorithm development (phase one). Between June 2020 and December 2020, patients were enrolled consecutively in a test set for algorithm test (phase two). Area under the curve (AUC), precision, recall, accuracy, and F1 score were calculated for the prediction model.

Results

Finally, a total of 18,209 patients were enrolled in phase one, including 13,590 patients (i.e., 6,089 CE, 4,539 LAA, and 2,962 SAO) in the model, and a total of 3,688 patients were enrolled in phase two, including 3,070 patients (i.e., 1,103 CE, 1,269 LAA, and 698 SAO) in the model. Among the six models, the best models were RF, XGBoost, and GBM, and we chose the RF model as our final model. Based on the test set, the AUC values of the RF model to predict CE, LAA, and SAO were 0.981 (95%CI, 0.978-0.986), 0.919 (95%CI, 0.911-0.928), and 0.918 (95%CI, 0.908-0.927), respectively. The most important items to identify CE, LAA, and SAO were atrial fibrillation and degree of stenosis of intracranial arteries.

Conclusion

The proposed RF model could be a useful diagnostic tool to help neurologists categorize etiologies of stroke.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT01274117].

Promising Biomarker Candidates for Cardioembolic Stroke Etiology. A Brief Narrative Review and Current Opinion

Determining the cause of stroke is considered one of the main objectives in evaluating a stroke patient in clinical practice. However, ischemic stroke is a heterogeneous disorder and numerous underlying disorders are implicated in its pathogenesis. Although progress has been made in identifying individual stroke etiology, in many cases underlying mechanisms still remain elusive. Since secondary prevention strategies are tailored toward individual stroke mechanisms, patients whose stroke etiology is unknown may not receive optimal preventive treatment. Cardioembolic stroke is commonly defined as cerebral vessel occlusion by distant embolization arising from thrombus formation in the heart. It accounts for the main proportion of ischemic strokes, and its share to stroke etiology is likely to rise even further in future decades. However, it can be challenging to distinguish cardioembolism from other possible etiologies. As personalized medicine advances, stroke researchers' focus is increasingly drawn to etiology-associated biomarkers. They can provide deeper insight regarding specific stroke mechanisms and can help to unravel previously undetected pathologies. Furthermore, etiology-associated biomarkers could play an important role in guiding future stroke prevention strategies. To achieve this, broad validation of promising candidate biomarkers as well as their implementation in well-designed randomized clinical trials is necessary. This review focuses on the most-promising candidates for diagnosis of cardioembolic stroke. It discusses existing evidence for possible clinical applications of these biomarkers, addresses current challenges, and outlines future perspectives.

Effect of Intensive Versus Standard Blood Pressure Control on Stroke Subtypes

[Figure: see text].

Associating cryptogenic ischemic stroke in the young with cardiovascular risk factor phenotypes

Acute Ischemic Stroke (AIS) in the young is increasing in prevalence and the largest subtype within this cohort is cryptogenic. To curb this trend, new ways of defining cryptogenic stroke and associated risk factors are needed. We aimed to gain insights into the presence or absence of cardiovascular risk factors in cases of cryptogenic stroke. We conducted a retrospective cohort study of patients aged 18-49 who presented to an urban tertiary care center with AIS. We manually collected predefined demographic, clinical, laboratory and radiological variables. Clinical risk phenotypes were determined using these variables through multivariate analysis of patients with the small and large vessel disease subtypes (vascular phenotype) and cardioembolic subtype (cardiac phenotype). The resultant phenotype models were applied to cases deemed cryptogenic. Within the 449 patients who met criteria, patients with small and large vessel disease (vascular phenotype) had higher rates of hypertension, intracranial atherosclerosis, and diabetes mellitus, and higher admission glucose, HbA1c, admission blood pressure, and cholesterol compared to the patients with cardioembolic AIS. The cardioembolic subgroup (cardiac phenotype) had significantly higher rates of congestive heart failure (CHF), rheumatic heart disease, atrial fibrillation, clotting disorders, left ventricular hypertrophy, larger left atrial sizes, lower ejection fractions, and higher B-type natriuretic peptide and troponin levels. Adjusted multivariate analysis produced six variables independently associated with the vascular phenotype (age, male sex, hemoglobin A1c, ejection fraction (EF), low-density lipoprotein (LDL) cholesterol, and family history of AIS) and five independently associated with the cardiac phenotype (age, female sex, decreased EF, CHF, and absence of intracranial atherosclerosis). Applying these models to cryptogenic stroke cases yielded that 51.5% fit the vascular phenotype and 3.1% fit the cardiac phenotype. In our cohort, half of young patients with cryptogenic stroke fit the risk factor phenotype of small and large vessel strokes.

Association of Atrial Fibrillation Without Cardiovascular Comorbidities and Stroke Risk: From the REGARDS Study

Background Atrial fibrillation (AF) is associated with a 5-fold increased stroke risk. While most patients with AF warrant anticoagulation, optimal treatment remains uncertain for patients with AF without cardiovascular comorbidities because the risk of stroke in this population has not been well-characterized. Methods and Results Participants (N=28 253; 55% women, mean age 64.6±9.4 years), from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study (2003-present) were classified into 1 of 4 groups based on the presence or absence of AF and the presence or absence of cardiovascular comorbidities. Cox proportional hazards analysis was used to compare the risk of stroke between groups. During 244 560 person-years of follow-up (median 8.7 years), 1206 strokes occurred. Compared with patients with neither AF nor cardiovascular comorbidities, we did not find an increased stroke risk (hazard ratio [HR], 1.23; 95% CI, 0.62-2.18 [P=0.511]) among participants with AF alone. Participants without AF but with cardiovascular comorbidities had both an elevated stroke risk (HR, 1.77; 95% CI, 1.48-2.18 [P<0.0001]) and an increased risk of cardioembolic stroke (HR, 2.34; 95% CI, 1.48-3.90 [P=0.0002]). Conclusions In this large cohort of participants with AF without cardiovascular comorbidities, we found that AF itself, without cardiovascular comorbidities, did not confer increased risk of stroke. Cardiovascular comorbidities, however, were associated with an increased risk of both stroke of any type and cardioembolic stroke, even in the absence of AF.

