Heterogeneity in measurement of NIHSS: a systematic review and meta-analysis.

BACKGROUND: The National Institutes of Health Stroke Scale (NIHSS) is a pivotal clinical tool used to assess patients with acute stroke. However, substantial heterogeneity in the application and interpretation of stroke scale items can occur. This systematic review aimed to elucidate heterogeneity in measuring the NIHSS. MATERIAL AND METHODS: A literature search was performed on PubMed/OVID/Cochran's CENTRAL from inception to 2023. The references of the included papers were reviewed for further eligible articles. Clinical characteristic, NIHSS values, and sources of heterogeneity were recorded. Non-human and non-English language articles were excluded. The study quality was assessed using MINORS and GRADE. Meta-analysis and meta-regression were performed using a random-effects model to explore the sources of heterogeneity. RESULTS: Twenty-one papers for a total of 818 patients (mean per study: 39 ± 37) and 9696 NIHSS examinations (median per study: 8 [CI95% 2 to 42]) were included. Motor function had a higher ICC agreement (ranging from 0.85 ["Right Leg"] to 0.90 ["Right Arm"]) compared to the remaining items (ranging from 0.58 ["Facial Palsy"] to 0.85 ["Level of consciousness commands"]. The meta-regression showed a low effect size of covariates such as language version, remote evaluation, and retrospective analysis on NIHSS items (e.g., for "Level of consciousness commands," language effect was 0.30 [CI95% 0.20 to 0.48] and for "Visual", the retrospective assessment effect was -0.27 [CI95% -0.51 to -0.03]). CONCLUSION: The NIHSS scores showed moderate to excellent inter-rater agreement, with the highest heterogeneity in non-motor function evaluation. Using a non-English version, remote evaluation and retrospective analysis had small effects in terms of heterogeneity in the NIHSS scores.

Endovascular Stroke Thrombectomy for Patients With Large Ischemic Core: A Review.

Importance: Recently, 6 randomized clinical trials-RESCUE-Japan-LIMIT (Recovery by Endovascular Salvage for Cerebral Ultra-Acute Embolism-Japan Large Ischemic Core Trial), ANGEL-ASPECT (Trial of Endovascular Therapy for Acute Ischemic Stroke With Large Infarct), SELECT2 (Trial of Endovascular Thrombectomy for Large Ischemic Strokes), TESLA (Thrombectomy for Emergent Salvage of Large Anterior Circulation Ischemic Stroke), TENSION (Endovascular Thrombectomy for Acute Ischemic Stroke With Established Large Infarct), and LASTE (Large Stroke Therapy Evaluation)-have concluded their investigations on the efficacy and safety of endovascular thrombectomy (EVT) for the treatment of patients with ischemic stroke, anterior-circulation large vessel occlusions, and large areas of ischemic changes defined as an Alberta Stroke Program Early Computed Tomography Score (ASPECTS) of 5 or less. Overall, the results appeared to be positive, with 5 of the 6 trials meeting their primary efficacy end point, and 1 trial that was a near miss. However, questions remain regarding how these trial results should be interpreted and incorporated into routine clinical practice. Observations: In this narrative review and analysis of published trials, important nuances of the available clinical data were identified, and important areas of lingering uncertainty were highlighted, including the efficacy and safety of EVT for patients with a low ASPECTS score in late treatment windows and those with large core volumes. Also emphasized was the possibly important role of advanced neuroimaging modalities such as perfusion and magnetic resonance imaging when making EVT treatment decisions for select patients with low ASPECTS scores. Conclusions and Relevance: Recent trial data provide strong evidence that EVT is safe and effective for patients with anterior, large vessel-occlusion stroke and low ASPECTS scores who present within 6 hours from stroke onset. However, patient outcomes often remain poor despite EVT treatment. The efficacy and safety of EVT for patients with low ASPECTS scores who present beyond 6 hours of stroke onset remain uncertain, and the current trial data seem too scarce to justify forgoing advanced stroke imaging during this extended time window. Furthermore, the efficacy and safety of EVT for patients with large core volumes (100 mL or greater) or M2 occlusions (ie, occlusions of the second segment of the middle cerebral artery) remain uncertain. Future research to better identify patients likely to meaningfully respond to EVT is needed to further optimize the stroke triage process and health care resource utilization.

