Abstract 205: Etiologic Ischemic Stroke Phenotypes in the NINDS Stroke Genetics Network

Background and Purpose: NINDS Stroke Genetics Network (SiGN) is an international consortium of ischemic stroke studies that aims to generate high quality phenotype data to identify the genetic basis of ischemic stroke subtypes. The goal of this analysis is to characterize the etiopathogenetic basis of ischemic stroke in the consortium. Methods: This analysis included 16,954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries. 52 trained and certified adjudicators used the web-based Causative Classification of Stroke System for etiologic stroke classification through chart reviews to determine both phenotypic (abnormal test findings categorized in major etiologic groups without weighting towards the most likely cause in the presence of multiple etiologies) and causative subtypes in each subject. Classification reliability was assessed with blinded re-adjudication of 1509 randomly selected cases. Findings: The figure shows the distribution of etiologic categories. Overall, only 40% to 54% of cases with a given major ischemic stroke etiology (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (kappa 0·72, 95%CI:0·69-0·75) and phenotypic classifications (kappa 0·73, 95%CI:0·70-0·75). Conclusions: This study provides high quality data on etiologic stroke subtypes and demonstrates that etiologic 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 suggests that the presence of an abnormality in a stroke patient does not necessarily mean that it is the cause of stroke.

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A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High Quality Data

10.31234/osf.io/asc67 ◽

2021 ◽

Author(s):

Victoria Leong ◽

Kausar Raheel ◽

Sim Jia Yi ◽

Kriti Kacker ◽

Vasilis M. Karlaftis ◽

...

Keyword(s):

Data Quality ◽

Response Times ◽

Psychological Research ◽

Cognitive Testing ◽

Quality Data ◽

High Quality ◽

Online Data ◽

Test Environment ◽

Web Based ◽

Cognitive Data

Background. The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted both safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the fore as a promising solution for rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. Here, we examine the opportunities and challenges afforded by the societal shift toward web-based testing, highlight an urgent need to establish a standard data quality assurance framework for online studies, and develop and validate a new supervised online testing methodology, remote guided testing (RGT). Methods. A total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (N=41) or online using remote guided testing (N=44), delivered using identical web-based platforms (CANTAB, Inquisit and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, response times), as well as overall task performance measures. Results. The results indicated that, across all measures of data quality and performance, RGT data was statistically-equivalent to data collected in person in the lab. Moreover, RGT participants out-performed the lab group on measured verbal intelligence, which could reflect test environment differences, including possible effects of mask-wearing on communication. Conclusions. These data suggest that the RGT methodology could help to ameliorate concerns regarding online data quality and - particularly for studies involving high-risk or rare cohorts - offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance.

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A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High Quality Data (Preprint)

10.2196/preprints.28368 ◽

2021 ◽

Author(s):

Victoria Leong ◽

Kausar Raheel ◽

Jia Yi Sim ◽

Kriti Kacker ◽

Vasilis M Karlaftis ◽

...

Keyword(s):

Data Quality ◽

Response Times ◽

Psychological Research ◽

Cognitive Testing ◽

Quality Data ◽

High Quality ◽

Online Data ◽

Test Environment ◽

Web Based ◽

Cognitive Data

BACKGROUND The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted both safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the fore as a promising solution for rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. OBJECTIVE Here, we examine the opportunities and challenges afforded by the societal shift toward web-based testing, highlight an urgent need to establish a standard data quality assurance framework for online studies, and develop and validate a new supervised online testing methodology, remote guided testing (RGT). METHODS A total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (N=41) or online using remote guided testing (N=44), delivered using identical web-based platforms (CANTAB, Inquisit and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, response times), as well as overall task performance measures. RESULTS The results indicated that, across all measures of data quality and performance, RGT data was statistically-equivalent to data collected in person in the lab. Moreover, RGT participants out-performed the lab group on measured verbal intelligence, which could reflect test environment differences, including possible effects of mask-wearing on communication. CONCLUSIONS These data suggest that the RGT methodology could help to ameliorate concerns regarding online data quality and - particularly for studies involving high-risk or rare cohorts - offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance. CLINICALTRIAL N.A.

