Dataset Information

External Validation of the ELAPSS Score for Prediction of Unruptured Intracranial Aneurysm Growth Risk.

ABSTRACT:

Background and purpose

Prediction of intracranial aneurysm growth risk can assist physicians in planning of follow-up imaging of conservatively managed unruptured intracranial aneurysms. We therefore aimed to externally validate the ELAPSS (Earlier subarachnoid hemorrhage, aneurysm Location, Age, Population, aneurysm Size and Shape) score for prediction of the risk of unruptured intracranial aneurysm growth.

Methods

From 11 international cohorts of patients ?18 years with ?1 unruptured intracranial aneurysm and ?6 months of radiological follow-up, we collected data on the predictors of the ELAPSS score, and calculated 3- and 5-year absolute growth risks according to the score. Model performance was assessed in terms of calibration (predicted versus observed risk) and discrimination (c-statistic).

Results

We included 1,072 patients with a total of 1,452 aneurysms. During 4,268 aneurysm-years of follow-up, 199 (14%) aneurysms enlarged. Calibration was comparable to that of the development cohort with the overall observed risks within the range of the expected risks. The c-statistic was 0.69 (95% confidence interval [CI], 0.64 to 0.73) at 3 years, compared to 0.72 (95% CI, 0.68 to 0.76) in the development cohort. At 5 years, the c-statistic was 0.68 (95% CI, 0.64 to 0.72), compared to 0.72 (95% CI, 0.68 to 0.75) in the development cohort.

Conclusion

s The ELAPSS score showed accurate calibration for 3- and 5-year risks of aneurysm growth and modest discrimination in our external validation cohort. This indicates that the score is externally valid and could assist patients and physicians in predicting growth of unruptured intracranial aneurysms and plan follow-up imaging accordingly.

SUBMITTER: Sanchez van Kammen M

PROVIDER: S-EPMC6780020 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Publications

External Validation of the ELAPSS Score for Prediction of Unruptured Intracranial Aneurysm Growth Risk.

Sánchez van Kammen Mayte M Greving Jacoba P JP Kuroda Satoshi S Kashiwazaki Daina D Morita Akio A Shiokawa Yoshiaki Y Kimura Toshikazu T Cognard Christophe C Januel Anne C AC Lindgren Antti A Koivisto Timo T Jääskeläinen Juha E JE Ronkainen Antti A Pyysalo Liisa L Öhman Juha J Rahi Melissa M Kuhmonen Johanna J Rinne Jaakko J Leemans Eva L EL Majoie Charles B CB Vandertop W Peter WP Verbaan Dagmar D Roos Yvo B W E M YBWEM Berg René van den RVD Boogaarts Hieronymus D HD Moudrous Walid W Wijngaard Ido R van den IRVD Hove Laura Ten LT Teo Mario M George Edward J St EJS Hackenberg Katharina A M KAM Abdulazim Amr A Etminan Nima N Rinkel Gabriël J E GJE Vergouwen Mervyn D I MDI

Journal of stroke 20190930 3

<h4>Background and purpose</h4>Prediction of intracranial aneurysm growth risk can assist physicians in planning of follow-up imaging of conservatively managed unruptured intracranial aneurysms. We therefore aimed to externally validate the ELAPSS (Earlier subarachnoid hemorrhage, aneurysm Location, Age, Population, aneurysm Size and Shape) score for prediction of the risk of unruptured intracranial aneurysm growth.<h4>Methods</h4>From 11 international cohorts of patients ≥18 years with ≥1 unrup ...[more]

PMID: 31590478

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Project description:The presence of an intracranial aneurysm is contraindicated to recombinant tissue plasminogen activator (r-tPA) treatment for acute ischemic stroke. However, it is difficult to exclude asymptomatic intracranial aneurysms by using conventional, noncontrast head computed tomography (CT), which is the only neuroimaging suggested before r-tPA. Recent case reports and series have shown that administering r-tPA to patients with a pre-existing aneurysm does not increase the bleeding risk. However, Asians are known to have a relatively higher bleeding risk, and little evidence is available regarding the risk of using r-tPA on Asian patients with intracranial aneurysms.Medical records from the Shuang Ho hospital stroke registration between July 2010 and December 2014 were retrospectively reviewed, and 144 patients received r-tPA. Unruptured intracranial aneurysms were detected using CT, or magnetic resonance or conventional angiography after r-tPA. The primary and secondary outcomes were the difference in overall intracranial hemorrhage (ICH) and symptomatic ICH after r-tPA. The differences were analyzed using Fisher's exact or Mann-Whitney U tests, and p < 0.05 was defined as the statistical significance.A total of 144 patients were reviewed, and incidental unruptured intracranial aneurysms were found in 11 of them (7.6%). No significant difference was observed in baseline demographic data between the aneurysm and nonaneurysm groups. Among patients with an unruptured aneurysm, two had giant aneurysms (7.7 and 7.4 mm, respectively). The bleeding risk was not significant different between aneurysm group (2 out of 11, 18%) with nonaneurysm group (7 out of 133, 5.3%) (p = 0.14). None of the patients with an unruptured aneurysm had symptomatic ICH, whereas one patient without an aneurysm exhibited symptomatic ICH.The presence of an unruptured intracranial aneurysm did not significantly increase the risk of overall and symptomatic ICH in Taiwanese patients after they received r-tPA.