UltraAIGenomics: Artificial Intelligence-Based Cardiovascular Disease Risk Assessment by Fusion of Ultrasound-Based Radiomics and Genomics Features for Preventive, Personalized and Precision Medicine: A Narrative Review.

Cardiovascular disease (CVD) diagnosis and treatment are challenging since symptoms appear late in the disease's progression. Despite clinical risk scores, cardiac event prediction is inadequate, and many at-risk patients are not adequately categorised by conventional risk factors alone. Integrating genomic-based biomarkers (GBBM), specifically those found in plasma and/or serum samples, along with novel non-invasive radiomic-based biomarkers (RBBM) such as plaque area and plaque burden can improve the overall specificity of CVD risk. This review proposes two hypotheses: (i) RBBM and GBBM biomarkers have a strong correlation and can be used to detect the severity of CVD and stroke precisely, and (ii) introduces a proposed artificial intelligence (AI)-based preventive, precision, and personalized ( aiP 3 ) CVD/Stroke risk model. The PRISMA search selected 246 studies for the CVD/Stroke risk. It showed that using the RBBM and GBBM biomarkers, deep learning (DL) modelscould be used for CVD/Stroke risk stratification in the aiP 3 framework. Furthermore, we present a concise overview of platelet function, complete blood count (CBC), and diagnostic methods. As part of the AI paradigm, we discuss explainability, pruning, bias, and benchmarking against previous studies and their potential impacts. The review proposes the integration of RBBM and GBBM, an innovative solution streamlined in the DL paradigm for predicting CVD/Stroke risk in the aiP 3 framework. The combination of RBBM and GBBM introduces a powerful CVD/Stroke risk assessment paradigm. aiP 3 model signifies a promising advancement in CVD/Stroke risk assessment.

Surgical Management for Primary Intracerebral Hemorrhage.

The incidence of primary intracerebral hemorrhage (ICH) is increasing, particularly in younger patients, in part, because of increased prescription of anticoagulants. The ICH incidence rate from 2016 to 2018 in the United States was nearly 79 per 100,000 person-years and as high as 367 per 100,000 person-years among those 75 years or older. Worldwide, ICH comprises 28% of all new strokes, but a higher disease burden than ischemic stroke because of its higher morbidity and mortality. While mortality seems to be decreasing, functional outcomes are not improving. After negative trials of open surgical evacuation, recent trials of medical management strategies including intensive blood pressure control and prothrombotic agents intended to reduce hematoma expansion failed to demonstrate efficacy. Concomitantly, continued interest in minimally invasive surgical approaches arose from appreciation of secondary iatrogenic injury incurred to subcortical white matter tracts from open surgical techniques. A positive trial of minimally invasive surgery for lobar hemorrhage has recently been reported, bringing new optimism and demanding a reconsideration of surgical management of ICH. In this narrative review, we summarize the landmark studies, review recent literature, and consider the outstanding questions surrounding surgical management of ICH.

Embolic Stroke of Undetermined Source: New Data and New Controversies on Cardiac Monitoring and Anticoagulation.