Stroke Etiology and Thrombus Computed Tomography Characteristics in Patients With Acute Ischemic Stroke

Background and Purpose—

If a relationship between stroke etiology and thrombus computed tomography characteristics exists, assessing these characteristics in clinical practice could serve as a useful additional diagnostic tool for the identification of stroke subtype. Our purpose was to study the association of stroke etiology and thrombus computed tomography characteristics in patients with acute ischemic stroke due to a large vessel occlusion.

Methods—

For 1429 consecutive patients enrolled in the MR CLEAN Registry, we determined stroke cause as defined by the TOAST (Trial of ORG 10172 in Acute Stroke Treatment) criteria. The association of stroke etiology with the hyperdense artery sign, clot burden score, and thrombus location was estimated with univariable and multivariable binary and ordinal logistic regression. Additionally, for 367 patients with available thin-section imaging, we assessed the association of stroke etiology with absolute and relative thrombus attenuation, distance from internal carotid artery-terminus to thrombus, thrombus length, and thrombus attenuation increase with univariable and multivariable linear regression.

Results—

Compared with cardioembolic strokes, noncardioembolic strokes were associated with presence of hyperdense artery sign (odds ratio, 2.2 [95% CI, 1.6–3.0]), lower clot burden score (common odds ratio, 0.4 [95% CI, 0.3–0.6]), shift towards a more proximal thrombus location (common odds ratio, 0.2 [95% CI, 0.2–0.3]), higher absolute thrombus attenuation (β, 3.6 [95% CI, 0.9–6.4]), decrease in distance from the ICA-terminus (β, −5.7 [95% CI, −8.3 to −3.0]), and longer thrombi (β, 8.6 [95% CI, 6.5−10.7]), based on univariable analysis. Thrombus characteristics of strokes with undetermined cause were similar to those of cardioembolic strokes.

Conclusions—

Thrombus computed tomography characteristics of cardioembolic stroke are distinct from those of noncardioembolic stroke. Additionally, our study supports the general hypothesis that many cryptogenic strokes have a cardioembolic cause. Further research should focus on the use of thrombus computed tomography characteristics as a diagnostic tool for stroke cause in clinical practice.

Documentation of breakthrough pain in narrative clinical records of children with life-limiting conditions: Feasibility of a retrospective review

This study explored the feasibility of generating reliable information on the frequency, nature and management of breakthrough pain (BTP) in children with life-limiting conditions and life-threatening illnesses (LTIs) from narrative clinical records. In the absence of standardized ways for documenting BTP, we conducted a consensus exercise to develop a glossary of terms that could denote BTP in the records. Thirteen clinicians who contributed to the records reached consensus on 45 terms which could denote BTP, while emphasizing the importance of contextual information. The results of this approach together with guidance for improving the reliability of retrospective reviews informed a data extraction instrument. A pilot test of this instrument showed poor agreement between raters. Given the challenges encountered, we do not recommend a retrospective review of BTP using narrative records. This study highlighted challenges of data extraction for complex symptoms such as BTP from narrative clinical records. For both clinical and research purposes, the recording of complex symptoms such as BTP would benefit from clear criteria for applying definitions, a more structured format and the inclusion of validated assessment tools. This study also showed the value of consensus exercises in improving understanding and interpretation of clinical notes within a service.

Cryptogenic stroke: Contemporary trends, treatments, and outcomes in the United States

Background

Nationwide data on patients with cryptogenic stroke (CS) are lacking. We evaluated patient and hospital characteristics, in-hospital treatments, and discharge outcomes among patients with CS compared with other subtypes in the Get With The Guidelines (GWTG)-Stroke registry.

Methods

We identified patients with ischemic stroke (IS) admitted to GWTG-Stroke participating hospitals between January 1, 2016, and September 30, 2017, with documented National Institutes of Health Stroke Scale (NIHSS) scale and stroke etiology (cardioembolic [CE], large artery atherosclerosis [LAA], small vessel occlusion [SVO], other determined etiology [OTH], or CS). Using multivariable logistic regression, we compared hospital treatments and discharge outcomes by subtype, adjusted for patient and hospital characteristics.

Results

Among 316,623 patients from 1,687 hospitals, there were 63,301 (20.0%) patients with CS. In multivariable analysis, patients with CS received IV thrombolysis more often than other subtypes and had lower mortality than CE, LAA, and OTH but higher mortality than SVO. They were more likely to be discharged home than all other subtypes and be independent at discharge than LAA, OTH, or SVO.

Conclusions

In a large contemporary nationwide registry, CS accounted for 20% of ISs among patients with a documented stroke etiology. Patients with CS had a distinct profile of treatments and outcomes relative to other subtypes. Improved subtype documentation and further research into CS are warranted to improve care and outcomes for patients with stroke.

Stroke aetiological classification reliability and effect on trial sample size: systematic review, meta-analysis and statistical modelling

Background

Inter-observer variability in stroke aetiological classification may have an effect on trial power and estimation of treatment effect. We modelled the effect of misclassification on required sample size in a hypothetical cardioembolic (CE) stroke trial.

Methods

We performed a systematic review to quantify the reliability (inter-observer variability) of various stroke aetiological classification systems. We then modelled the effect of this misclassification in a hypothetical trial of anticoagulant in CE stroke contaminated by patients with non-cardioembolic (non-CE) stroke aetiology. Rates of misclassification were based on the summary reliability estimates from our systematic review. We randomly sampled data from previous acute trials in CE and non-CE participants, using the Virtual International Stroke Trials Archive. We used bootstrapping to model the effect of varying misclassification rates on sample size required to detect a between-group treatment effect across 5000 permutations. We described outcomes in terms of survival and stroke recurrence censored at 90 days.

