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.
25
datasets available to search
ShareScore release 0.9.0
Dataset results
25 results for “mitral valve prolapse”
Mitral valve interstitial Tissue: Myxomatous P2 prolapse of the mitral valve vs. Control
GEO Series GSE109744. Homo sapiens. 24 samples. Type: Expression profiling by array.
Dataset related to the article "Multimodality imaging assessment of mitral annular disjunction in mitral valve prolapse"
<p>This record contains raw data related to the article "Multimodality imaging assessment of mitral annular disjunction in mitral valve prolapse".</p> <p><strong>Objective </strong>Mitral annular disjunction (MAD) is an abnormality linked to mitral valve prolapse (MVP), possibly associated with malignant ventricular arrhythmias. We assessed the agreement among different imaging techniques for MAD identification and measurement.</p> <p><strong>Methods </strong>131 patients with MVP and significant mitral regurgitation undergoing transthoracic echocardiography (TTE) and cardiac magnetic resonance (CMR) were retrospectively enrolled. Transoesophageal echocardiography (TOE) was available in 106 patients. MAD was evaluated in standard long-axis views (four-chamber, two-chamber, three-chamber) by each technique.</p> <p><strong>Results </strong>Considering any-length MAD, MAD prevalence was 17.3%, 25.5%, 42.0% by TTE, TOE and CMR, respectively (p<0.05). The agreement on MAD identification was moderate between TTE and CMR (κ=0.54, 95% CI 0.49 to 0.59) and good between TOE and CMR (κ=0.79, 95% CI 0.74 to 0.84). Assuming CMR as reference and according to different cut-off values for MAD (≥2 mm, ≥4 mm, ≥6 mm), specificity (95% CI) of TTE and TOE was 99.6 (99.0 to 100.0)% and 98.7 (97.4 to 100.0)%; 99.3 (98.4 to 100.0)% and 97.6 (95.8 to 99.4)%; 97.8 (96.2 to 99.3)% and 93.2 (90.3 to 96.1)%, respectively; sensitivity (95% CI) was 43.1 (37.8 to 48.4)% and 74.5 (69.4 to 79.5)%; 54.0 (48.7 to 59.3)% and 88.9 (85.2 to 92.5)%; 88.0 (84.5 o 91.5)% and 100.0 (100.0 to 100.0)%, respectively. MAD length was 8.0 (7.0-10.0), 7.0 (5.0-8.0], 5.0 (4.0-7.0) mm, respectively by TTE, TOE and CMR. Agreement on MAD measurement was moderate between TTE and CMR (ρ=0.73) and strong between TOE and CMR (ρ=0.86).</p> <p><strong>Conclusions </strong>An integrated imaging approach could be necessary for a comprehensive assessment of patients with MVP and symptoms suggestive for arrhythmias. If echocardiography is fundamental for the anatomic and haemodynamic characterisation of the MV disease, CMR may better identify small length MAD as well as myocardial fibrosis.</p>
Dataset related to the article 'Diagnostic Accuracy of Transillumination in Mitral Valve Prolapse: Side-by-Side Comparison of Standard Transthoracic Three-Dimensional Echocardiography against Surgical Findings'
<p>This record contains raw data related to the article 'Diagnostic Accuracy of Transillumination in Mitral Valve Prolapse: Side-by-Side Comparison of Standard Transthoracic Three-Dimensional Echocardiography against Surgical Findings'</p> <p>In patients with mitral valve (MV) prolapse (MVP) eligible for surgery, three-dimensional echocardiography (3DE) is routinely used for pre-operative assessment. Despite the worldwide use of transesophageal echocardiography in this context, transthoracic echocardiography (TTE) allows accurate noninvasive evaluation of MV anatomy and pathology in patients with good acoustic windows. Transillumination (TI) is a new 3D tool that improves the visualization of cardiac structures due to shadow effects achieved by the use of a virtual light source. We aimed to compare the diagnostic accuracy of TTE TI side-by-side with standard 3DE (s3DE) display in patients undergoing surgery for MVP, using surgical valve inspection as a reference standard.</p> <p>We prospectively studied 59 patients with good acoustic windows on TTE, undergoing surgery for MVP. The study was approved by the institutional review board with a written informed consent. 