Embolic strokes of undetermined source (ESUS) represent 9%-25% of all ischemic strokes. Based on the suspicion that a large proportion of cardioembolic sources remain undetected among embolic stroke of undetermined source patients, it has been hypothesized that a universal approach of anticoagulation would be better than aspirin for preventing recurrent strokes. However, 4 randomized controlled trials (RCTs), with different degrees of patient selection, failed to confirm this hypothesis. In parallel, several RCTs consistently demonstrated that prolonged cardiac monitoring increased atrial fibrillation detection and anticoagulation initiation compared with usual care in patients with ESUS, and later in individuals with ischemic stroke of known cause (e.g., large or small vessel disease). However, none of these trials or subsequent meta-analyses of all available RCTs have shown a reduction in stroke recurrence associated with the use of prolonged cardiac monitoring. In this article, we review the clinical and research implications of recent RCTs of antithrombotic therapy in patients with ESUS and in high-risk populations with and without stroke, with device-detected asymptomatic atrial fibrillation.

Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review.

Background: The field of precision medicine endeavors to transform the healthcare industry by advancing individualised strategies for diagnosis, treatment modalities, and predictive assessments. This is achieved by utilizing extensive multidimensional biological datasets encompassing diverse components, such as an individual's genetic makeup, functional attributes, and environmental influences. Artificial intelligence (AI) systems, namely machine learning (ML) and deep learning (DL), have exhibited remarkable efficacy in predicting the potential occurrence of specific cancers and cardiovascular diseases (CVD). Methods: We conducted a comprehensive scoping review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. Our search strategy involved combining key terms related to CVD and AI using the Boolean operator AND. In August 2023, we conducted an extensive search across reputable scholarly databases including Google Scholar, PubMed, IEEE Xplore, ScienceDirect, Web of Science, and arXiv to gather relevant academic literature on personalised medicine for CVD. Subsequently, in January 2024, we extended our search to include internet search engines such as Google and various CVD websites. These searches were further updated in March 2024. Additionally, we reviewed the reference lists of the final selected research articles to identify any additional relevant literature. Findings: A total of 2307 records were identified during the process of conducting the study, consisting of 564 entries from external sites like arXiv and 1743 records found through database searching. After 430 duplicate articles were eliminated, 1877 items that remained were screened for relevancy. In this stage, 1241 articles remained for additional review after 158 irrelevant articles and 478 articles with insufficient data were removed. 355 articles were eliminated for being inaccessible, 726 for being written in a language other than English, and 281 for not having undergone peer review. Consequently, 121 studies were deemed suitable for inclusion in the qualitative synthesis. At the intersection of CVD, AI, and precision medicine, we found important scientific findings in our scoping review. Intricate pattern extraction from large, complicated genetic datasets is a skill that AI algorithms excel at, allowing for accurate disease diagnosis and CVD risk prediction. Furthermore, these investigations have uncovered unique genetic biomarkers linked to CVD, providing insight into the workings of the disease and possible treatment avenues. The construction of more precise predictive models and personalised treatment plans based on the genetic profiles of individual patients has been made possible by the revolutionary advancement of CVD risk assessment through the integration of AI and genomics. Interpretation: The systematic methodology employed ensured the thorough examination of available literature and the inclusion of relevant studies, contributing to the robustness and reliability of the study's findings. Our analysis stresses a crucial point in terms of the adaptability and versatility of AI solutions. AI algorithms designed in non-CVD domains such as in oncology, often include ideas and tactics that might be modified to address cardiovascular problems. Funding: No funding received.

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a ~ 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models.

Sex discrepancies in the population incidence of stroke and hemorrhage related to atrial fibrillation or flutter.

