Development of a Prognostic Tool for the Stratification of Cardiovascular Risk in Patients With Ischemic Stroke

Cardiovascular Diseases Clinical Trial

Official title:

Development of a Prognostic Tool for the Stratification of Cardiovascular Risk in Patients With Ischemic Stroke

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT04189497
• Other study ID #: 25126/03-06-19
• Status: Completed
• Start date: June 30, 2019
• Est. completion date: November 20, 2019

Study information

• Verified date: December 2019
• Source: University of Thessaly
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The availability of several high-cost strategies for the prevention of cardiovascular morbidity and mortality in patients with established cardiovascular disease highlights the necessity of reliable risk stratification of these patients. Several such prognostic models are available for patients with coronary artery disease; however, for patients with ischemic stroke, the available risk stratification schemes are very few and have several limitations.

This study aims to develop a prognostication tool to stratify the risk of cardiovascular outcomes in patients with ischemic stroke.

The development of a well-designed prognostication tool for the stratification of cardiovascular risk in patients with ischemic stroke may assist to the identification of the highest-risk patients and hence, provide useful information to clinicians and authoritative bodies when prioritizing high-cost strategies for secondary stroke prevention.

Description:

Background and rationale Patients with established cardiovascular disease are at very high risk for recurrent cardiovascular events and mortality1. Nevertheless, within this very high risk group, there is significant variation of the underlying risk with some patients being at the extreme edge of the spectrum2,3.

The identification of these patients is of utmost importance as it may have implications for management strategies such as prioritization of high-cost strategies like PCSK9 inhibitors and aggressive treatment of modifiable risk factors like arterial hypertension and dyslipidemia. Refined risk stratification may also guide treatment decisions in situations where the balance between the expected benefit and the risk of serious adverse events is borderline like in patients with high bleeding risk who need aggressive antithrombotic treatment, or patients with intracranial bleeding and an indication for antithrombotic treatment4. In addition, it may allow identify those patients who may benefit more from an intensive follow-up schedule. Finally, improved risk stratification may have a positive impact on the motivation of the patient to adhere to secondary prevention strategies.

Identification of patients at greater risk of secondary vascular events after ischaemic stroke is challenging because stroke is an etiologically heterogeneous syndrome which may be caused by a diverse set of pathophysiologically discrete diseases like atrial fibrillation (AF), small vessel disease, atherosclerosis and others5.

The CHA2DS2VASc score has been shown to predict long-term stroke outcomes in patients with ischaemic stroke, both with and without AF6-8.

The Essen Stroke Risk score (ESRS) was derived from patients with ischaemic stroke in the CAPRIE trial and was shown to stratify the 1-year risk of stroke recurrence or major vascular events9.

However, the discriminatory performance of both scores in patients with ischemic stroke was modest (c-statistic approximately 0.55 for 1-year stroke recurrence and cardiovascular events) and further refinements are required for clinical application10.

Recently, a risk stratification tool was developed among placebo-treated patients with stable ischemic heart disease and previous myocardial infarction (MI) in the TRA2°P-TIMI50 trial11. This score is an integer-based scheme which consists of 9 easily assessed clinical parameters (age, diabetes mellitus,hypertension, smoking, peripheral arterial disease, previous stroke, previous coronary bypass grafting, heart failure and renal dysfunction) and showed a strong graded relationship with the rate of the composite outcome of cardiovascular death, MI and ischaemic stroke, as well as its individual components11.

Stroke and ischaemic heart disease share many risk factors and the INTERHEART and INTERSTROKE studies have shown that the 9 or 10 common cardiovascular risk factors account for >90% of MI or stroke12-14. In this context, several risk stratification models have been introduced to predict the overall cardiovascular risk (rather than its components like myocardial infarction or stroke), mainly in the general population at the primary care level15-18. In this context, it could be hypothesized that the prognostic performance of the TRA2°P score in patients with previous MI can be extended also to patients with ischemic stroke. However, the TRA2°P score performed less accurately in our cohort of ischemic stroke patients compared to the cohort of patients with previous MI in the original publication, with the c-statistics being 0.57 and 0.67 respectively (unpublished data).

