Risk Factors For Recurrent Stroke Research Articles

Genetic and clinical risk factors for stroke recurrence with different impact by assessment age: data from the UK Biobank

Abstract Background The predictive utility of genetic risk factors added to clinical risk factors for stroke recurrence is unclear. Furthermore, whether those predictive utility change in different age groups is uncertain. This study aimed to compare the association of genetic and clinical risk factors with recurrent stroke. Methods Data were collected from 5,378 patients with a history of stroke from the UK Biobank. Cox proportional hazards regression models were used to assess the associations of genetic, demographic, lifestyle, and comorbidity risk factors with stroke recurrence, both in overall and three age-based groups. Results Over a median follow-up of 11.5 (interquartile range [IQR] 10.6–12.3) years, 417 patients had recurrent stroke. The hazard ratio (HR) for recurrent stroke was most pronounced for diabetes mellitus (HR 2.28, 95% confidence interval [CI] 1.83-2.86). Additionally, current smoking, hypertension, age, and polygenic risk score for ischemic stroke (stroke PRS) were also significantly associated with recurrent stroke. Based on concordance index (C-index, 95% CI), the strongest predictors were diabetes mellitus (0.578, 0.556-0.599) followed by age, hypertension and stroke PRS. However, the stroke PRS (0.577, 0.527-0.627) was the strongest predictor in the younger 1/3 patient group (median age 54, IQR 50-57). In addition to demographic, lifestyle, and comorbidity risk factors, genetic risk factor improved C-index of the prediction model from 0.640 (0.592-0.688) to 0.652 (0.602-0.703) in the younger group. Conclusions Recurrent stroke is significantly associated with genetic and clinical risk factors. Genetic risk factor enhances the predictive model`s accuracy, particularly in younger patients.Prediction of stroke recurrence

Risk factors for carotid endarterectomy in the early period of stroke

The OBJECTIVE was to identify significant risk factors of complications after carotid endarterectomy in the acute period of ischemic stroke, thus improving the outcomes of surgical treatment of symptomatic internal carotid artery stenosis.METHODS AND MATERIALS. The results of treatment of 776 patients after carotid endarterectomy in the acute period of stroke operated in the State Budgetary Institution of Tuberculosis «Regional Clinical Hospital № 2» were subjected to the factor analysis. catamnesis of the disease was traced for at least one year from the surgical intervention.RESULTS. Repeated ispilatory stroke occurred in 13 patients. Significant factors were tortuosity of the target artery (OR, 6.94; 95 % cI=2.21–21.86; p=0.003), aneurysm in the tortuosity zone (OR, 138.5; 95 % cI=11.6–1643.1; p=0.001), the presence of an electric cardiac pacemaker in the patient (OR, 31.71; 95 % cI=2.69–373.84; p=0.05), and need for IcA resection (OR, 6.83; 95 % cI=2.1–21.48; p=0.004). The risk factor for contralateral stroke in the early postoperative period was the use of a temporary intraluminal shunt (OR – 35.86; 95 % cI=2.17–592.92; p=0.05). Tortuosity of the target artery (OR – 4.6; 95 % cI=1.1–18.3; p=0.017), the need for IcA resection and in the presence of complicated atherosclerotic plaque in the reconstruction area (OR – 6.84; 95 % cI=1.89–24.85; p=0.01) turned out to be the sig nificant risk of death in the immediate postoperative period.CONCLUSIONS. Significant risk factors for recurrent stroke and death after carotid endarterectomy performed in the acute period of stroke were the tortuosity of the target artery, an aneurysm in the tortuosity zone, the presence of an electric cardiac pacemaker in the patient and the need for IcA resection in the presence of complicated atherosclerotic plaque in the reconstruction zone. The only risk factor for contralateral stroke in the early postoperative period was the use of a temporary intraluminal shunt. Further large trials are needed to clarify the obtained results.

Associated Demographic Factors for the Recurrence and Prognosis of Stroke Patients within a Multi-Ethnic Asian Population.

