Cerebrovascular Diseases最新文献

{"title":"Detecting Atrial Fibrillation by Artificial Intelligence-Enabled Neuroimaging Examination.","authors":"Angelos Sharobeam, Mohammad Javad Shokri, Nandakishor Desai, Aravinda S Rao, Yohanna Kusuma, Marimuthu Palaniswami, Stephen M Davis, Bernard Yan","doi":"10.1159/000543042","DOIUrl":"10.1159/000543042","url":null,"abstract":"<p><strong>Introduction: </strong>Diagnosis of occult atrial fibrillation (AF) is difficult as it is often asymptomatic, leading to under-detection. Current diagnostic tests have variable limitations in feasibility and accuracy. Machine learning is gaining greater traction for clinical decision-making and may help facilitate the detection of undiagnosed AF when applied to magnetic resonance imaging (MRI). We hypothesize that a machine learning algorithm increases the accurate classification of MRIs of stroke patients into those due to AF versus large artery atherosclerosis.</p><p><strong>Methods: </strong>Stroke aetiology for each patient was determined by a review of medical records and investigations. Patients with either AF or large artery atherosclerosis were included. Patients were randomly divided into the training and validation groups (4:1). A 3D convolutional neural network (ConvNeXt) was developed to train and validate the algorithm. After training, the models were evaluated using common metrics for binary classification.</p><p><strong>Results: </strong>A total of 235 patients were analysed (97 with AF, 138 without AF). The mean age of the sample was 71.1 (SD 14.2), and 35% were female. The best discriminative performance was obtained in the 5th fold of cross-validation (AUC-ROC 0.88), and the overall model performance was 0.81 ± 0.05. The best performing metrics were precision (0.84 ± 0.08) and the F1-score (0.77 ± 0.06).</p><p><strong>Conclusion: </strong>Our machine learning algorithm has reasonable classification power in categorizing stroke patients into those with and without underlying AF. Testing in external validation datasets is critical to confirm these results.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-10"},"PeriodicalIF":2.2,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143413500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing Population-Based Radiological Brain Health in Stroke Epidemiology (APRISE): Rationale and Design.","authors":"Pooja Khatri, Heidi Sucharew, Russell P Sawyer, Vivek Khandwala, Lily Li-Li Wang, Rebecca Cornelius, Mary Gaskill-Shipley, Thomas A Tomsick, David Wang, Shantala Gangatirkar, Brady Jamal Williamson, Thomas Maloney, Paul Horn, Janice Carrozzella, Kathleen Alwell, Mary Haverbusch, Brett M Kissela, Achala Vagal","doi":"10.1159/000543431","DOIUrl":"https://doi.org/10.1159/000543431","url":null,"abstract":"<p><strong>Introduction: </strong>Approximately 20% of strokes in the United States are preceded by either a stroke or transient ischemic attack (TIA). Determining which stroke patients are at higher risk for recurrence allows for individualized, aggressive secondary stroke prevention. A comprehensive clinical decision tool, considering the full spectrum of radiological brain health\" including small vessel disease parameters, is currently lacking. Furthermore, large-scale characterization of pre-existing radiological brain health may elucidate novel phenotypes. This study aims (1) to characterize imaging manifestations of brain health at a population level, and associated demographic and clinical risk factors at the time of index stroke and (2) to create a 90-day and three-year prediction models of cerebrovascular disease recurrence (ischemic or hemorrhagic stroke) incorporating comprehensive parameters from routine clinical imaging.</p><p><strong>Methods: </strong>Our overall cohort was estimated to consist of 4250 patients hospitalized with stroke, including 525 with hemorrhagic and 3725 with ischemic/TIA subtypes, ascertained in the Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS) population of 1.4 million residents from January 1, 2015 through December 31, 2015. Among 3725 ischemic stroke/TIA patients, based on published and ongoing data collection, we estimated that approximately 16% will have a recurrent ischemic or hemorrhagic stroke over the subsequent three years. Among these, 80% were estimated to have MR imaging for review. Leveraging extensive clinical and demographic data already collected in the 2015 NIH-funded GCKNSS study, we will have obtained and centrally characterized magnetic resonance imaging (MRI), acute CT, and vascular data in patients with hospitalized stroke/TIAs. We will determine if and how pre-existing imaging parameters cluster using factor analysis, and identify associated demographic and clinical risk factors in multivariable modeling. We will develop short term (90-day) and long term (three-year) risk prediction models using the machine learning approach of random survival forest with internal validation, and perform Cox regression models as a sensitivity analysis.