Results

From 4655 titles, we found 14 articles describing three stroke classification systems. The inter-observer reliability of the classification systems varied from ‘fair’ to ‘very good’ and suggested misclassification rates of 5% and 20% for our modelling. The hypothetical trial, with 80% power and alpha 0.05, was able to show a difference in survival between anticoagulant and antiplatelet in CE with a sample size of 198 in both trial arms. Contamination of both arms with 5% misclassified participants inflated the required sample size to 237 and with 20% misclassification inflated the required sample size to 352, for equivalent trial power. For an outcome of stroke recurrence using the same data, base-case estimated sample size for 80% power and alpha 0.05 was n = 502 in each arm, increasing to 605 at 5% contamination and 973 at 20% contamination.

Conclusions

Stroke aetiological classification systems suffer from inter-observer variability, and the resulting misclassification may limit trial power.

Trial registration

Protocol available at reviewregistry540.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3222-x) contains supplementary material, which is available to authorized users.

Inter-rater Agreement for the Diagnosis of Stroke Versus Stroke Mimic

BACKGROUND AND PURPOSE

Patients who present emergently with acute neurological signs and symptoms represent unique diagnostic challenges for clinicians. We sought to characterize the reliability of physician diagnosis in differentiating aborted or imaging-negative acute ischemic stroke from stroke mimic.

METHODS

We constructed 10 case-vignettes of patients treated with thrombolysis with subsequent clinical improvement who lacked radiographic evidence of infarction. Using an online survey, we asked physicians to select a most likely final diagnosis after reading each case-vignette. Inter-rater agreement was evaluated using percent agreement and κ statistic for multiple raters with 95% confidence intervals reported.

RESULTS

Sixty-five physicians participated in the survey. Most participants were in practice for ≥5 years and over half were vascular neurologists. Physicians agreed on the most likely final diagnosis 71% of the time, κ of 0.21 (95% confidence interval, 0.06-0.54). Percent agreement was similar across participant practice locations, years of experience, subspecialty training, and personal experience with thrombolysis.

CONCLUSIONS

We found modest agreement among surveyed physicians in distinguishing ischemic stroke syndromes from stroke mimics in patients without radiographic evidence of infarction and clinical improvement after thrombolysis. Methods to improve diagnostic consensus after thrombolysis are needed to assure acute ischemic stroke patients and stroke mimics are treated safely and accurately.

Frequency of Ischemic Stroke Subtypes Based on Toast Classification at a Tertiary Care Center in Pakistan

BACKGROUND

The purpose of this study was to determine the frequency of ischemic stroke subtypes based on Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification at a tertiary care center in Pakistan.

MATERIALS AND METHODS

A cross-sectional study was conducted in Stroke Unit of Shifa International Hospital, Islamabad. We included 145 patients who presented to us from November 2015 to February 2016 with radiological confirmed neurological deficits consistent with ischemic stroke. The causes of ischemic stroke were classified according to TOAST criteria. Regression analysis and Chi-square test were used to compute P value.

RESULTS

Among the 145 patients diagnosed with ischemic stroke, there were 54.1% males and 45.9% females with a mean age of 65 ± 14 years. Nearly 62.7% patients had hypertension (HTN) as the most common risk factor, followed by 38.6% diabetes mellitus (DM), 27.5% heart failure, 19.3% valvular disease, 18.6% previous stroke, 16.4% smoking, 15.1% dyslipidemia, 13.7% ischemic heart disease, and 13.1% atrial fibrillation. HTN was significantly associated with large vessel disease (P = 0.028). DM was significantly associated with small vessel disease (P = 0.001). Smoking and atrial fibrillation both were associated with unknown etiology of stroke (P = 0.001 and P = 0.039, respectively). Most common etiology of stroke was cardioembolism (40%), and atrial fibrillation is found to be the most common cause of cardioembolic stroke with 30.6% incidence.

CONCLUSION

Our study concludes that cardioembolic stroke is the most common cause of acute ischemic stroke in our stroke unit. Atrial fibrillation is found to be the most common cause of cardioembolic stroke.

Polygenic Risk for Depression Increases Risk of Ischemic Stroke: From the Stroke Genetics Network Study

BACKGROUND AND PURPOSE

Although depression is a risk factor for stroke in large prospective studies, it is unknown whether these conditions have a shared genetic basis.

METHODS

We applied a polygenic risk score (PRS) for major depressive disorder derived from European ancestry analyses by the Psychiatric Genomics Consortium to a genome-wide association study of ischemic stroke in the Stroke Genetics Network of National Institute of Neurological Disorders and Stroke. Included in separate analyses were 12 577 stroke cases and 25 643 controls of European ancestry and 1353 cases and 2383 controls of African ancestry. We examined the association between depression PRS and ischemic stroke overall and with pathogenic subtypes using logistic regression analyses.

RESULTS

The depression PRS was associated with higher risk of ischemic stroke overall in both European (P=0.025) and African ancestry (P=0.011) samples from the Stroke Genetics Network. Ischemic stroke risk increased by 3.0% (odds ratio, 1.03; 95% confidence interval, 1.00-1.05) for every 1 SD increase in PRS for those of European ancestry and by 8% (odds ratio, 1.08; 95% confidence interval, 1.04-1.13) for those of African ancestry. Among stroke subtypes, elevated risk of small artery occlusion was observed in both European and African ancestry samples. Depression PRS was also associated with higher risk of cardioembolic stroke in European ancestry and large artery atherosclerosis in African ancestry persons.

CONCLUSIONS

Higher polygenic risk for major depressive disorder is associated with increased risk of ischemic stroke overall and with small artery occlusion. Additional associations with ischemic stroke subtypes differed by ancestry.