There is a paucity of studies investigating the outcomes amongst Asian stroke patients. Identifying subgroups of stroke patients at risk of poorer outcomes could identify patients who would benefit from targeted interventions. Therefore, the aim of this study was to identify which ischemic stroke patients at high risk of recurrent events and mortality. This cohort study adhered to STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines. We obtained data from the Singapore Stroke Registry (SSR) from 2005 to 2016 and cross referenced to the Death Registry, Myocardial Infarction Registry. Outcome measures included recurrent stroke, acute myocardial infarction (AMI), all-cause and stroke-related deaths. Multivariable Cox proportional hazards regression models were performed to determine risk factors for recurrent stroke, AMI, all-cause and stroke-related deaths. A total of 64,915 patients (6,705 young, and 58,210 older) were included in our analysis. Older stroke patients were found to have an increased risk of recurrent stroke (HR = 1.21, 95%CI: 1.12-1.30), AMI (HR = 1.73, 95%CI: 1.54-1.95), all-cause death (HR = 2.49, 95%CI: 2.34-2.64) and stroke-related death (HR = 176, 95%CI: 1.61-1.92). Amongst young stroke patients, males were at increased risk for recurrent stroke (HR = 1.18, 95%CI: 1.01-1.39) and AMI (HR = 1.41, 95%CI: 1.08-1.83), but at reduced risk for all-cause (HR = 0.78, 95%CI: 0.69-0.89) and stroke-related death (HR = 0.79, 95%CI: 0.67-0.94). Ethnicity appeared to influence outcomes, with Malay patients at increased risk of recurrent stroke (HR = 1.37, 95%CI: 1.14-1.65), AMI (HR = 2.45, 95%CI: 1.87-3.22), all-cause (HR = 1.43, 95%CI: 1.24-1.66) and stroke-related deaths (HR = 1.34, 95%CI: 1.09-1.64). Indian patients were also at increased risk of AMI (HR = 1.96, 95%CI: 1.41-2.72). Similar findings were seen amongst the older stroke patients. This study found that older stroke patients are at risk of poorer outcomes. Within the young stroke population specifically, males were predisposed to recurrent stroke and AMI but were protected against all-cause and stroke-related deaths. Males were also at reduced risk of all-cause and stroke-related deaths in the older stroke population. Additionally, Malay and Indian patients experience poorer outcomes after first stroke. Further optimisation of risk factors targeting these high-priority populations are needed to achieve high quality care.

Synthetic data in cancer and cerebrovascular disease research: A novel approach to big data.

Synthetic datasets are artificially manufactured based on real health systems data but do not contain real patient information. We sought to validate the use of synthetic data in stroke and cancer research by conducting a comparison study of cancer patients with ischemic stroke to non-cancer patients with ischemic stroke. retrospective cohort study. We used synthetic data generated by MDClone and compared it to its original source data (i.e. real patient data from the Ottawa Hospital Data Warehouse). We compared key differences in demographics, treatment characteristics, length of stay, and costs between cancer patients with ischemic stroke and non-cancer patients with ischemic stroke. We used a binary, multivariable logistic regression model to identify risk factors for recurrent stroke in the cancer population. Using synthetic data, we found cancer patients with ischemic stroke had a lower prevalence of hypertension (52.0% in the cancer cohort vs 57.7% in the non-cancer cohort, p<0.0001), and a higher prevalence of chronic obstructive pulmonary disease (COPD: 8.5% vs 4.7%, p<0.0001), prior ischemic stroke (1.7% vs 0.1%, p<0.001), and prior venous thromboembolism (VTE: 8.2% vs 1.5%, p<0.0001). They also had a longer length of stay (8 days [IQR 3-16] vs 6 days [IQR 3-13], p = 0.011), and higher costs associated with their stroke encounters: $11,498 (IQR $4,440 -$20,668) in the cancer cohort vs $8,084 (IQR $3,947 -$16,706) in the non-cancer cohort (p = 0.0061). A multivariable logistic regression model identified 5 predictors for recurrent ischemic stroke in the cancer cohort using synthetic data; 3 of the same predictors identified using real patient data with similar effect measures. Summary statistics between synthetic and original datasets did not significantly differ, other than slight differences in the distributions of frequencies for numeric data. We demonstrated the utility of synthetic data in stroke and cancer research and provided key differences between cancer and non-cancer patients with ischemic stroke. Synthetic data is a powerful tool that can allow researchers to easily explore hypothesis generation, enable data sharing without privacy breaches, and ensure broad access to big data in a rapid, safe, and reliable fashion.

Abstract WMP39: Incorporation of Automated Robotic Transcranial Doppler to Screen for Patent Foramen Ovale and Quantify Right to Left Shunt Severity in the Evaluation of Ischemic Stroke Patients for Stroke Etiology at a Comprehensive Stroke Center

Background: Patent foramen ovale (PFO) as a source of right-left shunting (RLS) is a recognized risk factor for recurrent stroke in young patients. Current standard care for RLS diagnosis includes transthoracic echocardiography (TTE), transesophageal echocardiography (TEE) and manual transcranial Doppler (TCD) which have disadvantages. The purpose of this retrospective review is to evaluate incorporation of an automated robotic TCD (rTCD) into the standard evaluation for RLS as cause of stroke, as prior studies have indicated higher sensitivity and quantification of RLS size to direct cardiology referral for potential PFO closure. Methods: Between Dec 2021-Oct 2022, 200 stroke patients age &lt;65 were included in this retrospective review. Average age was 55.7 ± 11.1 yrs. All patients had standard TTE and an rTCD (NovaSignal) with saline bubble injection at rest and Valsalva strain for assessment of RLS performed by echo and ultrasound technicians. Neurologists read results, including RLS shunt severity using the Spencer Shunt Grading scale (0-5), where Grade 3-5 is considered large. Results: The rate of positive RLS shunt using rTCD was 55.5% (n=111), of which 23.5% (n=47) were Spencer grade 3+ or higher. No bone window rate was 8.5% (n=17), which is lower than reported manual TCD rates. There were no rTCD RLS shunt negative patients who had a positive TTE or TEE. Of patients who had positive rTCD (n=14) and TTE with bubble, only 5 TTE’s were positive (35.7% sensitivity). Of rTCD positive patients (n=23) who also had TEE with bubble, only 11 were positive (48% sensitivity). And of 15 rTCD Grade 3+ RLS, only 11 TEE with bubble were positive (73% sensitivity). Conclusion: We successfully replaced rTCD for TTE with bubble to screen for RLS on patients who were admitted with a stroke or TIA, with the following advantages. Non-TCD technicians could be trained to perform the tests with accuracy. rTCD was more sensitive in detecting RLS than TTE with bubble. Quantification of RLS severity identified stroke patients with potentially higher risk of recurrence, prioritized to more aggressive medical management and cardiology referral for TEE and potential PFO closure.