</p><p><strong>Conclusion: </strong>The primary outcome is recurrence defined as any stroke (ischemic or hemorrhagic) occurring after index ischemic stroke or TIA event. For index ischemic strokes, the second event must within a different vascular territory if <14 days from the index event.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-15"},"PeriodicalIF":2.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143398309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between Periodontitis and Carotid Atherosclerosis: An Updated Systematic Review and Meta-Analysis.","authors":"Fangfei Ye, Min Chen, Qun Zhou","doi":"10.1159/000543955","DOIUrl":"10.1159/000543955","url":null,"abstract":"<p><strong>Introduction: </strong>Current studies on the relationship between periodontitis and carotid atherosclerosis (CAS) remain inconclusive. This updated meta-analysis was conducted to evaluate the relevant observational studies to drive a definite conclusion.</p><p><strong>Methods: </strong>Four major databases were searched for observational studies regarding the relationship between periodontitis and CAS published up to 14 December 2023. Software STATA 14.0 was used to calculate pooled odds ratios (OR) and 95% confidence interval (CI) in random-effects model.</p><p><strong>Results: </strong>Twenty-six articles were finally included. Periodontitis was significantly associated with CAS (OR = 1.97, 95% CI = 1.64-2.36; p = 0.000), however, statistical heterogeneity among studies. Sensitivity analysis indicated our results were robust. Although publication bias was observed, OR corrected by the trim-and-fill method was still increased (OR = 1.30, 95% CI = 1.06-1.58; p = 0.000).</p><p><strong>Conclusion: </strong>The findings revealed a significant association between periodontitis and CAS. However, long-term randomized controlled trials should be conducted to identify the causality.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-10"},"PeriodicalIF":2.2,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143389939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protocol for a Systematic and Scoping Review of Emergent Motion Capture Technology for Upper Extremity Assessment in Stroke.","authors":"Jarrad Fisher, Natasha A Lannin, Craig S Anderson, Xiaoying Chen","doi":"10.1159/000543914","DOIUrl":"10.1159/000543914","url":null,"abstract":"<p><strong>Introduction: </strong>A significant proportion of stroke survivors, ranging from 50% to 88%, experience upper limb motor impairments. Traditional upper limb assessments in clinical settings rely on subjective observations, leading to inconsistencies. Motion capture (MoCap) systems offer objective, precise assessments of kinematics. This review aimed to systematically evaluate emergent MoCap technologies for upper limb assessment in stroke patients.</p><p><strong>Methods: </strong>This protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols extension for Scoping Reviews (PRISMA-ScR) and the Cochrane Handbook for Systematic Reviews of Interventions version 6.4. The review is registered with the Open Science Framework. Searches will be conducted in PubMed, Medline, CINAHL, CENTRAL, and IEEE Xplore. We will include peer-reviewed studies from 2014 to 2024, in English, focusing on adults (≥18 years) post-stroke using MoCap technologies for upper limb assessment. Two or more reviewers will independently screen, select, and extract data. A narrative synthesis will describe the evidence's quality and content.</p><p><strong>Conclusion: </strong>This review will enhance our understanding of MoCap technologies for upper limb assessment post-stroke, identifying strengths, limitations, and providing evidence-based recommendations for clinical practice and future research. It aims to bridge the gap by capturing and analysing the latest advancements and their clinical applications.