It becomes evident that the currently available schemes to predict the overall vascular risk in patients with ischemic stroke do not offer a reliable prognosis which could be incorporated in management decisions.

Objective & study implications The objective of the study is to develop a prognostication tool for the stratification of the risk of major adverse cardiovascular events (MACE) in patients with ischemic stroke regardless of the underlying etiology or pathophysiologic mechanism.

MACE will be defined as a composite of nonfatal stroke, nonfatal myocardial infarction, and cardiovascular death during the follow-up of the patient. We will assess the time-to-event since the index stroke. In addition, we will also assess multiple events, i.e events occurring after the first outcome event. Stroke will be defined as an acute episode of neurological dysfunction caused by focal or global brain vascular injury and includes ischemic stroke, hemorrhagic stroke, and undetermined stroke. This includes fatal and non-fatal strokes. In case signs and symptoms resolve <24 hours, stroke requires neuroimaging evidence of acute brain ischemia (i.e. Transient Ischemic Attack with positive neuroimaging).

Myocardial infarction will be defined as evidence of myocardial necrosis in a clinical setting consistent with acute myocardial ischemia. The diagnosis of MI requires the combination of evidence of myocardial necrosis (either changes in cardiac biomarkers or post-mortem pathological findings) and supporting information derived from the clinical presentation, electrocardiographic changes, or the results of myocardial or coronary artery imaging. Cardiovascular death includes death due to stroke, myocardial infarction, heart failure or cardiogenic shock, sudden death or any other death due to other cardiovascular causes. In addition, death due to hemorrhage will be included.

We will assess the performance (e.g. its sensitivity, specificity, accuracy, positive predictive value and negative predictive value) of different cut-off values of the score match requirements for specific clinical settings.

The development of a well-designed prognostication tool for the stratification of cardiovascular risk in patients with ischemic stroke may assist to the identification of the highest-risk patients and hence, provide useful information to clinicians and authoritative bodies when prioritizing high-cost strategies for secondary stroke prevention like PCSK9 inhibitors. The generalizability of the prognostic tool will depend on the representativeness of the population included in the database; given that the analysis will be performed in all patients with ischemic stroke regardless of the underlying pathophysiologic mechanism, generalizability of the score is expected to be wide .

Study design & study population This will be a retrospective analysis in the Athens Stroke Registry, which is a prospective registry of all patients with acute first-ever ischemic stroke admitted between 1993 and 2010 within 24 hours after stroke onset and followed up for up to 10 years. An extended set of parameters is prospectively registered for each patient including demographics, medical history, vascular risk factors, previous treatment, stroke severity at admission, laboratory results, imaging data, in-hospital treatment and medication at discharge.

Patients are followed up prospectively at the outpatient clinic at 1, 3 and 6 months after hospital discharge and yearly thereafter for up to 10 years or until death. For those patients who are unable to attend the outpatient clinic, follow-up was assessed over a telephone interview with the patient or proxies, or at the patient's residence by medical personnel. The outcomes assessed are cardiovascular and all-cause mortality, myocardial infarction, stroke recurrence and a composite cardiovascular event consisting of myocardial infarction, angina pectoris, acute heart failure, sudden cardiac death, ischaemic stroke recurrence and aortic aneurysm rupture. Death and its causes are assessed from death certificates, patients' hospital records and information from general practitioners or family physicians.

The Athens Stroke Registry has supported many research projects with high-quality publications in high-profile journals, some of them may be found here. We expect that the dataset will include all eligible patients, i.e. approximately 3500 patients with ischemic stroke. The dataset will lock the day before the initiation of the study.

Access to the data registered in the Athens Stroke Registry will be sought by the responsible parties.

