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      Risk stratification in symptomatic intracranial atherosclerotic disease with conventional vascular risk factors and cerebral haemodynamics

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          Abstract

          Background and purpose

          Symptomatic intracranial atherosclerotic stenosis (sICAS) is associated with a considerable risk of recurrent stroke despite contemporarily optimal medical treatment. Severity of luminal stenosis in sICAS and its haemodynamic significance quantified with computational fluid dynamics (CFD) models were associated with the risk of stroke recurrence. We aimed to develop and compare stroke risk prediction nomograms in sICAS, based on vascular risk factors and these metrics.

          Methods

          Patients with 50%–99% sICAS confirmed in CT angiography (CTA) were enrolled. Conventional vascular risk factors were collected. Severity of luminal stenosis in sICAS was dichotomised as moderate (50%–69%) and severe (70%–99%). Translesional pressure ratio (PR) and wall shear stress ratio (WSSR) were quantified via CTA-based CFD modelling; the haemodynamic status of sICAS was classified as normal (normal PR&WSSR), intermediate (otherwise) and abnormal (abnormal PR&WSSR). All patients received guideline-recommended medical treatment. We developed and compared performance of nomograms composed of these variables and independent predictors identified in multivariate logistic regression, in predicting the primary outcome, recurrent ischaemic stroke in the same territory (SIT) within 1 year.

          Results

          Among 245 sICAS patients, 20 (8.2%) had SIT. The D 2H 2A nomogram, incorporating diabetes, dyslipidaemia, haemodynamic status of sICAS, hypertension and age ≥50 years, showed good calibration (P for Hosmer-Lemeshow test=0.560) and discrimination (C-statistic 0.73, 95% CI 0.60 to 0.85). It also had better performance in risk reclassification and provided larger net benefits in decision curve analysis, compared with nomograms composed of conventional vascular risk factors only, and plus the severity of luminal stenosis in sICAS. Sensitivity analysis in patients with anterior-circulation sICAS showed similar results.

          Conclusions

          The D 2H 2A nomogram, incorporating conventional vascular risk factors and the haemodynamic significance of sICAS as assessed in CFD models, could be a useful tool to stratify sICAS patients for the risk of recurrent stroke under contemporarily optimal medical treatment.

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          Most cited references34

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          Refining clinical risk stratification for predicting stroke and thromboembolism in atrial fibrillation using a novel risk factor-based approach: the euro heart survey on atrial fibrillation.

          Gregory Y. H. Lip, Robby Nieuwlaat, Ron Pisters … (2010)
          Contemporary clinical risk stratification schemata for predicting stroke and thromboembolism (TE) in patients with atrial fibrillation (AF) are largely derived from risk factors identified from trial cohorts. Thus, many potential risk factors have not been included. We refined the 2006 Birmingham/National Institute for Health and Clinical Excellence (NICE) stroke risk stratification schema into a risk factor-based approach by reclassifying and/or incorporating additional new risk factors where relevant. This schema was then compared with existing stroke risk stratification schema in a real-world cohort of patients with AF (n = 1,084) from the Euro Heart Survey for AF. Risk categorization differed widely between the different schemes compared. Patients classified as high risk ranged from 10.2% with the Framingham schema to 75.7% with the Birmingham 2009 schema. The classic CHADS(2) (Congestive heart failure, Hypertension, Age > 75, Diabetes, prior Stroke/transient ischemic attack) schema categorized the largest proportion (61.9%) into the intermediate-risk strata, whereas the Birmingham 2009 schema classified 15.1% into this category. The Birmingham 2009 schema classified only 9.2% as low risk, whereas the Framingham scheme categorized 48.3% as low risk. Calculated C-statistics suggested modest predictive value of all schema for TE. The Birmingham 2009 schema fared marginally better (C-statistic, 0.606) than CHADS(2). However, those classified as low risk by the Birmingham 2009 and NICE schema were truly low risk with no TE events recorded, whereas TE events occurred in 1.4% of low-risk CHADS(2) subjects. When expressed as a scoring system, the Birmingham 2009 schema (CHA(2)DS(2)-VASc acronym) showed an increase in TE rate with increasing scores (P value for trend = .003). Our novel, simple stroke risk stratification schema, based on a risk factor approach, provides some improvement in predictive value for TE over the CHADS(2) schema, with low event rates in low-risk subjects and the classification of only a small proportion of subjects into the intermediate-risk category. This schema could improve our approach to stroke risk stratification in patients with AF.
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            Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.