Exploring the Chagas Disease-Stroke “Connection”: Findings from a Large Multicenter Study

Introduction: Strokes are traditionally attributed to risk factors like aging, hypertension, diabetes, and atherosclerosis. Chagas disease has emerged as an important risk factor for stroke in Latin American. Our study aims at describing the largest cohort of patients with Chagas disease and ischemic stroke and determining variables associated with stroke recurrence and cardioembolic cause. Methods: This study is the result of a national multicenter cohort study conducted in Brazil. The study spanned from January 2009 to December 2016 and involved a comprehensive retrospective analysis of medical records of patients with both Chagas disease and stroke. This cohort comprised 499 individuals from diverse Brazilian regions, focusing on vascular risk factors and the epidemiological variables associated with Chagas disease and stroke. Results: Our findings underscore the significant prevalence of traditional vascular risk factors among Chagas disease patients who had stroke. 81% of patients had hypertension, 56% dyslipidemia, and 25% diabetes. We observed a 29.7% recurrence rate, especially within the cardioembolic subgroup. 56% of the patients had embolic stroke of undetermined source (ESUS). Specific electrocardiography abnormalities were associated with an increased risk of cardioembolic etiology (with three altered results increasing 81 fold the chance of the stroke being of cardioembolic nature). Age emerged as a protective factor (OR: 0.98, 95% confidence interval [CI]: 0.970–0.997) against cardioembolic etiology. Anticoagulation therapy was associated with reduced risk (OR: 0.221, 95% CI 0.104–0.472), highlighting the importance of accurate etiological classification. Conversely, female gender (OR: 1.83, 95% CI: 1.039–3.249) emerged as a significant risk factor for stroke recurrence. Conclusion: This study significantly advances our epidemiological understanding of the intersection between Chagas disease and stroke. It emphasizes the critical need for extensive epidemiological investigations, a deeper comprehension of stroke recurrence determinants, and accurate etiological classification to reduce the ESUS population. Our findings have substantial clinical implications, suggesting the need of control of vascular risk factors and comorbidities and hold promise for improving patient care and reducing the burden of Chagas disease and stroke worldwide.

An interpretable machine learning model for stroke recurrence in patients with symptomatic intracranial atherosclerotic arterial stenosis.

Symptomatic intracranial atherosclerotic stenosis (SICAS) is the most common etiology of ischemic stroke and one of the main causes of high stroke recurrence. The recurrence of stroke is closely related to the prognosis of ischemic stroke. This study aims to develop a machine learning model based on high-resolution vessel wall imaging (HR-VWI) to predict the risk of stroke recurrence in SICAS. This study retrospectively collected data from 180 SICAS stroke patients treated at the hospital between 2020.01 and 2022.01. Relevant imaging and clinical data were collected, and follow-up was conducted. The dataset was divided into a training set and a validation set in a ratio of 7:3. We employed the least absolute shrinkage and selection operator (LASSO) regression to perform a selection on the baseline data, laboratory tests, and neuroimaging data generated by HR-VWI scans collected from the training set. Finally, five machine learning techniques, including logistic regression model (LR), support vector machine (SVM), Gaussian naive Bayes (GNB), Complement naive Bayes (CNB), and k-nearest neighbors algorithm (kNN), were employed to develop a predictive model for stroke recurrence. Shapley Additive Explanation (SHAP) was used to provide visualization and interpretation for each patient. The model's effectiveness was evaluated using average accuracy, sensitivity, specificity, precision, f1 score, PR curve, calibration curve, and decision curve analysis. LASSO analysis revealed that "history of hypertension," "homocysteine level," "NWI value," "stenosis rate," "intracranial hemorrhage," "positive remodeling," and "enhancement grade" were independent risk factors for stroke recurrence in SICAS patients. In 10-fold cross-validation, the area under the curve (AUC) ranged from 0.813 to 0.912 in ROC curve analysis. The area under the precision-recall curve (AUPRC) ranged from 0.655 to 0.833, with the Gaussian Naive Bayes (GNB) model exhibiting the best ability to predict stroke recurrence in SICAS. SHAP analysis provided interpretability for the machine learning model and revealed essential factors related to the risk of stroke recurrence in SICAS. A precise machine learning-based prediction model for stroke recurrence in SICAS has been established to assist clinical practitioners in making clinical decisions and implementing personalized treatment measures.