Inclusion criteria All patients with acute ischemic stroke registered in the Athens Stroke registry will be included in the analysis regardless of the underlying etiology or pathophysiologic mechanism.

Exclusion criteria Patients with intracranial haemorrhage or transient ischemic attack. Primary outcome A well-validated prognostication tool for the stratification of the risk of major adverse cardiovascular events in patients with ischemic stroke regardless of the underlying etiology or the pathophysiologic mechanism of the index stroke.

Study duration and description of steps The study is expected to be completed within 18 months after its initiation.

Treatments This is a retrospective chart review analysis and as such, no treatment will be provided to study participants.

Methodology & Data Analysis The dataset will lock the day before the initiation of the study. Summaries of patient parameters and outcomes using appropriate descriptive statistics will be provided for all study variables including demographic and baseline characteristics. Mean, median, standard deviation, IQR, minimum, and maximum will be used to summarize continuous variables. Counts and percentages will be used to summarize categorical variables.

Design and development of the algorithm We will develop the prognostic tool using two research methodologies: a) classical statistical analysis based on regression approach, and b) machine learning (ML).

The overall predictive ability of the score will be measured via the area under the receiver-operating characteristic curve (AUC-ROC) generated by plotting sensitivity vs 1 − specificity. In addition, we will assess the performance (e.g. its sensitivity, specificity, accuracy, positive predictive value and negative predictive value) of different cut-off values of the score match requirements for specific clinical settings. Associations will be presented as hazard ratios (HR) with their corresponding 95% confidence intervals (95% CI).

With regard to the two analytical methodologies which will be followed:

• Classical statistical analysis based on regression We will perform multivariate stepwise regression with forward selection of covariates including demographics, medical history, vascular risk factors, previous treatment, stroke severity at admission, laboratory results, imaging data, in-hospital treatment and medication at discharge. For the multivariate analyses, the level of significance will be set at 5%. The log-odds of the final model will be used to define the coefficients in the proposed score.

• Machine learning In addition to classical statistical data analysis, also state-of-the-art Machine Learning (ML) predictive algorithms will be applied to develop a prognostic system to predict the primary outcome. Recent advances in ML have greatly helped to accelerate the progress of scientific areas such as brain-computer interfaces, computer vision, natural language processing and understanding, sentiment analysis, time series forecasting, autonomous driving, fraud detection, etc. The incorporation of ML into clinical medicine holds promise for better analysis and understanding of the data. It also holds the keys to unlocking real-time clinical decision support. Prediction is not new to medicine, but recently proposed ML algorithms can substantially improve health care delivery. In this study, we will experiment with a range of ML approaches (e.g. traditional and Convolutional Neural Networks (Deep Learning), Support Vector Machines (SVMs)] to build a robust prognostic system, capable to generalize to new and unknown inputs.

Validation

• Internal Validation Internal validation will be performed using bootstrapping and cross validation. Bootstrapping will assess the predictive ability of the model by creating copies of the datasets and recalculating AUC on these copies. Cross-validation will split the dataset in two parts (60%-40%), fits a model to one part (training dataset), and assesses its predictive ability using the other part (validation dataset).

• Validation between the two analytical methods The approach of developing the algorithm using two different analytical approached (classical statistical analysis with regression and machine learning) will allow for an indirect method of internal validation.

• External validation The developed algorithm will be externally validated in the LASTRO registry. The LASTRO registry is the ongoing, prospective registry of all patients with acute ischemic stroke admitted in the Department of Internal Medicine of the University of Thessaly at the Larissa University Hospital in Larissa, Greece. The registry was initiated in 2014 and is maintained by Prof. George Ntaios (the chief investigator of the Investigator-Initiated Study described in this document). The covariates registered in the LASTRO registry are grossly similar to the covariates registered in the Athens Stroke Registry, which will facilitate the external validation of the developed algorithm.