INTRODUCTION: Atrial fibrillation or flutter (AF) is a well-known risk factor for ischemic stroke. While female sex has been associated with higher stroke risk among AF patients, overall sex-specific real-world burdens of AF-related strokes and hemorrhages are unknown. METHODS: The 2016-2020 National Inpatient Sample was queried for hospitalizations, morbidity, and mortality due to AF-related ischemic strokes and bleeds. Patient demographic information, vascular risk factors, comorbidities, and stroke characteristics were extracted using ICD-10 codes. Overall incidences were calculated using total population estimates provided by the United States Census Bureau, and relative risk was calculated by comparing annual incidences between men and women. RESULTS: 2,420,870 ischemic stroke hospitalizations were identified; 542,635 (22.4%) were associated with AF. Overall, women had similar risk of hospitalization due to AF-related ischemic strokes compared to men; however, women had a higher risk of morbidity and mortality (RR 1.13 and 1.17, respectively; both p<0.001). In contrast, women had lower incidences of hospitalization, morbidity, and mortality due to AF-related bleeds (RR 0.82, 0.94, and 0.74, respectively; all p<0.001). Among patients with AF-related ischemic strokes, women had lower rates of anticoagulation use, higher rates of large vessel occlusion, and higher stroke severity (all p<0.001). These trends persisted among patients 80 years or older (all p<0.001). CONCLUSION: Women in the United States have higher incidences of morbidity and mortality from AF-related ischemic strokes than men. Future studies should investigate strategies to reduce morbidity and mortality due to AF-related strokes in women.

The impact of sex on stroke care: From epidemiology to outcome.

BACKGROUND: Carotid stenosis and atrial fibrillation are key risk factors for development of hemispheric strokes. In this review we aim to identify sex-specific differences in the pathophysiology and treatment of these risk factors and areas for future study. KEY FINDINGS: Women are underrepresented in research studies of stroke in patients with carotid disease and atrial fibrillation. However, key differences have been found between men and women that suggest that the development of carotid disease and atrial fibrillation occur at later stages of life and are associated with higher severity of stroke. Some treatments, including surgical treatment, seem to have different rates of efficacy and women and women are at higher risk of surgical complications. This suggests that treatment recommendations may need to be sex specific. CONCLUSION: Efforts should be made to address research and treatment gaps in women with stroke risk factors. This may lead to the development of sex-specific recommendations for stroke prevention and treatment.

Optimal Angiographic Goal and Number of Passes for Octogenarians Undergoing Endovascular Stroke Thrombectomy.

BACKGROUND: The optimal recanalization goal and number of endovascular thrombectomy (EVT) passes for elderly patients with large vessel occlusion strokes is unclear. METHODS: Consecutive patients 80 years or older undergoing EVT were identified from 2016 to 2022 at a single center. Clinical information, procedural details, and modified treatment in cerebral ischemia (mTICI) scores were collected. Primary outcome was modified Rankin scale (mRS) at 90 days. Bivariate and multivariable analyses were conducted to assess associations between mTICI scores, EVT passes, and 90-day outcomes. RESULTS: One hundred twenty-six patients were identified. At 90 days, mTICI 2b recanalization resulted in high rates of poor outcomes (8.7% functional independence and 60.9% mortality) not significantly different from mTICI 0, 1 or 2a (median mRS 6 vs. 6, P = 0.61). Complete recanalization (mTICI 2c or 3) led to significantly better mRS outcomes at 90 days compared to mTICI 2b (median mRS 4 vs. 6, adjusted P = 0.038), with 26.8% functional independence and 37.8% mortality. In multivariable analysis, complete recanalization was significantly associated with better 90-day outcomes than mTICI 2b or lower recanalization (odds ratio 4.24 [95% Confidence interval 1.46-12.3]; P = 0.002), while the number of passes was not independently associated with worse outcomes (P = 0.98). CONCLUSIONS: For octogenarians, mTICI 2b recanalization yields limited clinical benefit and results in poor 90-day outcomes. In contrast, complete recanalization is independently associated with significantly better outcomes. Thus, once the decision is made to pursue EVT in the elderly, mTICI 2c or better recanalization should be the angiographic goal. Providers should not withhold thrombectomy passes based on age alone.

Transcarotid Arterial Revascularization of Symptomatic Internal Carotid Artery Disease: A Systematic Review and Study-Level Meta-Analysis.

