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4,008 results for “Heart failure;”
Evaluation of the Effect of Animated Video-Assisted Nutrition Education on Heart Failure Patients
ClinicalTrials.gov study NCT07305272. IPD Sharing: YES. Countries: 1. Publications: 1.
Heart Failure Optimization at Home to Improve Outcomes (Hozho): A Pragmatic Clinical Trial in Navajo Nation
ClinicalTrials.gov study NCT05792085. IPD Sharing: NO. Countries: 1. Publications: 1.
Acute Effects of Inorganic Nitrite on Cardiovascular Hemodynamics in Heart Failure With Preserved Ejection Fraction
ClinicalTrials.gov study NCT01932606. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Dapagliflozin Evaluation to Improve the LIVEs of Patients With PReserved Ejection Fraction Heart Failure.
ClinicalTrials.gov study NCT03619213. IPD Sharing: YES. Countries: 20. Publications: 48.
Nitrate's Effect on Activity Tolerance in Heart Failure With Preserved Ejection Fraction
ClinicalTrials.gov study NCT02053493. IPD Sharing: YES. Countries: 1. Publications: 3.
POCUS-Guided Diuresis for Decompensated Heart Failure
ClinicalTrials.gov study NCT06921603. IPD Sharing: YES. Countries: 1. Publications: 27.
Study on the Efficacy and Mechanism of Cardiac Rehabilitation for Stem Cell Mobilization and Heart Failure Improvement
ClinicalTrials.gov study NCT00154466. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Nutritional Therapy Interventions in Heart Failure
ClinicalTrials.gov study NCT03424265. IPD Sharing: NO. Countries: 1. Publications: 2.
Stepped Care for Depression in Heart Failure
ClinicalTrials.gov study NCT02997865. IPD Sharing: YES. Countries: 1. Publications: 3.
Inhaled Selective Pulmonary Vasodilators for Advanced Heart Failure Therapies and Lung Transplantation Outcomes
ClinicalTrials.gov study NCT03081052. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Functional remodelling of perinuclear mitochondria alters nucleoplasmic Ca2+ signalling in heart failure
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Patient-specific models of dyssynchronous heart failure for assessment of regional work in patients undergoing cardiac resynchronization therapy
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Dataset related to article "Single-Cell Sequencing of Mouse Heart Immune Infiltrate in Pressure Overload-Driven Heart Failure Reveals Extent of Immune Activation."
<p>BACKGROUND:</p> <p>Inflammation is a key component of cardiac disease, with macrophages and T lymphocytes mediating essential roles in the progression to heart failure. Nonetheless, little insight exists on other immune subsets involved in the cardiotoxic response.</p> <p>METHODS:</p> <p>Here, we used single-cell RNA sequencing to map the cardiac immune composition in the standard murine nonischemic, pressure-overload heart failure model. By focusing our analysis on CD45<sup>+</sup> cells, we obtained a higher resolution identification of the immune cell subsets in the heart, at early and late stages of disease and in controls. We then integrated our findings using multiparameter flow cytometry, immunohistochemistry, and tissue clarification immunofluorescence in mouse and human.</p> <p>RESULTS:</p> <p>We found that most major immune cell subpopulations, including macrophages, B cells, T cells and regulatory T cells, dendritic cells, Natural Killer cells, neutrophils, and mast cells are present in both healthy and diseased hearts. Most cell subsets are found within the myocardium, whereas mast cells are found also in the epicardium. Upon induction of pressure overload, immune activation occurs across the entire range of immune cell types. Activation led to upregulation of key subset-specific molecules, such as oncostatin M in proinflammatory macrophages and PD-1 in regulatory T cells, that may help explain clinical findings such as the refractivity of patients with heart failure to anti-tumor necrosis factor therapy and cardiac toxicity during anti-PD-1 cancer immunotherapy, respectively.</p> <p>CONCLUSIONS:</p> <p>Despite the absence of infectious agents or an autoimmune trigger, induction of disease leads to immune activation that involves far more cell types than previously thought, including neutrophils, B cells, Natural Killer cells, and mast cells. This opens up the field of cardioimmunology to further investigation by using toolkits that have already been developed to study the aforementioned immune subsets. The subset-specific molecules that mediate their activation may thus become useful targets for the diagnostics or therapy of heart failure.</p> <p> </p> <p>This dataset is created in .ets form, we attach a pdf with the information about.</p>
