A Study of Cardiogenic Stroke Risk in Non-valvular Atrial Fibrillation Patients

Song, Ziliang; Xu, Kai; Hu, Xiaofeng; Jiang, Weifeng; Wu, Shaohui; Qin, Mu; Liu, Xu

doi:10.3389/fcvm.2020.604795

Cited by 9 publications

(5 citation statements)

References 39 publications

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“…Regarding several recent studies (38)(39)(40), the risk stratification is in high demand to prevent sudden death or stroke caused by cardiac diseases. Inspired by the present algorithm, the risk prediction of cardiac diseases can be automated based on the clinical data collected from the ECG or electronic heart records.…”

Section: Discussionmentioning

confidence: 99%

Automatic Detection for Multi-Labeled Cardiac Arrhythmia Based on Frame Blocking Preprocessing and Residual Networks

Zhang

2021

Front. Cardiovasc. Med.

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Introduction: Electrocardiograms (ECG) provide information about the electrical activity of the heart, which is useful for diagnosing abnormal cardiac functions such as arrhythmias. Recently, several algorithms based on advanced structures of neural networks have been proposed for auto-detecting cardiac arrhythmias, but their performance still needs to be further improved. This study aimed to develop an auto-detection algorithm, which extracts valid features from 12-lead ECG for classifying multiple types of cardiac states.Method: The proposed algorithm consists of the following components: (i) a preprocessing component that utilizes the frame blocking method to split an ECG recording into frames with a uniform length for all considered ECG recordings; and (ii) a binary classifier based on ResNet, which is combined with the attention-based bidirectional long-short term memory model.Result: The developed algorithm was trained and tested on ECG data of nine types of cardiac states, fulfilling a task of multi-label classification. It achieved an averaged F1-score and area under the curve at 0.908 and 0.974, respectively.Conclusion: The frame blocking and bidirectional long-short term memory model represented an improved algorithm compared with others in the literature for auto-detecting and classifying multi-types of cardiac abnormalities.

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Section: Discussionmentioning

confidence: 99%

Automatic Detection for Multi-Labeled Cardiac Arrhythmia Based on Frame Blocking Preprocessing and Residual Networks

Zhang

2021

Front. Cardiovasc. Med.

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“…The patients were divided into three groups based on a previous study and the tertiles of the BNP levels of all patients at admission [ 13 ]: group A had a BNP of <334.5 pg/mL (low BNP group), group B had a BNP of 334.5–1,288 pg/mL (slightly elevated BNP group), and group C had a BNP of >1,288 pg/mL (significantly elevated BNP group).…”

Section: Methodsmentioning

confidence: 99%

Relationship between Brain Natriuretic Peptide and Thromboembolic Events in Elderly Patients with Nonvalvular Atrial Fibrillation

Wang,

Huang,

et al. 2024

Cardiology Research and Practice

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Objective. To investigate the relationship between brain natriuretic peptide (BNP) and thromboembolic events in elderly patients with nonvalvular atrial fibrillation (NVAF). Methods. This is a prospective cohort study, and based on the inclusion and exclusion criteria, 180 elderly patients with NVAF were included. The patients received follow-up appointments in the clinic or by telephone every 6 months after the beginning of the study. The primary follow-up endpoints were thromboembolic and atherosclerotic events, including ischaemic stroke, myocardial infarction, and systemic embolism. The secondary endpoints were adverse events, including cardiovascular death, all-cause death, and hospitalisation for heart failure. Patients were divided into three groups according to their BNP level at admission: group A (BNP ≤334.5 pg/mL), group B (BNP = 334.5–1,288 pg/mL), and group C (BNP ≥1,288 pg/mL). Results. A total of 180 patients were enrolled in this study, with 50 patients in group A, 68 in group B, and 62 in group C. Compared with groups A and B, group C had a higher CHA2DS2-VASc score (Z = 15.142; P=0.001) and a lower ejection fraction (EF) value (Z = 119.893; P=0.001). The left atrium (LA) and left ventricular end-diastolic diameter (LVEDD) were larger (Z = 105.031; P=0.001 and Z = 74.430; P=0.001), respectively, suggesting that patients with significantly increased BNP had a higher risk of thromboembolism and atherosclerosis, lower EF, larger LA and LVEDD, and worse cardiac function. After 1 year of follow-up, the incidence of primary endpoint events (χ2 = 9.556; P=0.008) and secondary endpoint events (χ2 = 59.485; P=0.001) in group C were higher than those in groups A and B. Conclusion. Higher BNP levels may be an independent risk factor for thromboembolic and atherosclerotic events in elderly patients with NVAF. The higher the BNP level, the greater the risk of thromboembolic and atherosclerotic events.

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“…Recent studies also demonstrated that hyperuricemia was associated with IS among AF patients. Several case-control studies showed that uric acid level was closely associated with LA stasis (composed of LA thrombus, LASEC) in patients with NVAF (170)(171)(172)(173). In a study of NVAF patients at clinically low-intermediate risk (CHA 2 DS 2 -VASc score = 0 or 1), uric acid levels were higher in those with transesophageal echocardiography (TEE) thromboembolic risk than in those without TEE risk (174).…”

Section: Oxidative Stress and Inflammation Biomarkermentioning

confidence: 99%

A Review of Biomarkers for Ischemic Stroke Evaluation in Patients With Non-valvular Atrial Fibrillation

Shang

Zhang

Guo

et al. 2021

Front. Cardiovasc. Med.

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Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide and results in a significantly increased ischemic stroke (IS) risk. IS risk stratification tools are widely being applied to guide anticoagulation treatment decisions and duration in patients with non-valvular AF (NVAF). The CHA2DS2-VASc score is largely validated and currently recommended by renowned guidelines. However, this score is heavily dependent on age, sex, and comorbidities, and exhibits only moderate predictive power. Finding effective and validated clinical biomarkers to assist in personalized IS risk evaluation has become one of the promising directions in the prevention and treatment of NVAF. A number of studies in recent years have explored differentially expressed biomarkers in NVAF patients with and without IS, and the potential role of various biomarkers for prediction or early diagnosis of IS in patients with NVAF. In this review, we describe the clinical application and utility of AF characteristics, cardiac imaging and electrocardiogram markers, arterial stiffness and atherosclerosis-related markers, circulating biomarkers, and novel genetic markers in IS diagnosis and management of patients with NVAF. We conclude that at present, there is no consensus understanding of a desirable biomarker for IS risk stratification in NVAF, and enrolling these biomarkers into extant models also remains challenging. Further prospective cohorts and trials are needed to integrate various clinical risk factors and biomarkers to optimize IS prediction in patients with NVAF. However, we believe that the growing insight into molecular mechanisms and in-depth understanding of existing and emerging biomarkers may further improve the IS risk identification and guide anticoagulation therapy in patients with NVAF.

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A Study of Cardiogenic Stroke Risk in Non-valvular Atrial Fibrillation Patients

Cited by 9 publications

References 39 publications

Automatic Detection for Multi-Labeled Cardiac Arrhythmia Based on Frame Blocking Preprocessing and Residual Networks

Automatic Detection for Multi-Labeled Cardiac Arrhythmia Based on Frame Blocking Preprocessing and Residual Networks

Relationship between Brain Natriuretic Peptide and Thromboembolic Events in Elderly Patients with Nonvalvular Atrial Fibrillation

A Review of Biomarkers for Ischemic Stroke Evaluation in Patients With Non-valvular Atrial Fibrillation

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