Project description:BACKGROUND:Ruptured aneurysms, the commonest cause of nontraumatic subarachnoid hemorrhage, can be catastrophic; the mortality and morbidity of affected patients being very high. Some risk factors, such as smoking, hypertension and female sex have been identified, whereas others, such as hemodynamics, imaging, and genomics, remain unclear. Currently, no accurate model that includes all factors for predicting such rupture is available. We plan to use data from a large cohort of Chinese individuals to set up a multidimensional model for predicting risk of rupture of unruptured intracranial aneurysms (UIAs). METHODS:The China Intracranial Aneurysm Project-2 (CIAP-2) will comprise screening of a cohort of 500 patients with UIA (From CIAP-1) and focus on hemodynamic factors, high resolution magnetic resonance imaging (HRMRI) findings, genetic factors, and biomarkers. Possible risk factors for rupture of UIA, including genetic factors, biomarkers, HRMRI, and hemodynamic factors, will be analyzed. The first project of the China Intracranial Aneurysm Project (CIAP-1; chaired by the Department of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China) will prospectively collect a cohort of 5000 patients with UIA from 20 centers in China, and collect baseline information for each patient. Multidimensional data will be acquired in follow-up assessments. Statistically significant clinical features in the UIA cohort will also be analyzed and integrated into the model for predicting risk of UIA rupture. After the model has been set up, the resultant evidence-based prediction will provide a preliminary theoretical basis for treating aneurysms at high risk of rupture. DISCUSSION:This study will explore the risk of rupture of aneurysms and develop a scientific multidimensional model for predicting rupture of unruptured intracranial aneurysms. Clinical Trials registration A Study on a Multidimensional Prediction Model for Rupture Risk of Unruptured Intracranial Aneurysms (CIAP-2), NCT03133624. Registered: 16 April 2017. https://clinicaltrials.gov/ct2/show/NCT03133624.

Project description:Background and aimsThe role of statins in unruptured intracranial aneurysm (UIA) growth and rupture remains ambiguous. This study sought to determine whether atorvastatin is associated with aneurysm growth and rupture in patients harboring UIA <7 mm.MethodsThis prospective, multicenter cohort study consecutively enrolled patients with concurrent UIA <7 mm and ischemic cerebrovascular disease from four hospitals between 2016 and 2019. Baseline and follow-up patient information was recorded. Because of the strong anti-inflammatory effect of aspirin, patients using aspirin were excluded. Patients taking atorvastatin 20 mg daily were atorvastatin users. The primary and exploratory endpoints were aneurysm rupture and growth, respectively.ResultsAmong the 1087 enrolled patients, 489 (45.0%) took atorvastatin, and 598 (55%) took no atorvastatin. After a mean follow-up duration of 33.0 ± 12.5 months, six (1.2%) and five (0.8%) aneurysms ruptured in atorvastatin and non-atorvastatin groups, respectively. In the adjusted multivariate Cox analysis, UIA sized 5 to <7 mm, current smoker, and uncontrolled hypertension were associated with aneurysm rupture, whereas atorvastatin [adjusted hazard ratio (HR) 1.495, 95% confidence interval (CI) 0.417-5.356, p = 0.537] was not. Of 159 patients who had follow-up imaging, 34 (21.4%) took atorvastatin and 125 (78.6%) took no atorvastatin. Aneurysm growth occurred in five (14.7%) and 21 (16.8%) patients in atorvastatin and non-atorvastatin groups (mean follow-up: 20.2 ± 12.9 months), respectively. In the adjusted multivariate Cox analysis, UIAs sized 5 to <7 mm and uncontrolled hypertension were associated with a high growth rate; atorvastatin (adjusted HR 0.151, 95% CI 0.031-0.729, p = 0.019) was associated with a reduced growth rate.ConclusionsWe conclude atorvastatin use is associated with a reduced risk of UIA growth, whereas atorvastatin is not associated with UIA rupture.The trial registry name:: The Clinic Benefit and Risk of Oral Aspirin for Unruptured Intracranial Aneurysm Combined With Cerebral IschemiaClinical Trial Registration-URL:: http://www.clinicaltrials.gov Unique identifier:: NCT02846259.