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-7"},"PeriodicalIF":2.2,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143363862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coexisting Obesity and Malnutrition and its Impact on Stroke and Brain Structure: Insights from UK Biobank Study.","authors":"Yajun Li, Pan Zhang, Yingjie Xu, Jinghui Zhong, Miaomiao Hu, Wen Sun, BuChun Zhang","doi":"10.1159/000543819","DOIUrl":"10.1159/000543819","url":null,"abstract":"<p><strong>Introduction: </strong>The dual burden of malnutrition, characterized by the coexistence of malnutrition and obesity, represents a growing concern in global health. This study examines the association of combined effects of obesity and malnutrition with the risk of stroke and brain structure.</p><p><strong>Methods: </strong>Data from the UK Biobank, a large-scale population-based cohort study, were analyzed. Patients were stratified into nourished nonobese, malnourished nonobese, nourished obese, and malnourished obese. Malnutrition risk using objective scores includes the Controlling Nutritional Status (CONUT) score, Nutritional Risk Index (NRI), and Prognostic Nutritional Index (PNI). Obesity was defined as BMI ≥30. Cox proportional hazard models were used to assess the association between combined obesity and nutritional status and incident stroke. Kaplan-Meier curves for incident stroke were constructed. Linear regression models were used to evaluate the associations between combined obesity and nutritional status and brain structure.</p><p><strong>Results: </strong>A total of 409,694 participants were included in the analysis. Among them, 37,930 participants had imaging data. Kaplan-Meier curves illustrated a higher incidence of stroke in the malnourished obese group. Malnourished obese was found to increase the risk of stroke (HRCONUT 1.27, 95% CI 1.09-1.48; HRNRI 2.61, 95% CI 2.03-3.36; HRPNI 7.9, 95%CI 1.11-56.07), ischemic stroke (HRCONUT 1.29, 95% CI 1.08-1.54; HRNRI 2.8, 95% CI 2.09-3.76; HRPNI 8.43, 95% CI 1.19-59.83), and hemorrhagic stroke (HRNRI 2.53, 95% CI 1.57-4.09). Brain imaging analysis revealed associations between malnourished obese and certain structural parameters. Cerebral white matter hyperintensities may be associated with the occurrence of stroke.</p><p><strong>Conclusion: </strong>Malnourished obese is associated with the risk of stroke and brain structure parameters. Further research is needed to better understand the underlying mechanisms and develop targeted interventions for individuals with combined effects of obesity and malnutrition.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-9"},"PeriodicalIF":2.2,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143363853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neurological Deterioration after Acute Ischemic Stroke: A Common Phenomenon with Important Implications.","authors":"Jing Wang, Min Zhao, Yue Qiao, Sijie Li, Xunming Ji, Wenbo Zhao","doi":"10.1159/000543763","DOIUrl":"10.1159/000543763","url":null,"abstract":"<p><strong>Background: </strong>Neurological deterioration following acute ischemic stroke (AIS) is a common clinical phenomenon associated with poor clinical outcomes. However, neurological deterioration can be attributed to diverse mechanisms in different clinical contexts. Further, there is still a lack of standard and well-recognized definitions of neurological deterioration, which compounds the complexities and challenges of its early identification and management of neurological deterioration. As AIS becomes increasingly common, the need to address neurological deterioration after AIS in clinical practice and further improve functional outcomes is becoming more urgent.</p><p><strong>Summary: </strong>To facilitate earlier recognition and more precise interventions, in this review, we comprehensively outline the evolution of the definition of neurological deterioration, its incidence in various patient groups, and the potential underlying causes rooted in multiple pathophysiological mechanisms. We further highlight the diverse risk factors associated with neurological deterioration and provide an overview of the scientific basis and practical applications of preventative and therapeutic strategies.</p><p><strong>Key messages: </strong>Early identification and management of neurological deterioration in AIS patients is crucial but challenging due to lack of unified assessment criteria and diverse mechanisms. Standardizing definitions and developing targeted strategies based on pathological mechanisms and pharmacological profiles are needed to improve outcomes.