3D MV analysis, including evaluation of scallops, chordal rupture and cleft was performed using s3DE and TI. Data were acquired by two experienced operators using zoomed acquisition mode over 4 to 6 cardiac cycles and processed by adjusting gain, brightness and smoothing. For TI images, the virtual light source was set in the left ventricle to enhance MV visualization. At the end of each TTE study, a first reader analyzed post-processed s3DE images and, one week later, the TI images. Surgical findings of MV anatomy were collected and agreement was expressed using Cohen’s concordance coefficient kappa, sensitivity, specificity, negative and positive predictive value (NPV, PPV) and overall accuracy. A second reader, blinded to all prior measurements, repeated TI analysis to assess reproducibility using intraclass correlation coefficients (ICC). </p> <p>No differences were noted in etiological diagnosis (Myxomatous vs Fibroelastic Deficiency) between the two 3DE techniques and surgery. Based on s3DE, 53 patients (90%) were diagnosed with P<sub>2</sub> flail secondary to chordal rupture (N=51, 86%) or elongation (N=2, 14%). A cleft was diagnosed in 10 cases (17%), mostly located in the posterior leaflet. Based on TI, 53 patients (88%) were diagnosed with P<sub>2</sub> flail secondary to chordal rupture (N=48, 81%) or elongation (N=5, 19%). In 9 patients (15%) a cleft was found, mainly located in the posterior leaflet.</p> <p>The reproducibility of TI was good for prolapse detection (ICC=0.78) and chordal rupture localization (ICC= 0.73) and fair for cleft identification (ICC= 0.66). Overall, compared to the surgical reference, TI was significantly more accurate than s3DE for the identification of prolapse (94% vs 89%), chordal rupture (98% vs 92%) and cleft localization (87% vs 54%).</p> <p>Specifically, s3DE correctly detected the flail in the majority of patients (N=57, 97%); in 20 patients (34%), at least one scallop was erroneously diagnosed as prolapsing, while in 4 patients (7%), a second prolapsing scallop was missed by s3DE. In 2 cases (3%) the real flail was missed. Agreement between s3DE and surgery in prolapse identification was poor (kappa=0.30). By TI, the flail was correctly diagnosed in 57 cases (97%), while in 7 patients (12%) there was an over-diagnosis and in 4 cases (7%) an under-diagnosis. In 1 patient (2%), the flail was missed by TI. The agreement between TI and surgery in prolapse detection was considerably better (kappa=0.60). A significant difference (p<0.05) was found between s3DE and TI in sensitivity (87% vs 91%), specificity (92% vs 97%), PPV (75% vs 87%) and NPV (96% vs 98%) in scallop’s prolapse identification.</p> <p>Chordal rupture was diagnosed in 51 patients (86%) by s3DE, compared to 45 (76%) cases confirmed by surgery. Among these 45 patients, s3DE correctly identified rupture position in 41 (91%). The agreement between s3DE and surgery was moderate (kappa=0.43). In contrast, TI identified chordal rupture in 48 cases (81%); among 45 patients confirmed by surgery TI detected the correct rupture position in 44 (98%), resulting in a very good agreement (kappa=0.86). Compared to s3DE, TI showed a significant difference (p<0.05) in sensitivity (89% vs 98%), specificity (95% vs 99%), PPV (74% vs 94%) and NPV (96% vs 99%) in chordal rupture recognition.</p> <p>The agreement with surgery in terms of localization of cleft by s3DE was poor (k=0.17). Surgical valve inspection reported 8 cases (14%) with MV cleft (2 cleft of the anterior leaflet and 6 indentations of the posterior leaflet), only one was correctly diagnosed by s3DE, mainly due to signal drop-out. Concordance between TI and surgery in cleft localization was good (kappa=0.67); TI correctly diagnosed 6 out of 8 clefts. For cleft identification, sensitivity (13% vs 75%), specificity (96% vs 99%), PPV (10% vs 67%), and NPV (97% vs 99%) were significantly better (p<0.05) for TI compared to s3DE.</p> <p>Based on our results, in patients undergoing surgery for MVP, TI has the potential to improve the diagnostic accuracy of TTE in anatomical analysis of the MV compared to s3DE, and may thus contribute towards improved personalized presurgical planning.</p> <p> </p>
