Stroke prediction atrial fibrillation

To investigate the clinical significance of the CHA2 DS2 -VASc-60 score, lipoprotein (a) [Lp(a)], red blood cell distribution width (RDW), and their combined effect in patients with non-valvular atrial fibrillation (NVAF) who experience acute ischemic stroke (AIS). This retrospective analysis was conducted on the clinical data of hospitalized patients with NVAF at the Third Affiliated Hospital of Anhui Medical University between April 1, 2020, and April 1, 2023. Based on the diagnosis of acute ischemic stroke (AIS), the patients were divided into two groups: the AIS group (150 cases of NVAF patients with comorbid AIS) and the non-AIS group (163 cases of NVAF patients without AIS)...

Purpose To investigate whether the peak early filling rate normalized to the filling volume (PEFR/FV) estimated from four-dimensional (4D) flow cardiac MRI may be used to assess impaired left ventricular (LV) filling and predict clinical outcomes in individuals with hypertrophic cardiomyopathy (HCM). Materials and Methods Cardiac MRI with a 4D flow sequence and late gadolinium enhancement (LGE), as well as echocardiography, was performed in 88 individuals: 44 participants with HCM from a French prospective registry (ClinicalTrials...

OBJECTIVE: Studies have revealed that sex can predict differences in multiple aspects of atrial fibrillation (AF). These differences are underreported in the Middle East. This study aims to describe sex-specific differences in risk factors, symptomatology, management, and outcomes in Middle Eastern patients with AF. METHODS: The JoFib (Jordan-Atrial-Fibrillation) study is an observational, prospective, multicenter, nationwide registry in AF. Comparisons were made between female and male patients using Pearson chi-square and Mann-Whitney U tests...

Background  Reasons for the relatively poor performance of bleeding prediction models are not well understood but may relate to differences in predictors for various anatomical sites of bleeding. Methods  We pooled individual participant data from four randomized controlled trials of antithrombotic therapy in patients with coronary and peripheral artery diseases, embolic stroke of undetermined source (ESUS), or atrial fibrillation. We examined discrimination and calibration of models for any major bleeding, major gastrointestinal (GI) bleeding, and intracranial hemorrhage (ICH), according to the time since initiation of antithrombotic therapy, and indication for antithrombotic therapy...

Postoperative atrial fibrillation (POAF) after cardiac surgery is associated with elevated morbidity and mortality. Although current prediction models have limited efficacy, several perioperative interventions can reduce patients' risk of POAF. These begin with preoperative medications, including beta-blockers and amiodarone. Moreover, patients should be screened for preexisting atrial fibrillation (AF) so that concomitant surgical ablation and left atrial appendage occlusion can be performed in appropriate candidates...

BACKGROUND: Covert atrial fibrillation (AF) is a predominant aetiology of embolic stroke of undetermined source (ESUS). Evidence suggested that AF is more frequently detected by implantable loop recorder (ILR) than by conventional monitoring. However, the predictive factors associated with occult AF detected using ILRs are not well established yet. In this study we aim to investigate the predictors of AF detection in patients with ESUS undergoing an ILR. METHODS: This observational multi-centre study included consecutive ESUS patients who underwent ILR implantation...

In this study, we leveraged machine learning (ML) approach to develop and validate new assessment tools for predicting stroke and bleeding among patients with atrial fibrillation (AFib) and cancer. We conducted a retrospective cohort study including patients who were newly diagnosed with AFib with a record of cancer from the 2012-2018 Surveillance, Epidemiology, and End Results (SEER)-Medicare database. The ML algorithms were developed and validated separately for each outcome by fitting elastic net, random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and neural network models with tenfold cross-validation (train:test = 7:3)...

BACKGROUND: Atrial fibrillation (AF) is a common treatable risk factor for stroke. Screening for paroxysmal AF in general practice is difficult, but biomarkers might help improve screening strategies. OBJECTIVES: We investigated six blood biomarkers for predicting paroxysmal AF in general practice. METHODS: This was a pre-specified sub-study of the SCREEN-AF RCT done in Germany. Between 12/2017-03/2019, we enrolled ambulatory individuals aged 75 years or older with a history of hypertension but without known AF...

INTRODUCTION: Detection of paroxysmal atrial fibrillation (PAF) is crucial for secondary prevention in patients with recent strokes of unknown etiology. This systematic review and meta-analysis assess the predictive power of available risk scores for detecting new PAF after acute ischemic stroke (AIS). METHODS: PubMed, Embase, Scopus, and Web of Science databases were searched until September 2023 to identify relevant studies. A bivariate random effects meta-analysis model pooled data on sensitivity, specificity, and area under the curve (AUC) for each score...

BACKGROUND: Pulsed field ablation has recently emerged as an interesting non-thermal energy for atrial fibrillation ablation. At a time of rapid spread of this technology, there is still a lack of prospective real-life data. AIM: To describe multicentre prospective safety and 1-year efficacy data in three of the first French centres to use pulsed field ablation. METHODS: All consecutive patients undergoing a first pulsed field ablation were included prospectively...