The effect of educational level on the recurrence rate and number of episodes of stroke in stroke survivors

ObjectivesThis study aimed to assess the influence of educational level on the recurrence rate and number of stroke episodes in stroke survivors. Materials and methodsFor this cross-sectional study, information regarding patient characteristics, medical history, ability to perform activities of daily living, level of disability, number of episodes, and stroke recurrence was collected. Analyses were conducted using the chi-square test, analysis of variance, nonparametric test, Cox regression model, and the Kaplan-Meier method. ResultsOf the 696 stroke survivors enrolled in this study, the average stroke recurrence rate was 20.83 %, and the recurrence rates in patients with primary (or lower), secondary, and university (or higher) education were 26.58, 19.54 and 14.29 %, respectively. Patients with primary (or lower) or secondary education had a higher risk for stroke recurrence than those with a university education or higher. We found that the recurrence rate 10 years after an initial stroke was higher than that after 5 years. Moreover, there was a statistically significant difference in the cumulative recurrence rate among the three groups (χ2 = 9.36, P < 0.05). Lastly, the proportions of the number of stroke episodes differed between the various education level groups (P < 0.05). ConclusionsA lower educational level was shown to be a risk factor for stroke recurrence and education levels have an impact on the number of stroke episodes. Our results suggest that is necessary to strengthen post-stroke management and rehabilitation interventions for patients with low educational levels.

Association of plaque characteristics with long-term stroke recurrence in patients with intracranial atherosclerotic disease: a 3D high-resolution MRI-based cohort study

ObjectivesTo evaluate the predictive ability of plaque characteristics for long-term stroke recurrence among patients with symptomatic intracranial atherosclerotic disease (ICAD).MethodsThis cohort study included 132 patients with acute ischemic stroke (AIS) attributed to ICAD who were recruited between July 2017 and December 2020 and followed until stroke recurrence or December 2021. Plaque surface irregularity, degree of stenosis, plaque burden, remodeling ratio, enhancement ratio, and intraplaque hemorrhage were assessed with 3-dimensional high-resolution magnetic resonance vessel wall imaging (3D HR-MRI). Data were analyzed using Cox models, receiver operating characteristic (ROC) curves, and Kaplan–Meier survival analysis.ResultsOf the 132 patients, during a median follow-up of 2.8 years, stroke recurrence occurred in 35 patients. The multivariable-adjusted hazard ratio (95% confidence interval) of stroke recurrence was 3.15 (1.34–7.42) per 10% increase in plaque burden and 2.17 (1.27–3.70) for enhancement ratio. The area under the curve (AUC) to predict stroke recurrence was 0.725 (95% CI 0.629–0.822) for plaque burden, 0.692 (95% CI 0.593–0.792) for enhancement ratio, and only 0.595 (95% CI 0.492–0.699) for the Essen stroke risk score. The Kaplan–Meier survival analysis further demonstrated significant differences in survival of free recurrent stroke between patients with plaque burden or enhancement ratio below and above the optimum cut-offs (both p < 0.001).ConclusionHigher plaque burden and enhancement ratio are independent risk factors for long-term stroke recurrence among patients with symptomatic ICAD, and valuable imaging markers for predicting and stratifying risk of stroke recurrence.Clinical relevance statementIn patients with symptomatic ICAD, the results of this high-resolution magnetic resonance vessel wall imaging study have potential implications for optimal management of intracranial plaques and secondary prevention of stroke recurrence based on plaque burden and enhancement ratio.Key Points• Identification of intracranial plaque characteristics responsible for stroke recurrence is essential to preventing stroke recurrence in patients with symptomatic intracranial atherosclerotic disease.• Higher plaque burden and enhancement ratio are independent risk factors for stroke recurrence.• Plaque burden and enhancement ratio are valuable imaging markers in the prediction and stratification of the risk of stroke recurrence.

Plaque enhancement predicts recurrence in acute ischemic stroke patients with large artery intracranial atherosclerosis

BackgroundThe association between the degree of plaque enhancement and ischemic brain stroke recurrence remains unclear. We aimed to establish models to predict plaque enhancement and stroke recurrence. MethodsSeventy-eight participants with acute ischemic brain stroke due to intracranial arterial stenosis were recruited and divided into high enhancement (HE) and non-HE groups. The relationship between imaging characteristics (degree of stenosis, minimal lumen area, intraplaque hemorrhage, and plaque burden) and the degree of plaque contrast enhancement was analyzed. Inflammatory cytokine expression was examined by flow cytometry. Independent predictors of stroke recurrence were investigated via multivariate Cox proportional hazards regression analysis. Nomogram was used to construct a prediction model. Harrell's concordance indices (c-indices) and calibration curves were used to assess the discrimination of the nomogram. A risk prediction nomogram for prognosis was constructed. ResultsThirty-three participants were assigned to the HE group and 45 to the non-HE group. The degree of stenosis and plaque burden in the HE group was higher than that in the non-HE group (P<0.05). Multiple linear regression analysis showed the degree of stenosis was associated with HE (β=0.513; P=0.000). After adjusting for confounding factors, age (HR=1.115; 95%CI=1.034–1.203, P=0.005) and HE plaques (HR=10.457; 95%CI=1.176–93.018; P=0.035) were independent risk factors of stroke recurrence, whereas cytokine levels were not statistically significant between two group. ConclusionsHE of intracranial atherosclerosis plaques is an independent factor for ischemic brain stroke recurrence.