BACKGROUND: Transcarotid artery revascularization (TCAR) is an interventional therapy for symptomatic internal carotid artery disease. Currently, the utilization of TCAR is contentious due to limited evidence. In this study, we evaluate the safety and efficacy of TCAR in patients with symptomatic internal carotid artery disease compared with carotid endarterectomy (CEA) and carotid artery stenting (CAS). METHODS: A systematic review was conducted, spanning from January 2000 to February 2023, encompassing studies that used TCAR for the treatment of symptomatic internal carotid artery disease. The primary outcomes included a 30-day stroke or transient ischemic attack, myocardial infarction, and mortality. Secondary outcomes comprised cranial nerve injury and major bleeding. Pooled odds ratios (ORs) for each outcome were calculated to compare TCAR with CEA and CAS. Furthermore, subgroup analyses were performed based on age and degree of stenosis. In addition, a sensitivity analysis was conducted by excluding the vascular quality initiative registry population. RESULTS: A total of 7 studies involving 24 246 patients were analyzed. Within this patient cohort, 4771 individuals underwent TCAR, 12 350 underwent CEA, and 7125 patients underwent CAS. Compared with CAS, TCAR was associated with a similar rate of stroke or transient ischemic attack (OR, 0.77 [95% CI, 0.33-1.82]) and myocardial infarction (OR, 1.29 [95% CI, 0.83-2.01]) but lower mortality (OR, 0.42 [95% CI, 0.22-0.81]). Compared with CEA, TCAR was associated with a higher rate of stroke or transient ischemic attack (OR, 1.26 [95% CI, 1.03-1.54]) but similar rates of myocardial infarction (OR, 0.9 [95% CI, 0.64-1.38]) and mortality (OR, 1.35 [95% CI, 0.87-2.10]). CONCLUSIONS: Although CEA has traditionally been considered superior to stenting for symptomatic carotid stenosis, TCAR may have some advantages over CAS. Prospective randomized trials comparing the 3 modalities are needed.

Apixaban to Prevent Recurrence After Cryptogenic Stroke in Patients With Atrial Cardiopathy: The ARCADIA Randomized Clinical Trial.

Importance: Atrial cardiopathy is associated with stroke in the absence of clinically apparent atrial fibrillation. It is unknown whether anticoagulation, which has proven benefit in atrial fibrillation, prevents stroke in patients with atrial cardiopathy and no atrial fibrillation. Objective: To compare anticoagulation vs antiplatelet therapy for secondary stroke prevention in patients with cryptogenic stroke and evidence of atrial cardiopathy. Design, Setting, and Participants: Multicenter, double-blind, phase 3 randomized clinical trial of 1015 participants with cryptogenic stroke and evidence of atrial cardiopathy, defined as P-wave terminal force greater than 5000 µV × ms in electrocardiogram lead V1, serum N-terminal pro-B-type natriuretic peptide level greater than 250 pg/mL, or left atrial diameter index of 3 cm/m2 or greater on echocardiogram. Participants had no evidence of atrial fibrillation at the time of randomization. Enrollment and follow-up occurred from February 1, 2018, through February 28, 2023, at 185 sites in the National Institutes of Health StrokeNet and the Canadian Stroke Consortium. Interventions: Apixaban, 5 mg or 2.5 mg, twice daily (n = 507) vs aspirin, 81 mg, once daily (n = 508). Main Outcomes and Measures: The primary efficacy outcome in a time-to-event analysis was recurrent stroke. All participants, including those diagnosed with atrial fibrillation after randomization, were analyzed according to the groups to which they were randomized. The primary safety outcomes were symptomatic intracranial hemorrhage and other major hemorrhage. Results: With 1015 of the target 1100 participants enrolled and mean follow-up of 1.8 years, the trial was stopped for futility after a planned interim analysis. The mean (SD) age of participants was 68.0 (11.0) years, 54.3% were female, and 87.5% completed the full duration of follow-up. Recurrent stroke occurred in 40 patients in the apixaban group (annualized rate, 4.4%) and 40 patients in the aspirin group (annualized rate, 4.4%) (hazard ratio, 1.00 [95% CI, 0.64-1.55]). Symptomatic intracranial hemorrhage occurred in 0 patients taking apixaban and 7 patients taking aspirin (annualized rate, 1.1%). Other major hemorrhages occurred in 5 patients taking apixaban (annualized rate, 0.7%) and 5 patients taking aspirin (annualized rate, 0.8%) (hazard ratio, 1.02 [95% CI, 0.29-3.52]). Conclusions and Relevance: In patients with cryptogenic stroke and evidence of atrial cardiopathy without atrial fibrillation, apixaban did not significantly reduce recurrent stroke risk compared with aspirin. Trial Registration: ClinicalTrials.gov Identifier: NCT03192215.