            Michael J. Pencina, Ralph B. D' Agostino, Ramachandran S. Vasan (2008)
            Identification of key factors associated with the risk of developing cardiovascular disease and quantification of this risk using multivariable prediction algorithms are among the major advances made in preventive cardiology and cardiovascular epidemiology in the 20th century. The ongoing discovery of new risk markers by scientists presents opportunities and challenges for statisticians and clinicians to evaluate these biomarkers and to develop new risk formulations that incorporate them. One of the key questions is how best to assess and quantify the improvement in risk prediction offered by these new models. Demonstration of a statistically significant association of a new biomarker with cardiovascular risk is not enough. Some researchers have advanced that the improvement in the area under the receiver-operating-characteristic curve (AUC) should be the main criterion, whereas others argue that better measures of performance of prediction models are needed. In this paper, we address this question by introducing two new measures, one based on integrated sensitivity and specificity and the other on reclassification tables. These new measures offer incremental information over the AUC. We discuss the properties of these new measures and contrast them with the AUC. We also develop simple asymptotic tests of significance. We illustrate the use of these measures with an example from the Framingham Heart Study. We propose that scientists consider these types of measures in addition to the AUC when assessing the performance of newer biomarkers.
            Article 0 comments Cited 736 times – based on 0 reviews     Review now
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              Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association.

              Walter Kernan, Bruce Ovbiagele, Henry Black … (2014)
              The aim of this updated guideline is to provide comprehensive and timely evidence-based recommendations on the prevention of future stroke among survivors of ischemic stroke or transient ischemic attack. The guideline is addressed to all clinicians who manage secondary prevention for these patients. Evidence-based recommendations are provided for control of risk factors, intervention for vascular obstruction, antithrombotic therapy for cardioembolism, and antiplatelet therapy for noncardioembolic stroke. Recommendations are also provided for the prevention of recurrent stroke in a variety of specific circumstances, including aortic arch atherosclerosis, arterial dissection, patent foramen ovale, hyperhomocysteinemia, hypercoagulable states, antiphospholipid antibody syndrome, sickle cell disease, cerebral venous sinus thrombosis, and pregnancy. Special sections address use of antithrombotic and anticoagulation therapy after an intracranial hemorrhage and implementation of guidelines. © 2014 American Heart Association, Inc.
              Article 0 comments Cited 553 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Stroke Vasc Neurol
                Journal ID (iso-abbrev): Stroke Vasc Neurol
                Journal ID (hwp): svnbmj
                Journal ID (publisher-id): svn
                Title: Stroke and Vascular Neurology
                Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                ISSN (Print): 2059-8688
                ISSN (Electronic): 2059-8696
                Publication date Collection: February 2023
                Publication date (Electronic): 14 September 2022
                Volume: 8
                Issue: 1
                Pages: 77-85
                Affiliations
                [1 ] departmentDepartment of Medicine and Therapeutics , The Chinese University , Hong Kong, China
                [2 ] departmentDepartment of Neurology , The First Affiliated Hospital of Zhengzhou University , Zhengzhou, Henan, China
                [3 ] departmentDepartment of Neurology , The First Affiliated Hospital of Sun Yat-sen University , Guangzhou, Guangdong, China
                [4 ] departmentDepartment of Imaging and Interventional , The Chinese University , Hong Kong, China
                [5 ] departmentResearch Centre of Intelligent Healthcare, Faculty of Health and Life Science , Coventry University , Coventry, UK
                [6 ] departmentDepartment of Neurology , Nanjing University Medical School Affiliated Nanjing Drum Tower Hospital , Nanjing, Jiangsu, China
                [7 ] departmentDepartment of Radiology , Nanjing University Medical School Affiliated Nanjing Drum Tower Hospital , Nanjing, Jiangsu, China
                Author notes
                [Correspondence to ] Dr Xinyi Leng; xinyi_leng@ 123456cuhk.edu.hk
                Author information
                http://orcid.org/0000-0002-4983-209X
                http://orcid.org/0000-0002-1619-4992
                http://orcid.org/0000-0001-5288-0319
                http://orcid.org/0000-0001-8193-0709
                http://orcid.org/0000-0001-7300-6647
                Article
                Publisher ID: svn-2022-001606
                DOI: 10.1136/svn-2022-001606
                PMC ID: 9985805
                PubMed ID: 36104090
                SO-VID: 65e189b4-1fda-451d-9c33-ca3c3c5e56a4
                Copyright © © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
                License:

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

                History
                Date received : 29 March 2022
                Date accepted : 02 September 2022
                Funding
                Funded by: General Research Fund, Research Grants Council of Hong Kong;
                Award ID: 14106019
                Funded by: Direct Grant for Research, the Chinese University of Hong Kong;
                Award ID: 2019.033
                Categories
                Subject: Original Research
                Subject: 1506
                Custom metadata
                special-feature unlocked

                Keywords: stroke,risk factors,atherosclerosis,prospective studies
                Data availability:
                Keywords: stroke, risk factors, atherosclerosis, prospective studies

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