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Blood Biomarkers for the Differentiation of Cardiac Ischemic Stroke Subtypes: A Systematic Review

Cardiovascular & Haematological Disorders - Drug Targets ◽

10.2174/1871529x18666180829142354 ◽

2019 ◽

Vol 19 (3) ◽

pp. 215-227

Author(s):

Abhishek Pathak ◽

Surya P. Pandey ◽

Prasoon Madhukar ◽

Priya Dev ◽

Deepika Joshi ◽

...

Keyword(s):

Systematic Review ◽

Ischemic Stroke ◽

Cost Effective ◽

Sample Collection ◽

Blood Biomarkers ◽

Medical Databases ◽

Blood Biomarker ◽

Stroke Subtypes

Background: Blood biomarkers are a cost-effective and valid method to diagnose ischemic stroke and differentiate its subtypes in countries with poor resources. Objective: To perform a systematic review of published literature evaluating the diagnostic utility of blood-based biomarkers to diagnose and differentiate the etiology of ischemic stroke. Methods: A comprehensive literature search was carried out till December 2017 in major scientific and medical databases including PubMed, Cochrane, OVID and Google Scholar. Modified Quality Assessment of Diagnostic Accuracy Studies questionnaire was used to assess the methodological quality of each study. Results: Twenty-six studies were identified relevant to our systematic review. Various biomarkers have been studied, though only a few biomarkers such as a B-type natriuretic peptide (BNP) and Ddimer have proved their clinical utility. None of the other tested biomarkers appeared to have consistent results to diagnose ischemic stroke subtypes. Most of the studies had limitations in the classification of ischemic stroke, sample size, sample collection time, methods, biomarker selection and data analysis. Conclusion: Our systematic review does not recommend the use of any blood biomarker for clinical purposes based on the studies conducted to date. BNP and D-dimer may present optimal biomarker for diagnosis and differentiation of ischemic stroke. However, large well-designed clinical studies are required to validate utility of these biomarkers to differentiate subtypes of ischemic stroke.

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Design and rationale for examining neuroimaging genetics in ischemic stroke

Neurology Genetics ◽

10.1212/nxg.0000000000000180 ◽

2017 ◽

Vol 3 (5) ◽

pp. e180 ◽

Cited By ~ 15

Author(s):

Anne-Katrin Giese ◽

Markus D. Schirmer ◽

Kathleen L. Donahue ◽

Lisa Cloonan ◽

Robert Irie ◽

...

Keyword(s):

Ischemic Stroke ◽

Clinical Care ◽

Cerebrovascular Lesions ◽

Web Based ◽

Genome Wide ◽

Clinical Phenotyping ◽

Neuroimaging Genetics ◽

Analysis Platform

Objective:To describe the design and rationale for the genetic analysis of acute and chronic cerebrovascular neuroimaging phenotypes detected on clinical MRI in patients with acute ischemic stroke (AIS) within the scope of the MRI–GENetics Interface Exploration (MRI-GENIE) study.Methods:MRI-GENIE capitalizes on the existing infrastructure of the Stroke Genetics Network (SiGN). In total, 12 international SiGN sites contributed MRIs of 3,301 patients with AIS. Detailed clinical phenotyping with the web-based Causative Classification of Stroke (CCS) system and genome-wide genotyping data were available for all participants. Neuroimaging analyses include the manual and automated assessments of established MRI markers. A high-throughput MRI analysis pipeline for the automated assessment of cerebrovascular lesions on clinical scans will be developed in a subset of scans for both acute and chronic lesions, validated against gold standard, and applied to all available scans. The extracted neuroimaging phenotypes will improve characterization of acute and chronic cerebrovascular lesions in ischemic stroke, including CCS subtypes, and their effect on functional outcomes after stroke. Moreover, genetic testing will uncover variants associated with acute and chronic MRI manifestations of cerebrovascular disease.Conclusions:The MRI-GENIE study aims to develop, validate, and distribute the MRI analysis platform for scans acquired as part of clinical care for patients with AIS, which will lead to (1) novel genetic discoveries in ischemic stroke, (2) strategies for personalized stroke risk assessment, and (3) personalized stroke outcome assessment.