Risk factors for stroke recurrence in young patients with first-ever ischemic stroke: A meta-analysis.

At present, the incidence rate of ischemic stroke in young people is increasing yearly, and the age of onset is increasingly young. Therefore, primary and secondary prevention of ischemic stroke in young people, especially secondary prevention, is particularly crucial. We aimed to comprehensively evaluate risk factors for stroke recurrence in first-ever young ischemic stroke (YIS) patients. The meta-analysis was used to quantitatively analyze the research results on risk factors for stroke recurrence in first-ever YIS patients both domestically and internationally. Stata12.0 software was used for heterogeneity testing, publication bias analysis, sensitivity analysis, and the calculation of combined odds ratios and 95% confidence intervals. The odds ratio (OR) values of the relationship between hypertension and hyperlipidemia and recurrence of first-ever YIS were 1.54 (1.05-2.26) and 1.12 (1.00-1.25), respectively. The OR values of male sex, type 2 diabetes, smoking, drinking and YIS recurrence were 1.66 (0.98-2.79), 1.01 (0.64-1.59), 1.21 (0.83-1.76), and 1.28 (0.82-2.53), respectively. The relationship between male sex, type 2 diabetes, smoking, drinking and YIS recurrence was ambiguous. Hypertension and hyperlipidemia are important risk factors for stroke recurrence in first-ever YIS patients, and active intervention should be taken.

Impact of cerebral collateral flow on stroke outcomes after carotid stenting.

Internal carotid artery stenosis is a main contributor to recurrent ischemic stroke. This study aimed to evaluate associations between recurrent stroke and changes in prestenting flow direction in the primary collaterals or both primary and secondary collaterals, and the potential interaction between extra- and intracranial arteries. This longitudinal study recruited stroke patients without intracranial stenosis who underwent right-side carotid stenting between 2011 and 2019. The main study outcome was recurrent stroke. Predictive factors were anterior circulation flow direction change (ACFDC), posterior circulation flow direction change, and reversal of ophthalmic artery/leptomeningeal anastomosis (ROALA) detected by transcranial color-coded duplex (TCCD) before carotid stenting. Patient follow-up was 9 years. Risk factors for recurrent stroke were identified by Kaplan-Meier plot and Cox regression analyses. A total of 234 patients (mean age 70.88 ± 10.3 years, 86.32% male) were included, and 115 had recurrent stroke. Kaplan-Meier plot showed that patients with left ACFDC and ROALA had worse outcomes than those with ACFDC only, while patients with left ACFDC had worse outcome than those with right ACFDC (both p < 0.001). Cox regression analysis showed that recurrent stoke was associated with ACFDC at right (hazard ratio [95% CI]: 20.988 [2.549-172.790], p < 0.01), left (151.441 [20.100-1140.993], p < 0.001), and both sides (144.889 [19.089-1099.710], p < 0.001). Anterior circulation flow direction change is significantly associated with recurrent stroke in patients with unilateral carotid stenosis. Patients with ACFDC and ROALA together have worse outcomes compared to those with ACFDC only. Prestenting TCCD images help provide definitive information to predict outcomes after carotid stenting.

Synchronous multimode ultrasound for assessing right-to-left shunt: a prospective clinical study.

Right-to-left shunt (RLS) is associated with several conditions and causes morbidity. In this study, we aimed to evaluate the effectiveness of synchronous multimode ultrasonography in detecting RLS. We prospectively enrolled 423 patients with high clinical suspicion of RLS and divided them into the contrast transcranial Doppler (cTCD) group and synchronous multimode ultrasound group, in which both cTCD and contrast transthoracic echocardiography (cTTE) were performed during the same process of contrast-enhanced ultrasound imaging. The simultaneous test results were compared with those of cTCD alone. The positive rates of grade II (22.0%:10.0%) and III (12.7%:10.8%) shunts and the total positive rate (82.1748%) in the synchronous multimode ultrasound group were higher than those in the cTCD alone group. Among patients with RLS grade I in the synchronous multimode ultrasound group, 23 had RLS grade I in cTCD but grade 0 in synchronous cTTE, whereas four had grade I in cTCD but grade 0 in synchronous cTTE. Among patients with RLS grade II in the synchronous multimode ultrasound group, 28 had RLS grade I in cTCD but grade II in synchronous cTTE. Among patients with RLS grade III in the synchronous multimode ultrasound group, four had RLS grade I in cTCD but grade III in synchronous cTTE. Synchronous multimode ultrasound had a sensitivity of 87.5% and specificity of 60.6% in the patent foramen ovale (PFO) diagnosis. Binary logistic regression analyses showed that age (odds ratio [OR] = 1.041) and risk of paradoxical embolism score ≥ 7 (OR = 7.798) were risk factors for stroke recurrence, whereas antiplatelets (OR = 0.590) and PFO closure with antiplatelets (OR = 0.109) were protective factors. Synchronous multimodal ultrasound significantly improves the detection rate and test efficiency, quantifies RLS more accurately, and reduces testing risks and medical costs. We conclude that synchronous multimodal ultrasound has significant potential for clinical applications.