Role of Hyperintense Acute Reperfusion Marker for Classifying the Stroke Etiology

Purpose

The hyperintense acute reperfusion marker (HARM) is a delayed enhancement of the subarachnoid or subpial space observed on post-contrast fluid-attenuated inversion recovery (FLAIR) images and is associated with permeability changes to the blood–brain barrier in acute stroke. We investigated the relationship between HARM and stroke etiology based on the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification. In addition, we evaluated the relationship between HARM and stroke locations with respect to vascular territories and anatomic compartments.

Materials and methods

We recruited 264 consecutive patients (109 women; mean age 68.63 years) who were diagnosed with acute ischemic stroke and underwent brain magnetic resonance imaging (MRI) including post-contrast FLAIR and DWI within 7 days of symptom onset from May 2015 to March 2016 for this retrospective study. Post-contrast FLAIR images were obtained 5 min after gadolinium administration. The mean time interval between the onset of stroke symptoms and MRI acquisition in total included patients was 18 h and 7 min (median 12 h and 57 min, range 2–127 h). We analyzed the overall incidence and distribution patterns of HARM in acute ischemic stroke cases and compared the relative incidence and distribution patterns of HARM between the subgroups of stroke etiology based on conventional TOAST classification. We obtained odds ratio (OR) of HARM in different stroke locations based on vascular territories and anatomical compartments. This study was approved by our institutional review board.

Results

Among the 264 patients, 67 (25.38%) patients were HARM positive and 197 (74.62%) patients were HARM negative. There was significant difference in HARM incidence among the stroke subgroups (p < 0.001). Small vessel occlusion (SVO) was associated with the HARM-negative group (p < 0.001), while large artery atherosclerosis (LAA) and cardioembolism (CE) were associated with the HARM-positive group (p = 0.001). Also, regional pattern of HARM on the same vascular territory as the acute infarction was dominantly demonstrated regardless of stroke etiology. The OR for HARM from middle cerebral artery (MCA) infarction was 1.868 [95% confidence interval (CI): 1.025–3.401]. The OR for HARM from cortical infarction was 9.475 (95% CI: 4.754–18.883) compared to other anatomic compartments.

Conclusion

The presence of the HARM was significantly associated with embolic infarctions including LAA and CE. Conversely, SVO was exclusively associated with the absence of the HARM. Second, MCA and cortical infarction showed a more pronounced HARM compared to infarctions at other vascular territories and anatomic compartments. According to the results in the current study, we speculate that the presence of HARM on post-contrast FLAIR images was associated with specific stroke causes especially in embolic causes.

Assessment of the Predictive Validity of Etiologic Stroke Classification

Importance

The ability of present-day etiologic stroke classification systems to generate subtypes with discrete stroke characteristics is not known.

Objective

To test the hypothesis that etiologic stroke subtyping identifies different disease processes that can be recognized through their different clinical courses.

Design, Setting, and Participants

We performed a head-to-head evaluation of the ability of the Causative Classification of Stroke (CCS), Trial of Org 10172 in Acute Stroke Treatment (TOAST), and ASCO (A for atherosclerosis, S for small-vessel disease, C for cardiac source, and O for other cause) classification systems to generate etiologic subtypes with different clinical, imaging, and prognostic characteristics in 1816 patients with ischemic stroke. This study included 2 cohorts recruited at separate periods; the first cohort was recruited between April 2003 and June 2006 and the second between June 2009 and December 2011. Data analysis was performed between June 2014 and May 2016.

Main Outcomes and Measures

Separate teams of stroke-trained neurologists performed CCS, TOAST, and ASCO classifications based on information available at the time of hospital discharge. We assessed the association between etiologic subtypes and stroke characteristics by computing receiver operating characteristic curves for binary variables (90-day stroke recurrence and 90-day mortality) and by calculating the ratio of between-category to within-category variability from the analysis of variance for continuous variables (admission National Institutes of Health Stroke Scale score and acute infarct volume).

Results

Among the 1816 patients included, the median age was 70 years (interquartile range, 58-80 years) (830 women [46%]). The classification systems differed in their ability to assign stroke etiologies into known subtypes; the size of the undetermined category was 33% by CCS, 53% by TOAST, and 42% by ASCO (P < .001 for all binary comparisons). All systems provided significant discrimination for the validation variables tested. For the primary validation variable (90-day recurrence), the area under the receiver operating characteristic curve was 0.71 (95% CI, 0.66-0.75) for CCS, 0.61 (95% CI, 0.56-0.67) for TOAST, and 0.66 (95% CI, 0.60-0.71) for ASCO (P = .01 for CCS vs ASCO; P < .001 for CCS vs TOAST; P = .13 for ASCO vs TOAST). The classification systems exhibited similar discrimination for 90-day mortality. For admission National Institutes of Health Stroke Scale score and acute infarct volume, CCS generated more distinct subtypes with higher between-category to within-category variability than TOAST and ASCO.

Conclusions and Relevance

Our findings suggest that the major etiologic stroke subtypes are distinct categories with different stroke characteristics irrespective of the classification system used to identify them. We further show that CCS generates discrete etiologic categories with more diverse clinical, imaging, and prognostic characteristics than either TOAST or ASCO.

Etiologic classification of ischemic stroke: Where do we stand?

Despite major technological advances in ischemic stroke diagnostic techniques, our current understanding of stroke mechanisms and etiology continues to remain unclear in a significant percent of patients. As a result, several etiological ischemic stroke classifications have emerged during the last two decades but their reliability and validity is far from perfect and further world-wide research is needed in order to achieve the so much needed "standard reference language". An ideal ischemic stroke classification should both comprise all underlying pathologies that could potentially concur to an index event and emphasize the most likely etiological and pathophysiological mechanism. Currently available approaches to ischemic stroke classification are either phenotypic or causative in nature, a multitude of criteria being published by different authors. Phenotypic classifications are targeted towards describing the concurring underlying pathologies, without highlighting the most probable ischemic stroke etiology, while causative classifications focus on establishing the most likely cause, neglecting other associated diseases. A judicious use of this two different concepts might improve clinical research as well as daily clinical practice.

