Strokes

Present state and future of screening for atrial fibrillation: a state-of-the-art review.

Atrial fibrillation (AF) is the most common arrhythmia and is a leading cause of stroke and heart failure yet often remains undiagnosed. Screening has been proposed to identify asymptomatic AF and initiate preventive treatment, but evidence for reduction in hard clinical endpoints such as stroke and heart failure remains inconclusive. In this state-of-the-art review, we critically examine major AF...

Decoding cardiovascular risk in Chinese middle-aged and elderly adults: a 9-year prospective study integrating machine learning with explainable AI based on CHARLS cohort.

BACKGROUND: Cardiovascular disease constitutes the most formidable public health challenge in China, accounting for 48.98% and 47.35% of mortality in rural and urban populations, respectively, affecting approximately 330 million individuals. Existing risk stratification models predominantly derive from Western populations, with the Framingham Risk Equation systematically overestimating cardiovascu...

Technical Aspects and Clinical Relevance of Cuffless Devices for Blood Pressure Measurement. A Scientific Statement of the ESC Working Group on e-Cardiology, the ESC Council on Hypertension, and the European Association of Preventive Cardiology of the ESC.

Cuffless blood pressure (BP) monitoring devices represent a promising innovation in hypertension management. This scientific statement provides a comp...

Leveraging infarct topography for early warning: a robust model for predicting malignant cerebral edema after endovascular treatment in acute ischemic stroke.

BACKGROUND: The early prediction of malignant cerebral edema (MCE) following endovascular therapy for acute ischemic stroke is of paramount importance...

Real-Time MRI With Deep Learning for Efficient Evaluation of Neuromuscular Breathing Impairment.

Efficient detection of breathing impairment is critical for treatment and prognosis in neuromuscular disorders. However, standard pulmonary function t...

Which of the five anthropometric and lipid-based indexes best predicts hypertension? A machine learning approach.

Hypertension is associated with anthropometric and lipid-based indexes. This study aimed to examine and compare the predictive performance of these in...

Predicting Hypertension Persistence in Coarctation of the Aorta: A Feasibility Study.

Hypertension (HTN), despite contemporary endovascular repair, is a common and challenging complication of coarctation of the aorta (CoA), and its mech...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain a...

Machine Learning Models for Mortality Prediction in Intensive Care Unit Patients With Ischemic Stroke Associated With Intracranial Artery Stenosis: Retrospective Cohort Study.

BACKGROUND: Mortality prediction in intensive care unit (ICU) patients with ischemic stroke complicated by intracranial artery stenosis or occlusion r...

Non-pharmacological treatment of AECOPD.

Acute exacerbations of chronic obstructive pulmonary disease (AECOPDs) are acute events characterized by rapid worsening of dyspnea, cough, and sputum...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain li...

Regional brain age is decreased in children with sickle cell anemia.

DeepBrainNet, a machine learning tool, uses magnetic resonance imaging (MRI) to predict an individual's brain age, allowing calculation of the brain a...

The prognostic value of the PALBI score for mortality prediction in stroke: an internal and external validation study.

Recent studies show that there's a link between liver problems and how well someone does after having a stroke. The platelet-albumin-bilirubin (palbi)...

Blood Clot Classification in Ischemic Stroke Patients using ESAFH-Net with Explainable AI.

Evaluation of the impact of NOAC underdosing and exploration of bleeding risk factors in elderly patients with atrial fibrillation: artificial intelligence-based approach.

OBJECTIVE: Atrial fibrillation in elderly patients increases the risk of thromboembolism, necessitating long-term anticoagulation. While non-vitamin K...

AI-Based STroke Risk fActor Classification and Treatment (ABSTRACT) study.

BACKGROUND: Stroke is a leading cause of death and disability worldwide, costing the UK approximately £26 billion annually. While lifestyle modificati...

Association of allostatic load index with cognitive impairment in high-risk stroke populations.

BACKGROUND: Chronic psychosocial stress induces cumulative physiological dysregulation that accelerates biological aging and contributes to the develo...

Features of B-mode ultrasound and contrast-enhanced ultrasound of carotid plaque based on deep learning enhance the prediction of vulnerable plaques associated with acute ischemic stroke.

OBJECTIVES: To develop an AI model using ultrasound features of carotid plaque for predicting the risk of acute ischemic stroke (AIS) and assess its e...

Higher artificial intelligence-ECG atrial fibrillation prediction model output and estimated physiologic aging predict higher risk of adverse vascular events in patients with migraine.

OBJECTIVE: To investigate the ability of artificial intelligence-enabled electrocardiogram (AI-ECG) atrial fibrillation (AF) prediction model output a...

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.

BACKGROUND: Stroke is a complex, multidimensional disorder influenced by interacting inflammatory, immune, coagulation, endothelial, and metabolic pat...