Genetically-Determined LDL Negatively Impacts Clinical Evolution of Ischemic Stroke Survivors (S3.003)

<h3>Objective:</h3> We aim to study the contribution of genetically-determined lipid levels to the clinical trajectories of stroke survivors. <h3>Background:</h3> Ischemic Stroke survivors are at high risk of stroke recurrence. Understanding the genetic risk factors for stroke recurrence will help guide future prevention strategies. <h3>Design/Methods:</h3> We analyzed clinical and genetic data from the Vitamin Intervention Stroke Prevention (VISP) clinical trial, which examined high-dose vitamins in stroke survivors. Genetic susceptibility to increased LDL-c was modeled through a polygenic risk score built with genetic data on 38 known genetic risk variants for LDL-cholesterol (variants influencing other lipid traits were excluded). We divided the LDL-related polygenic risk score into 0–20, 20–80, and 80–100 percentile categories labeled as low, intermediate and high genetic predisposition to high LDL. We fitted multivariable (adjusting for age, sex, vascular risk factors, and statin treatment) Cox proportional hazards and logistic regression models to test whether higher polygenic risk for elevated LDL-c was associated with observed LDL-c, ischemic stroke recurrence, and composite risk of ischemic stroke and myocardial infarction. <h3>Results:</h3> Of the 2,164 stroke survivors enrolled in VISP, 1,567 (72%) had available LDL-c and genetic data. The mean LDL in the low, intermediate and high polygenic risk categories was 114.5 (SD 2.21), 123.2 (SD 1.23), and 128.8 (SD 2.35), respectively (unadjusted p&lt;0.001). Compared to stroke survivors with low polygenic risk, intermediate (HR 1.52, 95% CI 0.91–2.54) and high (HR 2.03, 95% CI 1.14–3.61) polygenic risk groups had significantly higher stroke recurrence risk (p test-for-trend 0.01). We observed similar associations when evaluating the composite risk of stroke and myocardial infarction (all p&lt;0.05). <h3>Conclusions:</h3> A higher polygenic risk for increased LDL-c is associated with worse clinical trajectories after stroke. Further research is needed to determine whether stroke survivors with an elevated genetic risk benefit from unique care pathways with additional monitoring and treatment. <b>Disclosure:</b> An immediate family member of Mr. Wu has received personal compensation for serving as an employee of Bristol-Myers Squibb. Mr. Wu has received research support from NIH. Dr. Rivier has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Pyxis Partners. Mr. Demarais has nothing to disclose. Ms. Conlon has nothing to disclose. Dr. Renedo has nothing to disclose. Mr. Torres-Lopez has nothing to disclose. Dr. Sharma has nothing to disclose. Dr. De Havenon has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Integra. Dr. De Havenon has stock in Certus. The institution of Dr. De Havenon has received research support from NIH/NINDS. The institution of Dr. De Havenon has received research support from Regeneron Pharmaceuticals. The institution of Dr. De Havenon has received research support from AMAG Pharmaceuticals. The institution of Dr. De Havenon has received research support from AMGEN. Dr. De Havenon has received publishing royalties from a publication relating to health care. Dr. Sheth has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Ceribell. Dr. Sheth has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Zoll. Dr. Sheth has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for NControl. Dr. Sheth has received stock or an ownership interest from Astrocyte. Dr. Sheth has received stock or an ownership interest from Alva. The institution of Dr. Sheth has received research support from Biogen. The institution of Dr. Sheth has received research support from Novartis. The institution of Dr. Sheth has received research support from Bard. The institution of Dr. Sheth has received research support from Hyperfine. Dr. Sheth has received intellectual property interests from a discovery or technology relating to health care. The institution of Dr. Falcone has received research support from NIH. The institution of Dr. Falcone has received research support from AHA.

Co-existing intracranial and extracranial carotid atherosclerosis predicts large-artery atherosclerosis stroke recurrence: a single-center prospective study utilizing combined head-and-neck vessel wall imaging.

