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Condition: Atrial Fibrillation
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Total 176 results found since Jan 2013.

Influence of Exercise Training on the Left Atrium:Implications for Atrial Fibrillation, Heart Failure and Stroke
Am J Physiol Heart Circ Physiol. 2023 Jul 28. doi: 10.1152/ajpheart.00322.2023. Online ahead of print.ABSTRACTThe left atrium (LA) plays a critical role in receiving pulmonary venous return and modulating left ventricular (LV) filling. With the onset of exercise, LA function contributes to the augmentation in stroke volume. Due to the growing focus on atrial imaging, there is now evidence that structural remodelling and dysfunction of the LA is associated with adverse outcomes including incident cardiovascular disease. In patients with established disease, pathological changes in atrial structure and function are associate...
Source: American Journal of Physiology. Heart and Circulatory Physiology - July 28, 2023 Category: Physiology Authors: Adrian Elliott Jonathan Ariyaratnam Erin J Howden Andr é La Gerche Prashanthan Sanders Source Type: research

Prediction of short-term atrial fibrillation risk using primary care electronic health records
Conclusions FIND-AF, a machine learning algorithm applicable at scale in routinely collected primary care data, identifies people at higher risk of short-term AF.
Source: Heart - June 26, 2023 Category: Cardiology Authors: Nadarajah, R., Wu, J., Hogg, D., Raveendra, K., Nakao, Y. M., Nakao, K., Arbel, R., Haim, M., Zahger, D., Parry, J., Bates, C., Cowan, C., Gale, C. P. Tags: Open access, Editor's choice Arrhythmias and sudden death Source Type: research

Sensors, Vol. 23, Pages 5618: Automated Signal Quality Assessment of Single-Lead ECG Recordings for Early Detection of Silent Atrial Fibrillation
s D. Zink Atrial fibrillation (AF) is an arrhythmic cardiac disorder with a high and increasing prevalence in aging societies, which is associated with a risk for stroke and heart failure. However, early detection of onset AF can become cumbersome since it often manifests in an asymptomatic and paroxysmal nature, also known as silent AF. Large-scale screenings can help identifying silent AF and allow for early treatment to prevent more severe implications. In this work, we present a machine learning-based algorithm for assessing signal quality of hand-held diagnostic ECG devices to prevent misclassification due to insu...
Source: Sensors - June 15, 2023 Category: Biotechnology Authors: Markus Lueken Michael Gramlich Steffen Leonhardt Nikolaus Marx Matthias D. Zink Tags: Article Source Type: research

Cardiovascular disease (CVD) outcomes and associated risk factors in a medicare population without prior CVD history: an analysis using statistical and machine learning algorithms
AbstractThere is limited information on predicting incident cardiovascular outcomes among high- to very high-risk populations such as the elderly ( ≥ 65 years) in the absence of prior cardiovascular disease and the presence of non-cardiovascular multi-morbidity. We hypothesized that statistical/machine learning modeling can improve risk prediction, thus helping inform care management strategies. We defined a population from the Medicare he alth plan, a US government-funded program mostly for the elderly and varied levels of non-cardiovascular multi-morbidity. Participants were screened for cardiovascular disease (CVD)...
Source: Internal and Emergency Medicine - June 9, 2023 Category: Emergency Medicine Source Type: research

MRI-based training model for left atrial appendage closure
ConclusionThe proposed contrast-agent and radiation-free MRI-based training model for percutaneous LAA closure enables the pre-interventional assessment of the influence of the TSP site on the access of patient-specific LAA shapes. A straightforward replication of this work is measured by using clinically available imaging protocols and a widespread 3D printer technique to build the model.
Source: International Journal of Computer Assisted Radiology and Surgery - March 30, 2023 Category: Intensive Care Source Type: research

Risk factor identification and prediction models for prolonged length of stay in hospital after acute ischemic stroke using artificial neural networks
ConclusionThe artificial neural network model achieved adequate discriminative power for predicting prolonged length of stay after acute ischemic stroke and identified crucial factors associated with a prolonged hospital stay. The proposed model can assist in clinically assessing the risk of prolonged hospitalization, informing decision-making, and developing individualized medical care plans for patients with acute ischemic stroke.
Source: Frontiers in Neurology - February 9, 2023 Category: Neurology Source Type: research

C1QC, VSIG4, and CFD as Potential Peripheral Blood Biomarkers in Atrial Fibrillation-Related Cardioembolic Stroke
Oxid Med Cell Longev. 2023 Jan 5;2023:5199810. doi: 10.1155/2023/5199810. eCollection 2023.ABSTRACTAtrial fibrillation (AF) is a major risk factor for ischemic stroke. We aimed to identify novel potential biomarkers with diagnostic value in patients with atrial fibrillation-related cardioembolic stroke (AF-CE).Publicly available gene expression profiles related to AF, cardioembolic stroke (CE), and large artery atherosclerosis (LAA) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and then functionally annotated. The support vector machine recursive feature elimi...
Source: Atherosclerosis - January 16, 2023 Category: Cardiology Authors: Qian Ding Juan Xing Fanghui Bai Wei Shao Kaiqi Hou Shoudu Zhang Yuanzheng Hu Baochao Zhang Hui Zhao Qian Xu Source Type: research

Prediction of incident atrial fibrillation in post-stroke patients using machine learning: a French nationwide study
ConclusionsML algorithms predict incident AF post-stroke with a better ability than previously developed clinical scores.Graphic AbstractAF: atrial fibrillation; DNN: deep neural network; IS: ischemic stroke; KNN: K-nearest neighbors; LR: logistic regression; RFC: random forest classifier; XGBoost: extreme gradient boosting
Source: Clinical Research in Cardiology - December 17, 2022 Category: Cardiology Source Type: research