In addition, we will seek to externally validate the developed algorithm in other external datasets, if feasible.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 3500
• Est. completion date: November 20, 2019
• Est. primary completion date: June 30, 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 130 Years

Eligibility

Inclusion Criteria:

• All patients with acute ischemic stroke registered in the Athens Stroke registry will be included in the analysis regardless of the underlying etiology or pathophysiologic mechanism

Exclusion Criteria:

• Patients with intracranial haemorrhage or transient ischemic attack

Related Conditions & MeSH terms

• Cardiovascular Diseases
• Cardiovascular Morbidity
• Cardiovascular Risk Factor
• Ischemia
• Stroke
• Stroke, Ischemic

Locations

Country	Name	City	State
Greece	University of Thessaly	Larissa

Sponsors (1)

Lead Sponsor	Collaborator
University of Thessaly

Country where clinical trial is conducted

Greece, 

References & Publications (18)

Andersen SD, Gorst-Rasmussen A, Lip GY, Bach FW, Larsen TB. Recurrent Stroke: The Value of the CHA2DS2VASc Score and the Essen Stroke Risk Score in a Nationwide Stroke Cohort. Stroke. 2015 Sep;46(9):2491-7. doi: 10.1161/STROKEAHA.115.009912. Epub 2015 Jul 30. — View Citation

Bohula EA, Bonaca MP, Braunwald E, Aylward PE, Corbalan R, De Ferrari GM, He P, Lewis BS, Merlini PA, Murphy SA, Sabatine MS, Scirica BM, Morrow DA. Atherothrombotic Risk Stratification and the Efficacy and Safety of Vorapaxar in Patients With Stable Ischemic Heart Disease and Previous Myocardial Infarction. Circulation. 2016 Jul 26;134(4):304-13. doi: 10.1161/CIRCULATIONAHA.115.019861. — View Citation

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Dorresteijn JA, Visseren FL, Wassink AM, Gondrie MJ, Steyerberg EW, Ridker PM, Cook NR, van der Graaf Y; SMART Study Group. Development and validation of a prediction rule for recurrent vascular events based on a cohort study of patients with arterial disease: the SMART risk score. Heart. 2013 Jun;99(12):866-72. doi: 10.1136/heartjnl-2013-303640. Epub 2013 Apr 10. — View Citation

Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, May M, Brindle P. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. BMJ. 2007 Jul 21;335(7611):136. Epub 2007 Jul 5. — View Citation

Kaasenbrood L, Boekholdt SM, van der Graaf Y, Ray KK, Peters RJ, Kastelein JJ, Amarenco P, LaRosa JC, Cramer MJ, Westerink J, Kappelle LJ, de Borst GJ, Visseren FL. Distribution of Estimated 10-Year Risk of Recurrent Vascular Events and Residual Risk in a Secondary Prevention Population. Circulation. 2016 Nov 8;134(19):1419-1429. Epub 2016 Sep 28. — View Citation

Lip GY, Nieuwlaat R, Pisters R, Lane DA, Crijns HJ. 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. Chest. 2010 Feb;137(2):263-72. doi: 10.1378/chest.09-1584. Epub 2009 Sep 17. — View Citation

Ntaios G, Hart RG. Embolic Stroke. Circulation. 2017 Dec 19;136(25):2403-2405. doi: 10.1161/CIRCULATIONAHA.117.030509. — View Citation

Ntaios G, Lip GY, Makaritsis K, Papavasileiou V, Vemmou A, Koroboki E, Savvari P, Manios E, Milionis H, Vemmos K. CHADS2, CHA2S2DS2-VASc, and long-term stroke outcome in patients without atrial fibrillation. Neurology. 2013 Mar 12;80(11):1009-17. doi: 10.1212/WNL.0b013e318287281b. Epub 2013 Feb 13. — View Citation

Ntaios G, Lip GY. Difficult situations in anticoagulation after stroke: between Scylla and Charybdis. Curr Opin Neurol. 2016 Feb;29(1):42-8. doi: 10.1097/WCO.0000000000000283. Review. — View Citation