Recurrent stroke in patients with patent foramen ovale: An observational prospective study of percutaneous closure of PFO versus non-closure

AIMS

Observational studies favor percutaneous closure of patent foramen ovale (PFO) over medical therapy to reduce the risk of recurrent stroke, whereas randomized clinical trials have not shown significant differences. This study aims to compare long-term outcomes of PFO closure versus non-closure.

METHODS AND RESULTS

Patients with PFO and stroke considered for PFO closure were invited to a long-term clinical follow-up. Of the 314 patients, 151 (48%) were accepted for closure and 163 (52%) were not accepted (mean age 50 vs. 58 years). The cumulative incidence of all-cause mortality, stroke or transient ischemic attacks (TIAs) for closure vs. non-closure under a mean follow-up time of five years was 10.6% (16 events) vs. 12.9% (21 events), p=0.53. Six patients, 3.7% vs. 3.6%, died in each group, but no deaths were associated with PFO closure, recurrent stroke or TIA. The incidence of recurrent stroke or TIA for closure vs. non-closure was 6.6% (10 events) vs. 9.2% (15 events), p=0.63. The respective event rates for stroke were 3.9% (6 events) vs. 5.5% (9 events), p=0.50 and for TIA, 2.6% (4 events) vs. 3.7% (6 events), p=0.59.

CONCLUSION

PFO closure was associated with a low risk of recurrent events; however, compared to the non-closure group, no significant differences could be demonstrated. Careful patient selection can avoid under- as well as over-treatment of PFO patients.

Left atrial septal pouch in cryptogenic stroke

Background: The left atrial septal pouch (LASP), an anatomic variant of the interatrial septum, has uncertain clinical significance. We examined the association between LASP and ischemic stroke subtypes in patients undergoing transesophageal echocardiography (TEE).

Methods: We determined the prevalence of LASP among consecutive patients who underwent TEE at our institution. Patients identified with ischemic strokes were further evaluated for stroke subtype using standard and modified criteria from the Trial of Org 10172 in Acute Stroke Treatment (TOAST). We compared the prevalence of LASP in ischemic stroke, cryptogenic stroke, and non-stroke patients using prevalence ratios (PR).

Results: The mean age of all 212 patients (including stroke and non-stroke patients) was 57 years. The overall prevalence of LASP was 17% (n = 35). Of the 75 patients who were worked-up for stroke at our institution during study period, we classified 31 as cryptogenic using standard TOAST criteria. The prevalence of LASP among cryptogenic stroke patients (using standard and modified TOAST criteria) was increased compared to the prevalence among other ischemic stroke patients (26 vs. 9%, p = 0.06; PR = 1.8, 95% CI = 1.1–3.1, and 30 vs. 10%, p = 0.04; PR = 2.2, 95% CI = 1.2–4.1, respectively).

Conclusion: In this population of relatively young patients, prevalence of LASP was increased in cryptogenic stroke compared to stroke patients of other subtypes. These findings suggest LASP is associated with cryptogenic stroke, which should be verified by future large-scale studies.

Genetic overlap between diagnostic subtypes of ischemic stroke

BACKGROUND AND PURPOSE

Despite moderate heritability, the phenotypic heterogeneity of ischemic stroke has hampered gene discovery, motivating analyses of diagnostic subtypes with reduced sample sizes. We assessed evidence for a shared genetic basis among the 3 major subtypes: large artery atherosclerosis (LAA), cardioembolism, and small vessel disease (SVD), to inform potential cross-subtype analyses.

METHODS

Analyses used genome-wide summary data for 12 389 ischemic stroke cases (including 2167 LAA, 2405 cardioembolism, and 1854 SVD) and 62 004 controls from the Metastroke consortium. For 4561 cases and 7094 controls, individual-level genotype data were also available. Genetic correlations between subtypes were estimated using linear mixed models and polygenic profile scores. Meta-analysis of a combined LAA-SVD phenotype (4021 cases and 51 976 controls) was performed to identify shared risk alleles.

RESULTS

High genetic correlation was identified between LAA and SVD using linear mixed models (rg=0.96, SE=0.47, P=9×10(-4)) and profile scores (rg=0.72; 95% confidence interval, 0.52-0.93). Between LAA and cardioembolism and SVD and cardioembolism, correlation was moderate using linear mixed models but not significantly different from zero for profile scoring. Joint meta-analysis of LAA and SVD identified strong association (P=1×10(-7)) for single nucleotide polymorphisms near the opioid receptor μ1 (OPRM1) gene.

CONCLUSIONS

Our results suggest that LAA and SVD, which have been hitherto treated as genetically distinct, may share a substantial genetic component. Combined analyses of LAA and SVD may increase power to identify small-effect alleles influencing shared pathophysiological processes.

Pathogenic ischemic stroke phenotypes in the NINDS-stroke genetics network

BACKGROUND AND PURPOSE

NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium.

METHODS

Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases.

RESULTS

The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75).

CONCLUSIONS

This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.

MRI-based Algorithm for Acute Ischemic Stroke Subtype Classification

Background and Purpose

In order to improve inter-rater reliability and minimize diagnosis of undetermined etiology for stroke subtype classification, using a stroke registry, we developed and implemented a magnetic resonance imaging (MRI)-based algorithm for acute ischemic stroke subtype classification (MAGIC).

Methods

We enrolled patients who experienced an acute ischemic stroke, were hospitalized in the 14 participating centers within 7 days of onset, and had relevant lesions on MR-diffusion weighted imaging (DWI). MAGIC was designed to reflect recent advances in stroke imaging and thrombolytic therapy. The inter-rater reliability was compared with and without MAGIC to classify the Trial of Org 10172 in Acute Stroke Treatment (TOAST) of each stroke patient. MAGIC was then applied to all stroke patients hospitalized since July 2011, and information about stroke subtypes, other clinical characteristics, and stroke recurrence was collected via a web-based registry database.