BACKGROUND: Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation can aid in identifying undiagnosed paroxysmal atrial fibrillation (AF) in patients with embolic stroke of undetermined source (ESUS). OBJECTIVE: We assessed the efficacy of an AI model in identifying AF based on SR ECGs in patients with ESUS. METHODS: A transformer-based vision AI model was developed using 737,815 SR ECGs from patients with and without AF to detect current paroxysmal AF or predict the future development of AF within a two-year period...

BACKGROUND: Ischemic stroke is associated with increased risk of morbidity and mortality in future vascular events. OBJECTIVES: To investigate whether CHA2DS2-VASc scores aid in risk stratification of middle-aged patients without atrial fibrillation (AF) experiencing ischemic stroke. METHODS: We analyzed data of 2628 patients, aged 40-65 years with no known AF who presented with acute ischemic stroke between January 2020 and February 2022...

BACKGROUND: Atrial fibrillation (AF) is a prevalent arrhythmic condition resulting in increased stroke risk and is associated with high mortality. Electrolyte imbalance can increase the risk of AF, where the relationship between AF and serum electrolytes remains unclear. METHODS: A total of 15,792 individuals were included in the observational study, with incident AF ascertainment in the Atherosclerosis Risk in Communities (ARIC) study. The Cox regression models were applied to calculate the hazard ratio (HR) and 95% confidence interval (CI) for AF based on different serum electrolyte levels...

BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other complications. Predicting AF risk in advance can improve early diagnostic efficiency. Deep learning has been used for disease risk prediction; however, it lacks adherence to evidence-based medicine standards. Identifying the underlying mechanisms behind disease risk prediction is important and required. METHODS: We developed an explainable deep learning model called HBBI-AI to predict AF risk using only heart beat-to-beat intervals (HBBIs) during sinus rhythm...

INTRODUCTION: Stroke embolic source have an unknown origin in 30-40% of cases. Mechanical thrombectomy for acute large vessel occlusion stroke has provided us with a method to directly retrieve the thrombi from patients for analysis. By collecting stroke-causing thrombi from known sources, we can then use high-throughput RNA sequencing (RNAseq) technology to directly measure the gene expression signatures of these clots. This may allow us to identify genetic markers to predict the cause of cryptogenic embolism...

Atrial cardiomyopathy is defined as any complex of structural, architectural, contractile or electrophysiological changes affecting atria, with the potential to produce clinically relevant manifestations. Most of our knowledge about the mechanistic aspects of atrial cardiomyopathy is derived from studies investigating animal models of atrial fibrillation and atrial tissue samples obtained from individuals who have a history of atrial fibrillation. Several noninvasive tools have been reported to characterize atrial cardiomyopathy in patients, which may be relevant for predicting the risk of incident atrial fibrillation and its related outcomes, such as stroke...

BACKGROUND: Atrial fibrillation (AF) pattern, relevant cardiac changes are important predictors of outcomes in AF, but their impact on patients with ischemic stroke and AF remained unclear. We aimed to explore the impact of AF patterns, cardiac structural and functional markers on long-term functional and cognitive outcomes in ischemic stroke patients with AF. METHODS: Ischemic stroke patients diagnosed with AF were enrolled in this retrospective cohort study. AF pattern was defined by both traditional and novel classification, in which patients were divided into AF diagnosed after stroke (AFDAS) and known before stroke (KAF)...

BACKGROUND: Traditional scores as CHADS2 and CHA2DS2-Vasc are suitable for predicting stroke and systemic embolism in patients with atrial fibrillation (AF) and have shown to be also associated with mortality. Other more complex scores have been recommended for survival prediction. The purpose of our analysis was to test the performance of different clinical scores in predicting 1-year mortality in AF patients. MATERIAL AND METHODS: CHADS2 and CHA2DS2-Vasc scores were calculated for AF patients of the BLITZ-AF register and compared to R2-CHADS2, R2-CHA2DS2-Vasc and CHA2DS2VASc-RAF scores in predicting 1-year survival...

BACKGROUND & AIMS: Previous observational studies have yielded inconsistent findings regarding associations between red/processed meat intake and the risk of cardiovascular disease (CVD). Some studies have suggested positive relationships, while others have demonstrated no significant associations. However, causal effects remain uncertain. This 2023 Mendelianrandomization (MR) study investigated the causal relationship between red and processed meat (porkmeat, mutton meat, beef meat)intake and CVD risk by analyzing summary data from the UK Biobank (exposure), CARDIoGRAMplusC4D (coronary artery disease [CAD]), MEGASTROKE (stroke), Nielsen et al...

OBJECTIVE: To systematically review the risk prediction model of Hemorrhages Transformation (HT) after intravenous thrombolysis in patients with Acute Ischemic Stroke (AIS). METHODS: Web of Science, The Cochrane Library, PubMed, Embase, CINAHL, CNKI, CBM, WanFang, and VIP were searched from inception to February 25, 2023 for literature related to the risk prediction model for HT after thrombolysis in AIS. RESULTS: A total of 17 included studies contained 26 prediction models, and the AUC of all models at the time of modeling ranged from 0...