Inflammatory Biomarkers and Stroke Subtype: An Important New Frontier

Inflammation is an established pathway in the formation, growth, and rupture of atherosclerotic plaques. Inflammation is thus essential to the pathogenesis of coronary heart disease and some types of ischemic stroke.1 The benefit of anti-inflammatory therapies, such as colchicine2 and the anti-IL1ß canakinumab,3 is proven in patients with coronary heart disease, yet it remains unproven for patients with ischemic stroke. Compared with coronary heart disease, the etiology of stroke is more heterogeneous. Besides arterio-arterial atherogenic embolism, possible etiologies are penetrator artery occlusion, cardioembolism, and other mechanisms. Finding a stroke etiology remains elusive in up to 30%-40% of patients despite a full evaluation. Understanding whether the stroke etiology modifies the association between inflammatory markers and recurrence risk is an important step to improve selection of patients for randomized trials on anti-inflammatory agents. IL-6 and high-sensitive CRP (hs-CRP) have been implicated in a higher recurrence risk after ischemic stroke by both an individual participant data meta-analysis4 and a Mendelian randomization study,5 but granular, in vivo results stratified by stroke etiology are lacking.

The BAND score: A simple model for upfront prediction of poor outcomes despite successful stroke thrombectomy.

BACKGROUND: While endovascular thrombectomy (EVT) is beneficial for patients with acute large vessel occlusion ischemic strokes, a significant portion of patients still do poorly despite successful recanalization. Identifying patients at high risk for poor outcomes can be helpful for future clinical trial design and optimizing acute stroke triage. METHODS: Consecutive EVT patients were identified from 2016 to 2021 at a Comprehensive Stroke Center, and clinical information was recorded. Poor outcome was defined as a 90-day modified Rankin Scale (mRS) of 4 or greater despite achieving a modified thrombolysis in cerebral infarction (mTICI) score of 2b or greater. Multivariable regression analyses were used to identify risk factors for poor outcomes, and a scoring system was constructed. RESULTS: 483 patients with successful recanalization were identified. From a randomly selected training cohort (n = 357), the 10-point BAND score was constructed from independent risk factors for poor outcomes: baseline disability (1 point: baseline mRS ≥ 2), age (1 point: 60-69 years, 2 points: 70-79 years, 3 points: 80-84 years, 4 points: 85 years or older), NIHSS (2 points: 13-17, 3 points: 18-22, and 4 points: ≥ 23), and delay from last known normal (1 point: ≥ 6 h). The BAND score was significantly associated with rates of poor outcomes (p < 0.001), and it achieved an area under the receiver-operating characteristic curve (AUC) of 0.80 (95 %CI 0.76-0.85) in our training cohort and 0.78 (95 %CI 0.70-0.86) in our validation cohort (n = 126). Overall, the BAND score had a significantly higher AUC value than the widely validated THRIVE score and the THRIVE-EVT calculation (p = 0.001 and 0.029, respectively). Among patients with high BAND scores (7 or higher), 88.2 % had poor outcomes. CONCLUSION: The BAND score is a simple tool to predict poor outcomes despite successful recanalization. Future studies are needed to confirm the BAND score's external validity.

Carotid Plaque-RADS: A Novel Stroke Risk Classification System.