Intracranial and extracranial plaque features on high-resolution vessel wall imaging (HR-VWI) are associated with large-artery atherosclerosis (LAA) stroke recurrence. However, most studies have focused on a single vascular bed, and the prognostic value of combined intracranial and extracranial plaque features has yet to be studied. This study aimed to investigate the roles of plaque features, plaque number, and co-existing atherosclerosis in predicting stroke recurrence, utilizing combined head-and-neck HR-VWI. From September 2016 to March 2020, participants with acute LAA ischemic strokes were prospectively enrolled and underwent combined head-and-neck HR-VWI. The participants were followed for stroke recurrence for at least 12months or until a subsequent event occurred. The imaging features at baseline, including conventional and histogram plaque features, plaque number, and co-existing atherosclerosis, were evaluated. Univariable Cox regression analysis and the least absolute shrinkage and selection operator (lasso) method were used for variable screening. Multivariable Cox regression analyses were used to determine the independent risk factors of stroke recurrence. A total of 97 participants (59 ± 12years, 63 men) were followed for a median of 30.9months, and 21 participants experienced recurrent strokes. Multivariable Cox analysis identified co-existing intracranial high signal on T1-weighted fat-suppressed images (HST1) and extracranial carotid atherosclerosis (HR, 6.12; 95% CI, 2.52-14.82; p = 0.001) as an independent imaging predictor of stroke recurrence. Co-existing intracranial HST1 and extracranial carotid atherosclerosis independently predicted LAA stroke recurrence. Combined head-and-neck HR-VWI is a promising technique for atherosclerosis imaging. This prospective study using combined head-and-neck HR-VWI highlighted the necessity of both intracranial culprit plaque evaluation and multi-vascular bed assessment, adding value to the prediction of stroke recurrence. • This study highlighted the necessity of both intracranial culprit plaque evaluation and multi-vascular bed assessment, adding value to the prediction of stroke recurrence. • This prospective study using combined head-and-neck HR-VWI found co-existing intracranial HST1 and extracranial carotid atherosclerosis to be independent predictors of stroke recurrence.

A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study.

Recurrent stroke accounts for 25-30% of all preventable strokes, and this study was conducted to establish a machine learning-based clinical predictive rice idol for predicting stroke recurrence within 1 year in patients with acute ischemic stroke (AIS). A total of 645 AIS patients at The Second Affiliated Hospital of Xuzhou Medical University were screened, included and followed up for 1 year for comprehensive clinical data. Univariate and multivariate logistic regression (LR) were used to screen the risk factors of stroke recurrence. The data set was randomly divided into training set and test set according to the ratio of 7:3, and the following six prediction models were established by machine algorithm: random forest (RF), Naive Bayes model (NBC), decision tree (DT), extreme gradient boosting (XGB), gradient boosting machine (GBM) and LR. The model with the strongest prediction performance was selected by 10-fold cross-validation and receiver operating characteristic (ROC) curves, and the models were investigated for interpretability by SHAP. Finally, the models were constructed to be visualized using a web calculator. Logistic regression analysis showed that right hemisphere, homocysteine (HCY), C-reactive protein (CRP), and stroke severity (SS) were independent risk factors for the development of stroke recurrence in AIS patients. In 10-fold cross-validation, area under curve (AUC) ranked from 0.777 to 0.959. In ROC curve analysis, AUC ranged from 0.887 to 0.946. RF model has the best ability to predict stroke recurrence, and HCY has the largest contribution to the model. A web-based calculator https://mlmedicine-re-stroke2-re-stroke2-baylee.streamlitapp.com/ has been developed accordingly. This study identified four independent risk factors affecting recurrence within 1 year in stroke patients, and the constructed RF-based prediction model had good performance.

An interpretable machine learning approach for predicting 30-day readmission after stroke

BackgroundStroke is the second leading cause of death worldwide and has a significantly high recurrence rate. We aimed to identify risk factors for stroke recurrence and develop an interpretable machine learning model to predict 30-day readmissions after stroke. MethodsStroke patients deposited in electronic health records (EHRs) in Xuzhou Medical University Hospital between February 1, 2021, and November 30, 2021, were included in the study, and deceased patients were excluded. We extracted 74 features from EHRs, and the top 20 features (chi-2 value) were used to build machine learning models. 80% of the patients were used for pre-training. Subsequently, a 20% holdout dataset was used for verification. The Shapley Additive exPlanations (SHAP) method was used to explore the interpretability of the model. ResultsThe cohort included 6,558 patients, of whom the mean (SD) age was 65 (11) years, 3,926 were males (59.86 %), and 132 (2.01 %) were readmitted within 30 days. The area under the receiver operating characteristic curve (AUROC) for the optimized model was 0.80 (95 % CI 0.68–0.80). We used the SHAP method to identify the top 10 risk factors (i.e., severe carotid artery stenosis, weak, homocysteine, glycosylated hemoglobin, sex, lymphocyte percentage, neutrophilic granulocyte percentage, urine glucose, fresh cerebral infarction, and red blood cell count). The AUROC of a model with the 10 features was 0.80 (95 % CI 0.69–0.80) and was not significantly different from that of the model with 20 risk factors. ConclusionsOur methods not only showed good performance in predicting 30-day readmissions after stroke but also revealed risk factors that provided valuable insights for treatments.