Ntaios G, Vemmos K, Lip GY, Koroboki E, Manios E, Vemmou A, Rodríguez-Campello A, Cuadrado-Godia E, Giralt-Steinhauer E, Arnao V, Caso V, Paciaroni M, Diez-Tejedor E, Fuentes B, Pérez Lucas J, Arauz A, Ameriso SF, Hawkes MA, Pertierra L, Gómez-Schneider M, Bandini F, Chavarria Cano B, Iglesias Mohedano AM, García Pastor A, Gil-Núñez A, Putaala J, Tatlisumak T, Barboza MA, Athanasakis G, Makaritsis K, Papavasileiou V. Risk Stratification for Recurrence and Mortality in Embolic Stroke of Undetermined Source. Stroke. 2016 Sep;47(9):2278-85. doi: 10.1161/STROKEAHA.116.013713. Epub 2016 Aug 9. — View Citation

O'Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H, Rao-Melacini P, Zhang X, Pais P, Agapay S, Lopez-Jaramillo P, Damasceno A, Langhorne P, McQueen MJ, Rosengren A, Dehghan M, Hankey GJ, Dans AL, Elsayed A, Avezum A, Mondo C, Diener HC, Ryglewicz D, Czlonkowska A, Pogosova N, Weimar C, Iqbal R, Diaz R, Yusoff K, Yusufali A, Oguz A, Wang X, Penaherrera E, Lanas F, Ogah OS, Ogunniyi A, Iversen HK, Malaga G, Rumboldt Z, Oveisgharan S, Al Hussain F, Magazi D, Nilanont Y, Ferguson J, Pare G, Yusuf S; INTERSTROKE investigators. Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case-control study. Lancet. 2016 Aug 20;388(10046):761-75. doi: 10.1016/S0140-6736(16)30506-2. Epub 2016 Jul 16. — View Citation

Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, Cooney MT, Corrà U, Cosyns B, Deaton C, Graham I, Hall MS, Hobbs FDR, Løchen ML, Löllgen H, Marques-Vidal P, Perk J, Prescott E, Redon J, Richter DJ, Sattar N, Smulders Y, Tiberi M, van der — View Citation

Ridker PM, Buring JE, Rifai N, Cook NR. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. JAMA. 2007 Feb 14;297(6):611-9. Erratum in: JAMA. 2007 Apr 4;297(13):1433. — View Citation

Teo KK, Dokainish H. The Emerging Epidemic of Cardiovascular Risk Factors and Atherosclerotic Disease in Developing Countries. Can J Cardiol. 2017 Mar;33(3):358-365. doi: 10.1016/j.cjca.2016.12.014. Epub 2016 Dec 24. Review. — View Citation

Weimar C, Diener HC, Alberts MJ, Steg PG, Bhatt DL, Wilson PW, Mas JL, Röther J; REduction of Atherothrombosis for Continued Health Registry Investigators. The Essen stroke risk score predicts recurrent cardiovascular events: a validation within the REduction of Atherothrombosis for Continued Health (REACH) registry. Stroke. 2009 Feb;40(2):350-4. doi: 10.1161/STROKEAHA.108.521419. Epub 2008 Nov 20. — View Citation

Woodward M, Brindle P, Tunstall-Pedoe H; SIGN group on risk estimation. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart. 2007 Feb;93(2):172-6. Epub 2006 Nov 7. — View Citation

Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004 Sep 11-17;364(9438):937-52. — View Citation

* Note: There are 18 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	A well-validated prognostication tool for the stratification of the risk of major adverse cardiovascular events in patients with ischemic stroke regardless of the underlying etiology or the pathophysiologic mechanism of the index stroke	The primary outcome of the study is to built a prognostication tool, in order to predict which stroke patients are going to have the highest risk of secondary major cardiovascular events	prognostication tool for major cardiovascular adverse events reported during the follow up period, up to 10 years