Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

143

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

143 results for “cardiac arteries”

Learn how ShareScore rates datasets ↗
ClinicalTrials.gov12/100

Devitalized Non-valved Pulmonary Artery Allograft Implant for the Repair of Congenital Cardiac Abnormalities

ClinicalTrials.gov study NCT00411658. IPD Sharing: Not stated. Countries: 0. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
zenodo8/100

Data set from the article Bari V, Vaini E, Pistuddi V, Fantinato A, Cairo B, De Maria B, Ranucci M, Porta A. Short-term multiscale complexity analysis of cardiovascular variability improves low cardiac output syndrome risk stratification after coronary artery bypass grafting. Physiol Meas. 2019 Apr 26;40(4):044001. doi: 10.1088/1361-6579/ab12f0. PMID: 30909175.

<p>Data set from the article Bari V, Vaini E, Pistuddi V, et al. Short-term multiscale complexity analysis of cardiovascular variability improves low cardiac output syndrome risk stratification after coronary artery bypass grafting.&nbsp;<em>Physiol Meas</em>. 2019;40(4):044001. Published 2019 Apr 26. doi:10.1088/1361-6579/ab12f0</p> <p>This is the abstract:</p> <p><strong>Background:&nbsp;</strong>Low cardiac output syndrome (LCOS) is a myocardial dysfunction leading to systemic hypoperfusion, favored by particular conditions of the autonomic nervous system. LCOS is one of the adverse events that might occur after cardiac surgery.</p> <p><strong>Objective:&nbsp;</strong>The aim is to test the hypothesis that short-term multiscale complexity (MSC) analysis of heart period (HP) and systolic arterial pressure (SAP) variability series in the frequency bands typical of cardiovascular control could be fruitfully exploited in identifying subjects at risk of developing LCOS after coronary artery bypass graft (CABG).</p> <p><strong>Approach:&nbsp;</strong>HP and SAP beat-to-beat series were derived from electrocardiogram (ECG) and invasive arterial pressure (AP) signal acquired in 128 patients scheduled for CABG before (PRE) and after (POST) the induction of general anesthesia with propofol and remifentanil. Subjects were labeled as LCOS (n = 14) and noLCOS (n = 114) according to the LCOS development. MSC markers were calculated as the complement to 1 of the modulus of the average position of the poles dropping in the low-frequency (LF, 0.04-0.15 Hz) and high-frequency (HF, 0.15-0.5 Hz) bands as derived from the autoregressive model of HP and SAP series. Traditional time and frequency domain indexes were also calculated.</p> <p><strong>Main results:&nbsp;</strong>Traditional parameters were able to assess the depression of the cardiovascular regulation induced by general anesthesia, but showed weak performances in differentiating LCOS and noLCOS groups. Conversely, HP complexity in LF band and SAP complexity in HF band assessed during POST remained associated with LCOS even after entering a multivariate logistic regression model adjusted for clinical and demographic factors.</p> <p><strong>Significance:&nbsp;</strong>The MSC approach can be fruitfully applied to improve risk stratification for LCOS after CABG likely because MSC markers describe the dysfunction of the sympathetic control and the impairment of the mechanical properties of the heart in the LCOS group.</p>

restrictedMay 2020View details →
zenodo8/100

Data set from the article Petrini M, Alì M, Cannaò PM, Zambelli D, Cozzi A, Codari M, Malavazos AE, Secchi F, Sardanelli F. Epicardial adipose tissue volume in patients with coronary artery disease or non-ischaemic dilated cardiomyopathy: evaluation with cardiac magnetic resonance imaging. Clin Radiol. 2019 Jan;74(1):81.e1-81.e7. doi: 10.1016/j.crad.2018.09.006. Epub 2018 Oct 15. PMID: 30336943.

<p>Data set from the article Petrini M, Al&igrave; M, Canna&ograve; PM, Zambelli D, Cozzi A, Codari M, Malavazos AE, Secchi F, Sardanelli F. Epicardial adipose tissue volume in patients with coronary artery disease or non-ischaemic dilated cardiomyopathy: evaluation with cardiac magnetic resonance imaging. Clin Radiol. 2019 Jan;74(1):81.e1-81.e7. doi: 10.1016/j.crad.2018.09.006. Epub 2018 Oct 15. PMID: 30336943.</p> <p>&nbsp;</p> <p>This is the abstract:</p> <p><strong>Aim: </strong> To compare the amount of epicardial adipose tissue (EAT) in patients with coronary artery disease (CAD) or non-ischaemic dilated cardiomyopathy (NIDCM) with that in patients with negative cardiac magnetic resonance imaging (CMR).</p> <p><strong>Materials and methods: </strong> One hundred and fifty patients (median age 57 years, interquartile range [IQR] 46-66 years) who underwent CMR were evaluated retrospectively: 50 with CAD, 50 with NIDCM, and 50 with negative CMR. For each patient, the EAT mass index (EATMI) to body surface area, end-diastolic volume index (EDVI), end-systolic volume index (ESVI), stroke volume (SV), ejection fraction (EF) for both ventricles, and left ventricle (LV) mass index were estimated. Intra and inter-reader reproducibility was tested in a random subset of 30 patients, 10 for each group. Mann-Whitney U test, Kruskal-Wallis test, Spearman&#39;s correlation, and Bland-Altman statistics were used.</p> <p><strong>Results: </strong> The EATMI in CAD patients (median 15.7 g/m<sup>2</sup>, IQR 8.3-25.7) or in NIDCM patients (15.9 g/m<sup>2</sup>, 11.5-18.1) was significantly higher than that in negative CMR patients (9.1 g/m<sup>2</sup>, 6-12; p&lt;0.001 both). No significant difference was found between CAD and NIDCM patients (p=1.000). A correlation between EATMI and LV mass index was found in NIDCM patients (r=0.455, p=0.002). Intra- and inter-reader reproducibility were up to 80% and 72%, respectively.</p> <p><strong>Conclusion: </strong> Patients with NIDCM or CAD exhibited an increased EATMI in comparison to negative CMR patients. CMR can be used to estimate EAT with good reproducibility.</p>

restrictedJun 2020View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record