Abstract 148: Genetically-Determined LDL Negatively Impacts Clinical Evolution Of Ischemic Stroke Survivors

Introduction: Ischemic Stroke survivors are at high risk of stroke recurrence. Understanding the genetic risk factors for stroke recurrence will help guide future prevention strategies. Hypothesis: Genetically-elevated LDL-cholesterol (LDL-c) negatively impact clinical trajectories after stroke, leading to higher risk of post-stroke acute vascular events. Methods: We analyzed clinical and genetic data from the Vitamin Intervention Stroke Prevention (VISP) clinical trial, which examined high-dose vitamins in stroke survivors. Genetic susceptibility to increased LDL-c was modeled through a polygenic risk score built with genetic data on 38 known genetic risk variants for LDL-cholesterol (variants influencing other lipid traits were excluded). We divided the LDL-related polygenic risk score into 0-20, 20-80, and 80-100 percentile categories labeled as low, intermediate and high genetic predisposition to high LDL. We fitted multivariable (adjusting for age, sex, vascular risk factors, and statin treatment) Cox proportional hazards and logistic regression models to test whether higher polygenic risk for elevated LDL-c was associated with observed LDL-c, ischemic stroke recurrence, and composite risk of ischemic stroke and myocardial infarction. Results: Of the 2,164 stroke survivors enrolled in VISP, 1,567 (72%) had available LDL-c and genetic data. The mean LDL in the low, intermediate and high polygenic risk categories was 114.5 (SD 2.21), 123.2 (SD 1.23), and 128.8 (SD 2.35), respectively (unadjusted p&lt;0.001). Compared to stroke survivors with low polygenic risk, those with intermediate (HR 1.52, 95% CI 0.91-2.54) and high (HR 2.03, 95% CI 1.14-3.61) polygenic risk had significantly higher risk of stroke recurrence (p test-for-trend 0.01). We observed similar associations when evaluating the composite risk of stroke and myocardial infarction (all p&lt;0.05) and when conducting these analyses using logistic regression (all p&lt;0.05). Conclusions: A higher polygenic risk for increased LDL-c is associated with worse clinical trajectories after stroke. Further research is needed to determine whether stroke survivors with an elevated genetic risk benefit from unique care pathways with additional monitoring and treatment.

Non-modifiable and modifiable factors contributing to recurrent stroke: A systematic review and meta-analysis

BackgroundThe risk factors for recurrent stroke are multi-factorial. It is important to identify risk factors contributing to recurrent stroke in order to produce effective preventive measurement. This study aims to find non-modifiable and modifiable factors contributing to recurrent stroke. MethodsA Systematic review of studies on non-modifiable and modifiable factors contributing to recurrent stroke in the PubMed, ProQuest, and EBSCO were employed to search related articles published from January 2010 to January 2021. The Pooled Hazard Ratio (PHR) of the risk factors were calculated by using fixed and random-effect models. The heterogeneity was computed by calculation of I2. Publication bias was assessed using Egger's test. All data processing and analysis were performed using STATA 16.0. ResultsModifiable risk factors contributing to recurrent stroke included ischemic heart disease (PHR = 2.78 [95% CI 1.91–6.47]), atrial fibrillation (PHR = 1.87 [95% CI 1.23–2.52]), hypertension (PHR = 1.66 [95% CI] 1.15–2.17]), and obesity (PHR = 0.85 [95% CI] 0.78–0.92]). Non-modifiable risk factor associated to recurrent stroke was older age (PHR = 1.03 [95% CI 1.02–1.04]). The heterogeneity calculation showed homogenous among studies in hypertension, obesity and older age (I2 ≤ 50%). ConclusionIschemic heart disease, atrial fibrillation, hypertension, obesity and older age contribute to recurrent stroke. Thus, prevention measurements for recurrent stroke are suggested in patients with these conditions.

January 2023 Stroke Highlights

HomeStrokeVol. 54, No. 1January 2023 Stroke Highlights No AccessResearch ArticleRequest AccessFull TextAboutView Full TextView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toNo AccessResearch ArticleRequest AccessFull TextJanuary 2023 Stroke Highlights José Rafael Romero, MD José Rafael RomeroJosé Rafael Romero https://orcid.org/0000-0002-1101-2950 Search for more papers by this author Originally published21 Dec 2022https://doi.org/10.1161/STROKEAHA.122.042016Stroke. 2023;54:4is related toCovert Brain Infarction as a Risk Factor for Stroke Recurrence in Patients With Atrial FibrillationBlood Pressure Control Targets and Risk of Cardiovascular and Cerebrovascular Events After Intracerebral HemorrhagePhysical Activity Is Inversely Associated With Severe Intracranial Stenosis in Stroke-Free Participants of NOMAS"January 2023 Stroke Highlights." Stroke, 54(1), p. 4 Previous Back to top Next FiguresReferencesRelatedDetailsRelated articlesCovert Brain Infarction as a Risk Factor for Stroke Recurrence in Patients With Atrial FibrillationDo Yeon Kim, et al. Stroke. 2023;54:87-95Blood Pressure Control Targets and Risk of Cardiovascular and Cerebrovascular Events After Intracerebral HemorrhageKay-Cheong Teo, et al. Stroke. 2023;54:78-86Physical Activity Is Inversely Associated With Severe Intracranial Stenosis in Stroke-Free Participants of NOMASDixon Yang, et al. Stroke. 2023;54:159-166 January 2023Vol 54, Issue 1 Advertisement Article InformationMetrics © 2022 American Heart Association, Inc.https://doi.org/10.1161/STROKEAHA.122.042016PMID: 36542068 Originally publishedDecember 21, 2022 PDF download Advertisement