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Efficient capture of high-quality real-world data on treatments for glaucoma: the Fight Glaucoma Blindness! Registry

BMJ Open Ophthalmology ◽

10.1136/bmjophth-2021-000903 ◽

2021 ◽

Vol 6 (1) ◽

pp. e000903

Author(s):

Mitchell Lawlor ◽

Vuong Nguyen ◽

Anne Brooks ◽

Colin Clement ◽

Jamie E Craig ◽

...

Keyword(s):

Data Collection ◽

Real World ◽

Steering Committee ◽

Quality Data ◽

Easy Access ◽

Routine Practice ◽

Real World Data ◽

High Quality ◽

Data Set ◽

Web Based

ObjectiveTo describe the development and implementation of a web-based high-quality data collection tool to track the outcomes of glaucoma treatments in routine practice.Methods and analysisThis is a prospective observational registry study. An international steering committee undertook an iterative structured process to define a minimum, patient-centred data set designed to track outcomes of glaucoma treatment. The outcomes were coded into a web-based programme allowing easy access for rapid data entry. Clinicians receive personal reports enabling instant audit of their outcomes. Analyses of aggregated anonymised data on real-world outcomes are analysed and periodically reported with the goal of improving patient care.ResultsThe minimum data set developed by the international steering committee includes the following: a baseline visit captures 13 mandatory fields in order to accurately phenotype each patient’s subtype of glaucoma and to allow comparison between services, and a follow-up visit includes only four mandatory fields to allow completion within 30 s.Currently, there are 157 surgeons in 158 ophthalmology practices across Australia and New Zealand who are registered. These surgeons are tracking 5570 eyes of 3001 patients and have recorded 67 074 visits. The median number of eyes per surgeon is 22 eyes with a range of 1–575. The most common glaucoma procedure, excluding cataract surgery, is iStent inject, with 2316 cases.ConclusionThis software tool effectively facilitates data collection on safety and efficacy outcomes of treatments for different subgroups of glaucoma within a real-world setting. It provides a template to evaluate new treatments as they are introduced into practice.

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EndoVAscular treatment and ThRombolysis for Ischemic Stroke Patients (EVA-TRISP) registry: basis and methodology of a pan-European prospective ischaemic stroke revascularisation treatment registry

BMJ Open ◽

10.1136/bmjopen-2020-042211 ◽

2021 ◽

Vol 11 (8) ◽

pp. e042211

Author(s):

Annika Nordanstig ◽

Sami Curtze ◽

Henrik Gensicke ◽

Sanne M Zinkstok ◽

Hebun Erdur ◽

...

Keyword(s):