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-16"},"PeriodicalIF":2.2,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hair Follicle Mesenchymal Stem Cells Induce Neural Regeneration and Repair after Transient Ischemic Stroke.","authors":"Chen Yang, Lei Yu, Jia Wang, Xiaokun Wang, Yuhan Yang, Ni He, Shijing Zhang, Xu Gao, Hao Tang, Chendan Zou","doi":"10.1159/000543261","DOIUrl":"10.1159/000543261","url":null,"abstract":"<p><strong>Introduction: </strong>Considering the increasing recognition of the promising characteristic of hair follicle mesenchymal stem cells (HFMSCs) as multipotential cells with differentiation capability, in this study, we sought to investigate their hitherto unexplored therapeutic potentials in a rat model of transient ischemic stroke.</p><p><strong>Methods: </strong>Rat transient ischemic stroke model was established to verify the effect of HFMSC transplantation. Behavioral experiment and triphenyltetrazolium chloride staining were used to estimate neurological outcome after HFMSC therapy. Pathological experiments were performed to investigate the therapeutic roles of HFMSCs.</p><p><strong>Results: </strong>HFMSCs inhibited neural apoptosis and promoted neural proliferation. The number of neural cells around ischemic core increased after HFMSC transplantation. Besides, the transplanted HFMSCs expressed neuron-specific marker in the penumbra. Finally, HFMSCs diminished infarct area and improved neurological scores.</p><p><strong>Conclusion: </strong>HFMSCs can improve neurological outcome via anti-apoptosis and promoting neural stem cells proliferation, highlighting their therapeutic promise for ischemic stroke treatment.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-12"},"PeriodicalIF":2.2,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perfusion Image-Aided Treatment Decision for Acute Ischemic Stroke: Validation of a Clinical Decision Support System.","authors":"Xiang Li, Chao Wei, Yuefei Wu, Xiang Gao, Jie Sun, Tianqi Xu, Chushuang Chen, Qing Yang, Mark W Parsons, Yi Huang, Jianhong Yang, Longting Lin","doi":"10.1159/000543142","DOIUrl":"10.1159/000543142","url":null,"abstract":"<p><strong>Introduction: </strong>Our collaborative team has previously developed a prognostic model for acute ischemic stroke (AIS). This model, known as the clinical decision support system (CDSS), aims to provide personalized assistance to clinicians in making treatment decisions and improving patient prognosis. The objective of this study was to externally validate the model using Chinese AIS patients.</p><p><strong>Methods: </strong>All enrolled patients arrived at the hospital within 24 h after stroke onset. The primary outcome was the likelihood of a favorable functional outcome, which was defined as a modified Rankin Scale (mRS) <2 at 90 days. The model's predictive performance was evaluated by assessing its discriminative power (area under the curve [AUC]) and calibration power (Hosmer-Lemeshow goodness-of-fit test, Brier score).</p><p><strong>Results: </strong>In the validation cohort of 298 patients, the model demonstrated a moderate discriminatory ability to predict a favorable functional outcome (mRS 0-1), with an AUC of 0.805 (95% CI, 0.756-0.849). The calibration performance of the model was assessed using the Hosmer-Lemeshow chi-squared test, yielding a value of 9.211 and a p value of 0.325, and additionally, the Brier score for the prediction of a good outcome was 0.153, further supporting the model's good calibration performance.</p><p><strong>Conclusion: </strong>The study introduces the CDSS that integrates clinical baseline data and imaging indicators of brain perfusion status. This CDSS provides clinicians with an intuitive risk assessment of different treatment strategies for AIS patients. Moreover, the CDSS highlights substantial variations in treatment outcomes among patients, suggesting that it has the potential to significantly enhance personalized treatment approaches.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-11"},"PeriodicalIF":2.2,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of Right Bundle Branch Block with Ischemic Stroke Incidence: A UK Biobank Cohort Study.","authors":"Dougho Park, Sopheak Phoung, Phoeuk Borei, Myeonghwan Bang, Seungsoo Kim, Yousin Suh, Hyoung Seop Kim, Jong Hun Kim","doi":"10.1159/000543258","DOIUrl":"10.1159/000543258","url":null,"abstract":"<p><strong>Introduction: </strong>Right bundle branch block (RBBB) is often considered benign; however, its association with ischemic stroke (IS) remains unclear. We aimed to investigate the relationship between RBBB and the incidence of IS.</p><p><strong>Methods: </strong>We conducted a retrospective cohort study using the UK Biobank database (2004-2021), which included 3,634 participants with new-onset RBBB and 3,643 matched controls. The primary outcome was the incidence of IS, while the secondary outcomes included atrial fibrillation (AF) and all-cause mortality. We applied a propensity score matching with variables such as age, sex, presence of hypertension, diabetes, dyslipidemia, and the Charlson Comorbidity Index. Subsequently, time-dependent Cox regression analyses were performed to assess the association between RBBB and the outcomes.