Project description:ImportanceUnruptured intracranial aneurysms not undergoing preventive endovascular or neurosurgical treatment are often monitored radiologically to detect aneurysm growth, which is associated with an increase in risk of rupture. However, the absolute risk of aneurysm rupture after detection of growth remains unclear.ObjectiveTo determine the absolute risk of rupture of an aneurysm after detection of growth during follow-up and to develop a prediction model for rupture.Design, setting, and participantsIndividual patient data were obtained from 15 international cohorts. Patients 18 years and older who had follow-up imaging for at least 1 untreated unruptured intracranial aneurysm with growth detected at follow-up imaging and with 1 day or longer of follow-up after growth were included. Fusiform or arteriovenous malformation-related aneurysms were excluded. Of the 5166 eligible patients who had follow-up imaging for intracranial aneurysms, 4827 were excluded because no aneurysm growth was detected, and 27 were excluded because they had less than 1 day follow-up after detection of growth.ExposuresAll included aneurysms had growth, defined as 1 mm or greater increase in 1 direction at follow-up imaging.Main outcomes and measuresThe primary outcome was aneurysm rupture. The absolute risk of rupture was measured with the Kaplan-Meier estimate at 3 time points (6 months, 1 year, and 2 years) after initial growth. Cox proportional hazards regression was used to identify predictors of rupture after growth detection.ResultsA total of 312 patients were included (223 [71%] were women; mean [SD] age, 61 [12] years) with 329 aneurysms with growth. During 864 aneurysm-years of follow-up, 25 (7.6%) of these aneurysms ruptured. The absolute risk of rupture after growth was 2.9% (95% CI, 0.9-4.9) at 6 months, 4.3% (95% CI, 1.9-6.7) at 1 year, and 6.0% (95% CI, 2.9-9.1) at 2 years. In multivariable analyses, predictors of rupture were size (7 mm or larger hazard ratio, 3.1; 95% CI, 1.4-7.2), shape (irregular hazard ratio, 2.9; 95% CI, 1.3-6.5), and site (middle cerebral artery hazard ratio, 3.6; 95% CI, 0.8-16.3; anterior cerebral artery, posterior communicating artery, or posterior circulation hazard ratio, 2.8; 95% CI, 0.6-13.0). In the triple-S (size, site, shape) prediction model, the 1-year risk of rupture ranged from 2.1% to 10.6%.Conclusion and relevanceWithin 1 year after growth detection, rupture occurred in approximately 1 of 25 aneurysms. The triple-S risk prediction model can be used to estimate absolute risk of rupture for the initial period after detection of growth.

Project description:BACKGROUND:Intracranial aneurysms (IAs) are dangerous because of their potential to rupture. We previously found significant RNA expression differences in circulating neutrophils between patients with and without unruptured IAs and trained machine learning models to predict presence of IA using 40 neutrophil transcriptomes. Here, we aim to develop a predictive model for unruptured IA using neutrophil transcriptomes from a larger population and more robust machine learning methods. METHODS:Neutrophil RNA extracted from the blood of 134 patients (55 with IA, 79 IA-free controls) was subjected to next-generation RNA sequencing. In a randomly-selected training cohort (n?=?94), the Least Absolute Shrinkage and Selection Operator (LASSO) selected transcripts, from which we constructed prediction models via 4 well-established supervised machine-learning algorithms (K-Nearest Neighbors, Random Forest, and Support Vector Machines with Gaussian and cubic kernels). We tested the models in the remaining samples (n?=?40) and assessed model performance by receiver-operating-characteristic (ROC) curves. Real-time quantitative polymerase chain reaction (RT-qPCR) of 9 IA-associated genes was used to verify gene expression in a subset of 49 neutrophil RNA samples. We also examined the potential influence of demographics and comorbidities on model prediction. RESULTS:Feature selection using LASSO in the training cohort identified 37 IA-associated transcripts. Models trained using these transcripts had a maximum accuracy of 90% in the testing cohort. The testing performance across all methods had an average area under ROC curve (AUC)?=?0.97, an improvement over our previous models. The Random Forest model performed best across both training and testing cohorts. RT-qPCR confirmed expression differences in 7 of 9 genes tested. Gene ontology and IPA network analyses performed on the 37 model genes reflected dysregulated inflammation, cell signaling, and apoptosis processes. In our data, demographics and comorbidities did not affect model performance. CONCLUSIONS:We improved upon our previous IA prediction models based on circulating neutrophil transcriptomes by increasing sample size and by implementing LASSO and more robust machine learning methods. Future studies are needed to validate these models in larger cohorts and further investigate effect of covariates.

Dataset Information

External Validation of the ELAPSS Score for Prediction of Unruptured Intracranial Aneurysm Growth Risk.

Background and purpose

Methods

Results

Conclusion

Publications

External Validation of the ELAPSS Score for Prediction of Unruptured Intracranial Aneurysm Growth Risk.

Similar Datasets

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