Data from: Development and validation of warning system of ventricular tachyarrhythmia in patients with heart failure with heart rate variability data
Implantable-cardioverter defibrillators (ICD) detect and terminate life-threatening ventricular tachyarrhythmia with electric shocks after they occur. This puts patients at risk if they are driving or in a situation where they can fall. ICD's shocks are also very painful and affect a patient's quality of life. It would be ideal if ICDs can accurately predict the occurrence of ventricular tachyarrhythmia and then issue a warning or provide preventive therapy. Our study explores the use of ICD data to automatically predict ventricular arrhythmia using heart rate variability (HRV). A 5 minute and a 10 second warning system are both developed and compared. The participants for this study consist of 788 patients who were enrolled in the ICD arm of the Sudden Cardiac Death – Heart Failure Trial (SCD-HeFT). Two groups of patient rhythms, regular heart rhythms and pre-ventricular-tachyarrhythmic rhythms, are analyzed and different HRV features are extracted. Machine learning algorithms, including random forests (RF) and support vector machines (SVM), are trained on these features to classify the two groups of rhythms in a subset of the data comprising the training set. These algorithms are then used to classify rhythms in a separate test set. This performance is quantified by the area under the curve (AUC) of the ROC curve. Both RF and SVM methods achieve a mean AUC of 0.81 for 5-minute prediction and mean AUC of 0.87-0.88 for 10-second prediction; an AUC over 0.8 typically warrants further clinical investigation. Our work shows that moderate classification accuracy can be achieved to predict ventricular tachyarrhythmia with machine learning algorithms using HRV features from ICD data. These results provide a realistic view of the practical challenges facing implementation of machine learning algorithms to predict ventricular tachyarrhythmia using HRV data, motivating continued research on improved algorithms and additional features with higher predictive power.
Transcriptomic and spatial datasets of human ex vivo right atrial tissue in ischemic heart disease and heart failure
<p>This dataset contains raw counts and processed data and annotations for our transcriptomic and spatial dissection of human ex vivo right atrial tissue in ischemic heart disease and heart failure.</p> <p> </p> <p>snRNA.zip contains the snRNA-seq dataset for heart right atrial appendade and pericardial fluid.</p> <p>VISIUM.zip contains the Visium spatial transcriptomics data</p> <p>Molecular cartography.zip contains the Resolve Biosciences molecular cartography spatial transcriptomics data</p>
Data from: Early prediction of in-hospital mortality in patients with congestive heart failure in intensive care unit: a retrospective observational cohort study
<p class="MsoNormal">Objective: Congestive heart failure (CHF) is a clinical syndrome in which heart disease progresses to a severe stage. Risk assessment and early diagnosis of death in patients with CHF are critical to patient prognosis and treatment. The purpose of this study was to establish a nomogram predicting in-hospital death for CHF patients in the ICU.</p> <p>Design: A retrospective observational cohort study.</p> <p>Setting and participants: The data of study from 30,411 CHF patients in the Medical Information Mart for Intensive Care (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD).</p> <p>Primary outcome: In-hospital mortality.</p> <p>Results: The inclusion criteria were met by 15983 subjects, whose in-hospital mortality rate was 12.4%. Multivariate analysis determined that the independent risk factors were age, race, norepinephrine, dopamine, phenylephrine, vasopressin, <a>mechanical</a> <a>ventilation</a>, intubation, HepF, heart rate, respiratory rate, temperature, SBP, AG, BUN, creatinine, chloride, MCV, RDW, and WBC. The C-index of the nomogram (0.767, 95%CI: 0.759–0.779) was <a>superior</a> to that of the traditional SOFA, APSIII and GWTGHF score, indicating its discrimination power. Calibration plots demonstrated that the predicted results are in good agreement with the observed results. The decision curves of the derivation and validation sets both had net benefits.