Ischemic Stroke ◽

Ischaemic Stroke ◽

Endovascular Treatment ◽

Intravenous Thrombolysis ◽

Quality Data ◽

Stroke Patients ◽

High Quality ◽

Specific Patient ◽

Safety And Efficacy ◽

Research Questions

PurposeThe Thrombolysis in Ischemic Stroke Patients (TRISP) collaboration was a concerted effort initiated in 2010 with the purpose to address relevant research questions about the effectiveness and safety of intravenous thrombolysis (IVT). The collaboration also aims to prospectively collect data on patients undergoing endovascular treatment (EVT) and hence the name of the collaboration was changed from TRISP to EVA-TRISP. The methodology of the former TRISP registry for patients treated with IVT has already been published. This paper focuses on describing the EVT part of the registry.ParticipantsAll centres committed to collecting predefined variables on consecutive patients prospectively. We aim for accuracy and completeness of the data and to adapt local databases to investigate novel research questions. Herein, we introduce the methodology of a recently constructed academic investigator-initiated open collaboration EVT registry built as an extension of an existing IVT registry in patients with acute ischaemic stroke (AIS).Findings to dateCurrently, the EVA-TRISP network includes 20 stroke centres with considerable expertise in EVT and maintenance of high-quality hospital-based registries. Following several successful randomised controlled trials (RCTs), many important clinical questions remain unanswered in the (EVT) field and some of them will unlikely be investigated in future RCTs. Prospective registries with high-quality data on EVT-treated patients may help answering some of these unanswered issues, especially on safety and efficacy of EVT in specific patient subgroups.Future plansThis collaborative effort aims at addressing clinically important questions on safety and efficacy of EVT in conditions not covered by RCTs. The TRISP registry generated substantial novel data supporting stroke physicians in their daily decision making considering IVT candidate patients. While providing observational data on EVT in daily clinical practice, our future findings may likewise be hypothesis generating for future research as well as for quality improvement (on EVT). The collaboration welcomes participation of further centres willing to fulfill the commitment and the outlined requirements.

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SPARKLE (Subtypes of Ischaemic Stroke Classification System), Incorporating Measurement of Carotid Plaque Burden: A New Validated Tool for the Classification of Ischemic Stroke Subtypes

Neuroepidemiology ◽

10.1159/000362417 ◽

2014 ◽

Vol 42 (4) ◽

pp. 243-251 ◽

Cited By ~ 25

Author(s):

Chrysi Bogiatzi ◽

Thapat Wannarong ◽

A. Ian McLeod ◽

Marnin Heisel ◽

Daniel Hackam ◽

...

Keyword(s):

Ischemic Stroke ◽

Ischaemic Stroke ◽

Classification System ◽

Carotid Plaque ◽

Plaque Burden ◽

Stroke Subtypes ◽

Stroke Classification

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Amino Acid Biosignature in Plasma among Ischemic Stroke Subtypes

BioMed Research International ◽

10.1155/2019/8480468 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 5

Author(s):

Vânia A. M. Goulart ◽

Marcelo M. Sena ◽

Thiago O. Mendes ◽

Helvécio C. Menezes ◽

Zenilda L. Cardeal ◽

...

Keyword(s):

Ischemic Stroke ◽

Amino Acid ◽

Cognitive Abilities ◽

Plasma Concentrations ◽

Control Group ◽

Concentration Data ◽

Stroke Subtypes ◽

Important Amino Acid ◽

And Control

Ischemic stroke is a neurovascular disorder caused by reduced or blockage of blood flow to the brain, which may permanently affect motor and cognitive abilities. The diagnostic of stroke is performed using imaging technologies, clinical evaluation, and neuropsychological protocols, but no blood test is available yet. In this work, we analyzed amino acid concentrations in blood plasma from poststroke patients in order to identify differences that could characterize the stroke etiology. Plasma concentrations of sixteen amino acids from patients with chronic ischemic stroke (n = 73) and the control group (n = 16) were determined using gas chromatography coupled to mass spectrometry (GC-MS). The concentration data was processed by Partial Least Squares-Discriminant Analysis (PLS-DA) to classify patients with stroke and control. The amino acid analysis generated a first model able to discriminate ischemic stroke patients from control group. Proline was the most important amino acid for classification of the stroke samples in PLS-DA, followed by lysine, phenylalanine, leucine, and glycine, and while higher levels of methionine and alanine were mostly related to the control samples. The second model was able to discriminate the stroke subtypes like atherothrombotic etiology from cardioembolic and lacunar etiologies, with lysine, leucine, and cysteine plasmatic concentrations being the most important metabolites. Our results suggest an amino acid biosignature for patients with chronic stroke in plasma samples, which can be helpful in diagnosis, prognosis, and therapeutics of these patients.

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