BACKGROUND: Carotid artery atherosclerosis is highly prevalent in the general population and is a well-established risk factor for acute ischemic stroke. Although the morphological characteristics of vulnerable plaques are well recognized, there is a lack of consensus in reporting and interpreting carotid plaque features. OBJECTIVES: The aim of this paper is to establish a consistent and comprehensive approach for imaging and reporting carotid plaque by introducing the Plaque-RADS (Reporting and Data System) score. METHODS: A panel of experts recognized the necessity to develop a classification system for carotid plaque and its defining characteristics. Using a multimodality analysis approach, the Plaque-RADS categories were established through consensus, drawing on existing published reports. RESULTS: The authors present a universal classification that is applicable to both researchers and clinicians. The Plaque-RADS score offers a morphological assessment in addition to the prevailing quantitative parameter of "stenosis." The Plaque-RADS score spans from grade 1 (indicating complete absence of plaque) to grade 4 (representing complicated plaque). Accompanying visual examples are included to facilitate a clear understanding of the Plaque-RADS categories. CONCLUSIONS: Plaque-RADS is a standardized and reliable system of reporting carotid plaque composition and morphology via different imaging modalities, such as ultrasound, computed tomography, and magnetic resonance imaging. This scoring system has the potential to help in the precise identification of patients who may benefit from exclusive medical intervention and those who require alternative treatments, thereby enhancing patient care. A standardized lexicon and structured reporting promise to enhance communication between radiologists, referring clinicians, and scientists.

Plateauing atrial fibrillation burden in acute ischemic stroke admissions in the United States from 2010 to 2020.

BACKGROUND: Utilization of oral anticoagulants for acute ischemic stroke (AIS) prevention in patients with atrial fibrillation (AF) increased in the United States over the last decade. Whether this increase has been accompanied by any change in AF prevalence in AIS at the population level remains unknown. The aim of this study is to evaluate trends in AF prevalence in AIS hospitalizations in various age, sex, and racial subgroups over the last decade. METHODS: We used data contained in the 2010-2020 National Inpatient Sample to conduct a serial cross-sectional study. Primary AIS hospitalizations with and without comorbid AF were identified using International Classification of Diseases Codes. Joinpoint regression was used to compute annualized percentage change (APC) in prevalence and to identify points of change in prevalence over time. RESULTS: Of 5,190,148 weighted primary AIS hospitalizations over the study period, 25.1% had comorbid AF. The age- and sex-standardized prevalence of AF in AIS hospitalizations increased across the entire study period 2010-2020 (average APC: 1.3%, 95% confidence interval (CI): 0.8-1.7%). Joinpoint regression showed that prevalence increased in the period 2010-2015 (APC: 2.8%, 95% CI: 1.9-3.9%) but remained stable in the period 2015-2020 (APC: -0.3%, 95% CI: -1.0 to 1.9%). Upon stratification by age and sex, prevalence increased in all age/sex groups from 2010 to 2015 and continued to increase throughout the entire study period in hospitalizations in men 18-39 years (APC: 4.0%, 95% CI: 0.2-7.9%), men 40-59 years (APC: 3.4%, 95% CI: 1.9-4.9%) and women 40-59 years (APC: 4.4%, 95% CI: 2.0-6.8%). In contrast, prevalence declined in hospitalizations in women 60-79 (APC: -1.0%, 95% CI: -0.5 to -1.5%) and women ⩾ 80 years over the period 2015-2020 but plateaued in hospitalizations in similar-aged men over the same period. CONCLUSION: AF prevalence in AIS hospitalizations in the United States increased over the period 2010-2015, then plateaued over the period 2015-2020 due to declining prevalence in hospitalizations in women ⩾ 60 years and plateauing prevalence in hospitalizations in men ⩾ 60 years.

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool.

BACKGROUND: Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD. OBJECTIVE: This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP3) framework benefiting the pharmaceutical paradigm. METHOD: The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdgeTM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers. CONCLUSIONS: Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdgeTM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm.

Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review.

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.