Putative Circulating MicroRNAs Are Able to Identify Patients with Mitral Valve Prolapse and Severe Regurgitation
<p>This record contains raw data related to the article “Putative Circulating MicroRNAs Are Able to Identify Patients with Mitral Valve Prolapse and Severe Regurgitation”. Mitral valve prolapse (MVP) associated with severe mitral regurgitation is a debilitating disease with no pharmacological therapies available. MicroRNAs (miRNA) represent an emerging class of circulating biomarkers that have never been evaluated in MVP human plasma. Our aim was to identify a possible miRNA signature that is able to discriminate MVP patients from healthy subjects (CTRL) and to shed light on the putative altered molecular pathways in MVP. We evaluated a plasma miRNA profile using Human MicroRNA Card A followed by real-time PCR validations. In addition, to assess the discriminative power of selected miRNAs, we implemented a machine learning analysis. MiRNA profiling and validations revealed that miR-140-3p, 150-5p, 210-3p, 451a, and 487a-3p were significantly upregulated in MVP, while miR-223-3p, 323a-3p, 340-5p, and 361-5p were significantly downregulated in MVP compared to CTRL (<em>p</em> ≤ 0.01). Functional analysis identified several biological processes possible linked to MVP. In addition, machine learning analysis correctly classified MVP patients from CTRL with high accuracy (0.93) and an area under the receiving operator characteristic curve (AUC) of 0.97. To the best of our knowledge, this is the first study performed on human plasma, showing a strong association between miRNAs and MVP. Thus, a circulating molecular signature could be used as a first-line, fast, and cheap screening tool for MVP identification.</p>
Influence of chest conformation on myocardial strain parameters in healthy subjects with mitral valve prolapse
<p>Raw data.</p> <p>Abstract<br> Chest shape might affect myocardial strain parameters. However, the relationship between myocardial strain parameters and<br> chest conformation has not been previously investigated in subjects with mitral valve prolapse (MVP). Between April 2019<br> and May 2020, 60 healthy subjects (50.1 ± 8.6 year/old, 46.6% females) with MVP and mild-to-moderate mitral regurgitation,<br> and 60 controls matched by age, sex, and cardiovascular risk factors were consecutively studied. Participants underwent<br> modified Haller index (MHI) assessment (ratio of chest transverse diameter over the distance between sternum and spine),<br> and transthoracic echocardiography implemented with 2D-speckle tracking analysis. MHI was significantly greater in MVP<br> group than controls (2.6 ± 0.35 vs 2.1 ± 0.23, p < 0.0001). Left ventricular (LV) ejection fraction was similar in MVP and<br> controls (63.5 ± 3.7% vs 64.3 ± 3.9%, p = 0.25). LV regional and global longitudinal (GLS), circumferential (GCS) and radial<br> strain (GRS) parameters and LV peak twist were all significantly lower in MVP compared to controls (all p < 0.0001). MVP<br> subjects with a tight chest (MHI > 2.5, n = 30), and those with MHI ≤ 2.5 (n = 30) were then separately analyzed. A significant<br> impairment in myocardial strain parameters and LV peak twist was documented in MVP subjects with MHI > 2.5, but not in<br> those with MHI ≤ 2.5. MHI showed a strong inverse correlation with LV-GLS (r = − 0.85), GCS (r = − 0.84), GRS (r = − 0.84)<br> and LV peak twist (r = − 0.94). In MVP subjects, impairment of myocardial strain parameters is not due to intrinsic reduction<br> of cardiac contractility function, but it appears to be related to the degree of chest deformity.</p>
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.