</p><p><strong>Results: </strong>The cumulative incidence of IS was higher in the RBBB group. RBBB was independently associated with an increased risk of IS (adjusted hazard ratio [aHR], 3.57; 95% confidence interval [CI], 2.12-6.03; p < 0.001), as well as AF (aHR, 4.58; 95% CI, 3.86-5.43; p < 0.001) and all-cause mortality (aHR, 2.66; 95% CI, 2.35-3.02; p < 0.001).</p><p><strong>Conclusion: </strong>RBBB was associated with an increased risk of IS, independent of age, sex, and other comorbidities. These findings emphasize the need for careful monitoring and management of patients with RBBB to mitigate the risk of IS and other adverse outcomes. Further research is needed to elucidate the underlying mechanisms and better inform clinical management strategies for patients with RBBB.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-6"},"PeriodicalIF":2.2,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142982883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional Outcome Prediction in Japanese Patients with Nonsurgical Intracerebral Hemorrhage: The FSR ICH Score.","authors":"Takuya Kiyohara, Ryu Matsuo, Fumi Irie, Kuniyuki Nakamura, Jun Hata, Yoshinobu Wakisaka, Takanari Kitazono, Masahiro Kamouchi, Tetsuro Ago","doi":"10.1159/000543362","DOIUrl":"10.1159/000543362","url":null,"abstract":"<p><strong>Introduction: </strong>There has been limited research on predicting the functional prognosis of patients with nonsurgical intracerebral hemorrhage (ICH) from the acute stage. The aim of this study was to develop a risk prediction model for the natural course in patients with nonsurgical ICH and to evaluate its performance using a multicenter hospital-based prospective study of stroke patients in Japan.</p><p><strong>Methods: </strong>We consecutively registered a total of 1,017 patients with acute ICH (mean age, 68 years) who underwent conservative treatment and followed them up for 3 months. The study outcome was a poor functional outcome (modified Rankin Scale score, 4-6) at 3 months after ICH onset. To develop the risk prediction model for natural course in patients with nonsurgical ICH, we included the following clinical common factors assessed on admission in daily clinical practice for ICH: age, sex, medical history (hypertension, diabetes mellitus, dyslipidemia, pre-stroke dementia, previous stroke, coronary artery disease, smoking status, alcohol drinking status, oral anticoagulation, and antiplatelet medication), admission status (time from onset to admission, systolic blood pressure, diastolic blood pressure, pulse pressure, plasma glucose levels, severity of the stroke), and neuroradiologic data (ICH location, intraventricular hemorrhage, and hematoma volume). The risk prediction model for poor functional outcome was developed using logistic regression analysis. In addition, the risk prediction model was translated into a point-based simple risk score (FSR ICH score) using the approach in the Framingham Heart Study.</p><p><strong>Results: </strong>At 3 months after the ICH onset, 323 (31.8%) patients developed a poor functional outcome. Age, diabetes mellitus, pre-stroke dementia, NIHSS score on admission, intraventricular hemorrhage, and hematoma volume were included in the risk prediction model. This model demonstrated excellent discrimination (C statistic = 0.884 [95% confidence interval, 0.863-0.905]; optimism-corrected C statistic based on 200 bootstrap samples = 0.877) and calibration (Hosmer-Lemeshow goodness-of-fit test: p = 0.72). The FSR ICH score, a point-based simple risk score, also showed excellent discrimination, with a C statistic of 0.882 (95% CI: 0.861-0.903).</p><p><strong>Conclusions: </strong>We developed a new risk prediction model for 3-month poor functional outcome in patients with nonsurgical ICH using a multicenter hospital-based prospective study in Japan. The current risk prediction model has the potential to be a useful tool for estimating the natural course in patients with nonsurgical ICH, aiding in making treatment decisions, including surgical options, early formulation of rehabilitation plans, and efficient utilization of medical resources.</p>","PeriodicalId":9683,"journal":{"name":"Cerebrovascular Diseases","volume":" ","pages":"1-8"},"PeriodicalIF":2.2,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142945390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}