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1,041 results for “cardiovascular diseases”
Data from: Effects of fermented vegetables on the gut microbiota for prevention of cardiovascular disease
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Risk factors for cardiovascular disease (CVD) in adults with type 1 diabetes: findings from prospective real-life T1D exchange registry
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Associations of serum uric acid with cardiovascular disease risk factors: a retrospective cohort study in Southeastern China
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Systematic review data of whole grains versus placebo or refined grains on cardiovascular disease risk factors.
<p class="Body"><span>This dataset comprises data extracted 29 publications which were included in a systematic review and meta-analysis of randomised controlled trials which compared whole grain versus refined grain dietary intake on cardiovascular disease risk factors. There were 80 cardiovascular disease risk factor outcome measures considered in the review. Data were extracted by one investigator and checked for accuracy twice. Study characteristics were extracted, including study design, sample population, and details of the intervention and control conditions. Outcome data were extracted for the intervention and comparator groups were baseline, change, and follow-up variables, variable units, and statistical significance over time and between groups. Adverse events were also recorded. The 29 included studies measured and reported on 40 outcomes. Extracted outcomes can be grouped as haemodynamics (reported by 12 studies), body composition (15 studies), blood lipids (18 studies), glycaemic and/or insulin markers (19 studies), inflammatory markers (21 studies), oxidative stress markers (6 studies), and cardiovascular comorbidity incidence (2 studies). Rigorous analysis, including meta-regression, may be carried out using this data to evaluate the cause and effect relationship of whole grains on cardiovascular risk by considering confounding variables on pooled outcomes. </span></p>
Prediction of cardiovascular diseases by integrating multi-modal features with machine learning methods
<p>Electrocardiogram (ECG) and Phonocardiogram (PCG) play important roles in early prevention and diagnosis of cardiovascular diseases. As the development of machine learning technique, detection of cardiovascular diseases from ECG and PCG has been attracted much attention. However, current available methods are mostly based on single data resource. It is desirable to develop efficient multi-modal machine learning methods to predict and diagnose cardiovascular diseases. In this study, we propose a novel multi-modal method for predicting cardiovascular diseases based on ECG and PCG features. By building up conventional neural networks, we extract ECG and PCG deep coding features respectively. The genetic algorithm is used to screen the combined features and obtain the best feature subset. Then support vector machine makes classification decision. Experimental results show that compared with using single-modal features ECG and PCG, the performance of this method reaches an AUC value of 0.936 when using multi-modal data resources.</p> <p>This dataset is developed from a real-world dataset which was assembled by PhysioNet/CinC Challenge in 2016. The original dataset can be downloaded from website (<a href="http://www.physionet.org/challenge/2016/">http://www.physionet.org/challenge/2016/</a>).</p>
Clinical and physical parameters of cardiovascular disease patients and occurence of adverse events during exercise
<h2>Supplementary data for the publication available at doi: 10.1038/s41598-024-68223-y.</h2> <p>The article aimed to evaluate the predictive power of physical and clinical parameters to predict the rate of adverse events during exercise-based cardiac rehabilitation.</p> <p>Here the reader can find all anonymized data and complete analysis of results that support the findings reported in the cited publication.</p>
Table A6 images from Computer-aided drug design (CADD) to de-orphanise marine molecules: Finding potential therapeutic agents for neurodegenerative and cardiovascular diseases
<p>High Reslution Images from Table A6</p>
Data from: Conflicts at work are associated with a higher risk of cardiovascular disease
Background: Only few authors have analyzed the impact of workplace conflicts and the resulting stress on the risk of developing cardiovascular disorders. The goal of this study was to analyze the association between workplace conflicts and cardiovascular disorders in patients treated by German general practitioners. Methods: Patients with an initial documentation of a workplace conflict experience between 2005 and 2014 were identified in 699 general practitioner practices (index date). We included only those that were between the ages of 18 and 65 years, had a follow-up time of at least 180 days after the index date, and had not been diagnosed with angina pectoris, myocardial infarction, coronary heart diseases, or stroke prior to the documentation of the workplace mobbing. In total, this study consisted of 7,374 patients who experienced conflicts and 7,374 controls for analysis. The main outcome measure was the incidence of angina pectoris, myocardial infarction, and stroke correlated with workplace conflict experiences. Results: After a maximum of five years of follow-up, 2.9% of individuals who experienced workplace conflict were affected by cardiovascular diseases, while only 1.4% were affected in the control group (p-value<0.001). Workplace conflict was associated with a 1.63-fold increase in the risk of developing cardiovascular diseases. Finally, the impact of workplace conflict was higher for myocardial infarction (OR=2.03) than for angina pectoris (OR=1.79) and stroke (OR=1.56). Conclusions: Overall, we found a significant association between workplace conflicts and cardiovascular disorders.
Cardiovascular Risk Markers and Response to Statins After Kawasaki Disease
ClinicalTrials.gov study NCT00305201. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Effect of Amount and Type of Dietary Carbohydrates on Risk for Cardiovascular Heart Disease and Diabetes
ClinicalTrials.gov study NCT00608049. IPD Sharing: Not stated. Countries: 1. Publications: 6.
Ruminant Trans Fats and the Risk of Cardiovascular Disease in Women
ClinicalTrials.gov study NCT00930137. IPD Sharing: Not stated. Countries: 1. Publications: 11.
Integrating Hypertension and Cardiovascular Diseases Care Into Existing HIV Services Package in Botswana (InterCARE)
ClinicalTrials.gov study NCT05414526. IPD Sharing: NO. Countries: 1. Publications: 3.
Treatment of Cardiovascular Disease With Low Dose Rivaroxaban in Advanced Chronic Kidney Disease
ClinicalTrials.gov study NCT03969953. IPD Sharing: YES. Countries: 12. Publications: 0.
FGF23 and Cardiovascular Damage in Anemia With an Without Chronic Kidney Disease.
ClinicalTrials.gov study NCT05356325. IPD Sharing: NO. Countries: 1. Publications: 5.
Prevention of Cardiovascular Disease With Polypill Among Pars Cohort Participants
ClinicalTrials.gov study NCT03459560. IPD Sharing: NO. Countries: 1. Publications: 12.
Cohort Study on Treatment of Cardiovascular Diseases With Traditional Chinese Medicine
ClinicalTrials.gov study NCT05309343. IPD Sharing: YES. Countries: 1. Publications: 1.
Value of Cardiac Rehabilitation on the Treatment of Cardiovascular Disease
ClinicalTrials.gov study NCT05320848. IPD Sharing: NO. Countries: 1. Publications: 5.
Evaluating a Web-Based Cardiovascular Disease Risk Factor Reduction Program Among American Indians
ClinicalTrials.gov study NCT00608387. IPD Sharing: Not stated. Countries: 1. Publications: 4.
RiSE to Prevent Cardiovascular Disease in African Americans
ClinicalTrials.gov study NCT03878290. IPD Sharing: NO. Countries: 1. Publications: 13.
The KaHOLO Project: Preventing Cardiovascular Disease in Native Hawaiians
ClinicalTrials.gov study NCT02620709. IPD Sharing: Not stated. Countries: 1. Publications: 2.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.