Results

The overall intra-class correlation coefficient (ICC) value was 0.43 (95% CI, 0.31-0.57) for MAGIC and 0.28 (95% CI, 0.18-0.42) for TOAST. Large artery atherosclerosis (LAA) was the most common cause of acute ischemic stroke (38.3%), followed by cardioembolism (CE, 22.8%), undetermined cause (UD, 22.2%), and small-vessel occlusion (SVO, 14.6%). One-year stroke recurrence rates were the highest for two or more UDs (11.80%), followed by LAA (7.30%), CE (5.60%), and SVO (2.50%).

Conclusions

Despite several limitations, this study shows that the MAGIC system is feasible and may be helpful to classify stroke subtype in the clinic.

Agreement between TOAST and CCS ischemic stroke classification: the NINDS SiGN study

OBJECTIVE

The objective of this study was to assess the level of agreement between stroke subtype classifications made using the Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS) systems.

METHODS

Study subjects included 13,596 adult men and women accrued from 20 US and European genetic research centers participating in the National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN). All cases had independently classified TOAST and CCS stroke subtypes. Kappa statistics were calculated for the 5 major ischemic stroke subtypes common to both systems.

RESULTS

The overall agreement between TOAST and CCS was moderate (agreement rate, 70%; κ = 0.59, 95% confidence interval [CI] 0.58-0.60). Agreement varied widely across study sites, ranging from 28% to 90%. Agreement on specific subtypes was highest for large-artery atherosclerosis (κ = 0.71, 95% CI 0.69-0.73) and lowest for small-artery occlusion (κ = 0.56, 95% CI 0.54-0.58).

CONCLUSION

Agreement between TOAST and CCS diagnoses was moderate. Caution is warranted when comparing or combining results based on the 2 systems. Replication of study results, for example, genome-wide association studies, should utilize phenotypes determined by the same classification system, ideally applied in the same manner.

Embolic strokes of undetermined source: the case for a new clinical construct

Cryptogenic (of unknown cause) ischaemic strokes are now thought to comprise about 25% of all ischaemic strokes. Advances in imaging techniques and improved understanding of stroke pathophysiology have prompted a reassessment of cryptogenic stroke. There is persuasive evidence that most cryptogenic strokes are thromboembolic. The thrombus is thought to originate from any of several well established potential embolic sources, including minor-risk or covert cardiac sources, veins via paradoxical embolism, and non-occlusive atherosclerotic plaques in the aortic arch, cervical, or cerebral arteries. Accordingly, we propose that embolic strokes of undetermined source are a therapeutically relevant entity, which are defined as a non-lacunar brain infarct without proximal arterial stenosis or cardioembolic sources, with a clear indication for anticoagulation. Because emboli consist mainly of thrombus, anticoagulants are likely to reduce recurrent brain ischaemia more effectively than are antiplatelet drugs. Randomised trials testing direct-acting oral anticoagulants for secondary prevention of embolic strokes of undetermined source are warranted.

Ischemic stroke subtype classification: an asian viewpoint

Proper classification of the causative mechanism of stroke is important for optimizing stroke treatment and assessing prognosis. The primary etiology of stroke differs according to race and ethnicity: emboli originating from the heart or extracranial large arteries are common in Western populations, whereas small-vessel occlusion or intracranial atherosclerosis is more prevalent in Asians. Intracranial atherosclerosis frequently leads to stroke by branch-artery occlusion, and the degree of stenosis in these cases is often <50%. Mild intracranial atherosclerotic stenosis may cause distal embolization, if the atherosclerotic plaque is sufficiently vulnerable. Moreover, high-resolution magnetic resonance imaging studies have identified small plaques causing infarction, even in patients with normal-appearing vascular findings. Such cases, which are prevalent in Asia, could not be classified as large-artery atherosclerosis by previous classification systems. Additionally, single subcortical infarctions, which are usually attributed to lipohyalinotic small-vessel disease, can have other causes, including microatheroma of perforators and atherothrombotic lesions at the parental artery. Single subcortical infarctions associated with parental artery disease or those bordering on the main vessel more often have atherosclerotic characteristics than do those associated with lipohyalinosis of the penetrating artery. In countries where intracranial atherosclerosis is common, such atherosclerotic single subcortical infarctions are predicted to be prevalent. These cases, however, could not be appropriately classified in previous systems. Further effort should be devoted to formulate ischemic stroke classification systems that adequately incorporate results of recent studies and reflect the underling pathologic mechanisms, especially in patients with single subcortical infarction and intracranial atherosclerosis.

Types of Stroke Recurrence in Patients with Ischemic Stroke: A Substudy from the PRoFESS Trial

Background

Risk profiles for stroke recurrence are poorly characterized.

Aims

We determined the variation in the risk and type of recurrent stroke among index ischemic stroke subtypes, and whether index stroke subtype and conventional stroke risk factors were predictors of stroke recurrence.

Methods

Patients enrolled in the Prevention Regimen for Effectively Avoiding Second Strokes trial were included in this study.

Results

In 1794 patients' recurrent stroke subtypes were the same as the index stroke in: 48·3% of patients with large artery atherothrombosis stroke; 50% of patients with cardioembolic stroke; 48·7% of patients with small artery occlusion stroke; 8·1% of patients with stroke of other etiology, and 45·3% of patients with undetermined etiology stroke. Patients with cardioembolic stroke, who were unwilling or unable to take oral anticoagulants, had the greatest risk of stroke recurrence. Predictors of stroke recurrence in multivariable analysis were: older age and previous stroke among large artery atherothrombosis strokes; older age, male sex, previous stroke, previous transient ischemic attack, hypertension, diabetes, and tobacco use among small artery occlusion strokes; older age among cardioembolic strokes; atrial fibrillation and anti-diabetic medications among other etiology strokes; older age, previous stroke and atrial fibrillation among undetermined etiology strokes. Predictors of brain hemorrhage as recurrent stroke were index small artery occlusion stroke, older age, previous stroke, and antiplatelet treatment with aspirin plus extended-release dipyridamole.