</p> <p>Conclusion: The twenty independent risk factors for in-hospital mortality of CHF patients were age, race, norepinephrine, dopamine, phenylephrine, vasopressin, <a>mechanical</a> <a>ventilation</a>, intubation, HepF, heart rate, respiratory rate, temperature, SBP, AG, BUN, creatinine, chloride, MCV, RDW, and WBC. The nomogram that included these factors accurately predicted the in-hospital mortality of CHF patients. The novel nomogram has the potential to be a clinical practice aided predictive tool for predicting and assessing mortality in CHF patients in the ICU.</p>
Association between depression and sarcopenia in patients with heart failure
<p>Dataset for Association between depression and sarcopenia in patients with heart failure.</p>
Part 2 of Age-related proteostatic imbalance exacerbates heart failure with preserved ejection fraction pathogenesis in old mice
<p>Heart failure with preserved ejection fraction (HFpEF) is a leading cause of hospitalization and death in the elderly. While aging strongly increases the incidence of HFpEF, the specific influences of aging on HFpEF at molecular and pathophysiological levels remain unclear. Here, we show that aged mice, when subjected to chronic metabolic and hypertensive stress (2-hit stress), develop an aggravated cardiometabolic HFpEF phenotype compared to younger counterparts. Aged HFpEF mice also display unique pathological characteristics reminiscent of those found in HFpEF patients. We demonstrate that age-related dysfunction in protein quality control (PQC) exacerbates proteostatic stress in HFpEF. Specifically, we demonstrate that increased protein synthesis induced by 2-hit stress combines with age-related impairment in protein degradation in aged HFpEF hearts, culminating in the accumulation of protein aggregates. These findings underscore the importance of incorporating aging into preclinical HFpEF models and support the therapeutic potentials of targeting PQC mechanisms to ameliorate disease outcomes.</p> <p>The deposited data are lc-ms data acquired on the Thermo QEx-Plus system. For any questions, please contact mike kinter mike-kinter at omrf.org</p> <p>This upload contains the second part of the data. The majority of the data and a complete list of authors can be found in 10.5281/zenodo.10993216</p>
Validation of Soluble Suppression of Tumorigenesis-2, Heart-Type Fatty Acid-Binding Protein and Lipoprotein-Associated Phospholipase A2 as Tools in the Assessment of Chronic Heart Failure
<p>Chronic heart failure (CHF) is a major public health and growing problem, which imposes a relevant burden, with high prevalence and mortality rates. Therefore, reliable cardiac biomarkers are needed to identify individuals with CHF. The goal of this study was to validate the diagnostic utility of some cardiac biomarkers as tools in the assessment of CHF. This was a hospital-based case-control study where a total of 180 participants (aged 30-85 years) consisting of 100 participants with CHF and 80 apparently healthy controls were recruited for the study. Serum troponin I, sST2, H-FABP, and LP-PLA2, were measured using ELISA technique. The value of P≤ 0.05 was regarded as statistically significant. Serum levels of sST2, H-FABP, and Lp-PLA2, were significantly higher in CHF participants when compared with control (p<0.05). Lp-PLA2 had a sensitivity of 99%, specificity of 95%, H-FABP had a sensitivity of 95%, specificity of 100%, and sST2 had a sensitivity of 80%, specificity of 92%, which were all higher when compared with that of Troponin I (20% and 95% respectively).In conclusion, Lp-PLA2, H-FABP, and sST2 were higher in CHF individuals, indicating the possible presence of inflammation and myocardial injury. The markers were more sensitive and specific than troponin I, suggesting their potential use as reliable biomarkers for the assessment of chronic heart failure.</p>
Preliminary report: Reduced hand sensory and motor function in persons living with heart failure.
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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.