Conclusions

Risk predictors for stroke recurrence and for brain hemorrhage differ by index ischemic stroke subtype, information that is important when initiating secondary prevention therapy.

Does the STAF score help detect paroxysmal atrial fibrillation in acute stroke patients?

BACKGROUND AND PURPOSE

Detecting paroxysmal atrial fibrillation (pAF) soon after acute cerebral ischaemia has a major impact on secondary stroke prevention. Recently, the STAF score, a composite of clinical and instrumental findings, was introduced to identify stroke patients at risk of pAF. We aimed to validate this score in an independent study population.

METHODS

Consecutive patients admitted to our stroke unit with acute ischaemic stroke were prospectively enrolled. The diagnostic work-up included neuroimaging, neuroultrasound, baseline 12-channel electrocardiogram (ECG), 24-h Holter ECG, continuous ECG monitoring, and echocardiography. Presence of AF was documented according to the medical history of each patient and after review of 12-lead ECG, 24-h Holter ECG, or continuous ECG monitoring performed during the stay on the ward. Additionally, a telephone follow-up visit was conducted for each patient after 3 months to inquire about newly diagnosed AF. Items for each patient-age, baseline NIHSS, left atrial dilatation, and stroke etiology according to the TOAST criteria - were assessed to calculate the STAF score.

RESULTS

Overall, 584 patients were enrolled in our analysis. AF was documented in 183 (31.3%) patients. In multivariable analysis, age, NIHSS, left atrial dilatation, and absence of vascular etiology were independent predictors for AF. The logistic AF-prediction model of the STAF score revealed fair classification accuracy in receiver operating characteristic curve analysis with an area under the curve of 0.84. STAF scores of ≥5 had a sensitivity of 79% and a specificity of 74% for predicting AF.

CONCLUSION

The value of the STAF score for predicting the risk of pAF in stroke patients is limited.

Stroke subtyping for genetic association studies? A comparison of the CCS and TOAST classifications

BACKGROUND

A reliable and reproducible classification system of stroke subtype is essential for epidemiological and genetic studies. The Causative Classification of Stroke system is an evidence-based computerized algorithm with excellent inter-rater reliability. It has been suggested that, compared to the Trial of ORG 10172 in Acute Stroke Treatment classification, it increases the proportion of cases with defined subtype that may increase power in genetic association studies. We compared Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications in a large cohort of well-phenotyped stroke patients.

METHODS

Six hundred ninety consecutively recruited patients with first-ever ischemic stroke were classified, using review of clinical data and original imaging, according to the Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications.

RESULTS

There was excellent agreement subtype assigned by between Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system (kappa = 0·85). The agreement was excellent for the major individual subtypes: large artery atherosclerosis kappa = 0·888, small-artery occlusion kappa = 0·869, cardiac embolism kappa = 0·89, and undetermined category kappa = 0·884. There was only moderate agreement (kappa = 0·41) for the subjects with at least two competing underlying mechanism. Thirty-five (5·8%) patients classified as undetermined by Trial of ORG 10172 in Acute Stroke Treatment were assigned to a definite subtype by Causative Classification of Stroke system. Thirty-two subjects assigned to a definite subtype by Trial of ORG 10172 in Acute Stroke Treatment were classified as undetermined by Causative Classification of Stroke system.

CONCLUSIONS

There is excellent agreement between classification using Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke systems but no evidence that Causative Classification of Stroke system reduced the proportion of patients classified to undetermined subtypes. The excellent inter-rater reproducibility and web-based semiautomated nature make Causative Classification of Stroke system suitable for multicenter studies, but the benefit of reclassifying cases already classified using the Trial of ORG 10172 in Acute Stroke Treatment system on existing databases is likely to be small.

Potential association between frequent nonsynonymous variant of NPPA and cardioembolic stroke

Atrial natriuretic peptide (ANP, also known as NPPA) and brain natriuretic peptide (BNP, also known as NPPB) have been determined as genetic factors for several diseases, including stroke and myocardial infarction, in human and rat models. To investigate the potential association between polymorphisms of the NPPA gene and stroke in a Korean population, nine single-nucleotide polymorphisms (SNPs) of NPPA and NPPB genes were genotyped in a total of 941 Korean subjects, including 674 stroke patients (109 hemorrhagic and 565 ischemic) and 267 unaffected controls. Genotype comparisons of the targeted alleles revealed that there were no significant associations between stroke patients and control subjects, or among hemorrhagic, ischemic, and control groups. However, in logistic analysis for Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification of ischemic stroke, nonsynonymous rs5065 (STOP152Arg) and rs5067 in 3'UTR of NPPA, which were in complete linkage disequilibrium, showed significant associations with cardioembolic stroke. These two SNPs showed higher frequencies in cardioembolic stroke patients than those in controls and ischemic patients with small-vessel occlusion (p=0.002, adjusted p=0.02). It was also found that NPPA rs5065C allele in all of the Korean subjects existed as heterozygous compared with Caucasian and African populations. Although further replications in larger cardioembolic stroke subjects are required, our preliminary findings suggest that the nonsynonymous rs5065C of the NPPA gene, which could produce a new or dysfunctional transcript, is possibly associated with cardioembolism.

Classifying Ischemic Stroke, from TOAST to CISS

Ischemic stroke classification is critical in conducting basic research and clinical practice. A precise analysis of stroke subtypes requires the integration of clinical features, findings from diagnostic tests, and knowledge about potential etiologic factors by competent diagnostic investigators. We performed a literature review of the published stroke classification systems and examined each for its benefits and limitations in the evaluation of the stroke etiology. Two major approaches to etiologic classifications of ischemic stroke are currently being used: the causative and phenotypic subtyping. The most widely used causative system is the Trial of Org 10172 in acute stroke treatment (TOAST) classification. With the advances in modern diagnostic technology, new stroke subclassification systems, such as the causative classification system (CCS) and Chinese ischemic stroke subclassification (CISS) system, have been developed to enhance the accuracy of TOAST. The A-S-C-O (Atherosclerosis, Small-vessel disease, Cardiac source, Other cause) phenotypic classification system makes efforts to identify the most likely etiology but not neglecting the possibility of other potential multiple causes. We conclude that the ideal stroke classification system needs to be valid, easy to use, evidence-based, and incorporate new information as it emerges.

Siblings with ischemic stroke study: results of a genome-wide scan for stroke loci

BACKGROUND AND PURPOSE

Ischemic stroke has a strong familial component to risk. The Siblings With Ischemic Stroke Study (SWISS) is a genome-wide, family-based analysis that included use of imputed genotypes. The Siblings With Ischemic Stroke Study was conducted to examine the associations between single-nucleotide polymorphisms (SNPs) and risk of stroke and stroke subtypes within pairs.

METHODS

The Siblings With Ischemic Stroke Study enrolled 312 probands with ischemic stroke from 70 US and Canadian centers. Affected siblings were ascertained by centers and confirmed by central record review; unaffected siblings were ascertained by telephone contact. Ischemic stroke was subtyped according to Trial of Org 10172 in Acute Stroke Treatment criteria. Genotyping was performed with an Illumina 610 quad array (probands) and an Illumina linkage V array (affected siblings). SNPs were imputed by using 1000 Genomes Project data and MACH software. Family-based association analyses were conducted by using the sibling transmission-disequilibrium test.

RESULTS

For all pairs, the correlation of age at stroke within pairs of affected siblings was r=0.83 (95% CI, 0.78-0.86; P<2.2×10(-16)). The correlation did not differ substantially by subtype. The concordance of stroke subtypes among affected pairs was 33.8% (kappa=0.13; P=5.06×10(-4)) and did not differ by age at stroke in the proband. Although no SNP achieved genome-wide significance for risk of ischemic stroke, there was clustering of the most associated SNPs on chromosomes 3p (neuronal nitric oxide synthase) and 6p.

CONCLUSIONS

Stroke subtype and age at stroke in affected sibling pairs exhibit significant clustering. No individual SNP reached genome-wide significance. However, 2 promising candidate loci were identified, including 1 that contains neuronal nitric oxide synthase, although these risk loci warrant further examination in larger sample collections.

The Causative Classification of Stroke system: an international reliability and optimization study

BACKGROUND

Valid and reliable ischemic stroke subtype determination is crucial for well-powered multicenter studies. The Causative Classification of Stroke System (CCS, available at http://ccs.mgh.harvard.edu) is a computerized, evidence-based algorithm that provides both causative and phenotypic stroke subtypes in a rule-based manner. We determined whether CCS demonstrates high interrater reliability in order to be useful for international multicenter studies.

METHODS

Twenty members of the International Stroke Genetics Consortium from 13 centers in 8 countries, who were not involved in the design and development of the CCS, independently assessed the same 50 consecutive patients with acute ischemic stroke through reviews of abstracted case summaries. Agreement among ratings was measured by kappa statistic.

RESULTS

The κ value for causative classification was 0.80 (95% confidence interval [CI] 0.78-0.81) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.70 (95% CI 0.69-0.71) for the 16-subtype CCS. Correction of a software-related factor that generated ambiguity improved agreement: κ = 0.81 (95% CI 0.79-0.82) for the 5-subtype, 0.79 (95% CI 0.77-0.80) for the 8-subtype, and 0.79 (95% CI 0.78-0.80) for the 16-subtype CCS. The κ value for phenotypic classification was 0.79 (95% CI 0.77-0.82) for supra-aortic large artery atherosclerosis, 0.95 (95% CI 0.93-0.98) for cardioembolism, 0.88 (95% CI 0.85-0.91) for small artery occlusion, and 0.79 (0.76-0.82) for other uncommon causes.

CONCLUSIONS

CCS allows classification of stroke subtypes by multiple investigators with high reliability, supporting its potential for improving stroke classification in multicenter studies and ensuring accurate means of communication among different researchers, institutions, and eras.

Advances in the diagnosis of etiologic subtypes of ischemic stroke

A fundamental goal of etiologic stroke classification is to generate subgroups with discrete phenotypic, therapeutic, and prognostic features. Accurate stroke classification requires integration of multiple aspects of diagnostic stroke evaluation in a standardized manner. Diagnostic test findings can be simply organized into major etiologic groups to create a phenotypic subtype, or they can be reduced to a single causative subtype through a decision-making process. It is essential for a classification system to provide consistent results across different raters in different clinical settings. Comparability of subtype assignments is the key to valid communication of research results across the field. This article highlights important theoretical aspects of etiologic stroke classification and reviews major etiologic classification systems that have benefited from recent advances in etiologic stroke evaluation.

Candidate gene polymorphisms for ischemic stroke

BACKGROUND AND PURPOSE

Ischemic stroke (IS) is a multifactorial disorder with strong evidence from twin, family, and animal model studies suggesting a genetic influence on risk and prognosis. Several candidate genes for IS have been proposed, but few have been replicated. We investigated the contribution of 67 candidate genes (369 single nucleotide polymorphisms [SNPs]) on the risk of IS in a North American population of European descent.

METHODS

Two independent studies were performed. In the first, 342 SNPs from 52 candidate genes were genotyped in 307 IS cases and 324 control subjects. The SNPs significantly associated with IS were tested for replication in another cohort of 583 IS cases and 270 control subjects. In the second study, 212 SNPs from 62 candidate genes were analyzed in 710 IS cases with subtyping available and 3751 control subjects.

RESULTS

None of the candidate genes (SNPs) were significantly associated with IS risk independent of known stroke risk factors after correction for multiple hypotheses testing.

CONCLUSIONS

These results are consistent with previous meta-analyses that demonstrate an absence of genetic association of variants in plausible candidate genes with IS risk. Our study suggests that the effect of the investigated SNPs may be weak or restricted to specific populations or IS subtypes.