| Title |
Early detection of left ventricular diastolic dysfunction using conventional and speckle tracking echocardiography in a large animal model of metabolic dysfunction
|
|---|---|
| Published in |
The International Journal of Cardiovascular Imaging, December 2017
|
| DOI | 10.1007/s10554-017-1287-8 |
| Pubmed ID | |
| Authors |
Mark M. P. van den Dorpel, Ilkka Heinonen, Sanne M. Snelder, Hendrik J. Vos, Oana Sorop, Ron T. van Domburg, Daphne Merkus, Dirk J. Duncker, Bas M. van Dalen |
| Abstract |
Left ventricular (LV) diastolic dysfunction is one of the important mechanisms responsible for symptoms in patients with heart failure. The aim of the current study was to identify parameters that may be used to detect early signs of LV diastolic dysfunction in diabetic pigs on a high fat diet, using conventional and speckle tracking echocardiography. The study population consisted of 16 healthy Göttingen minipigs and 18 minipigs with experimentally induced metabolic dysfunction. Echocardiography measurements were performed at baseline and 3-month follow-up. The ratio of peak early (E) and late filling velocity (E/A ratio) and the ratio of E and the velocity of the mitral annulus early diastolic wave (E/Em ratio) did not change significantly in both groups. Peak untwisting velocity decreased in the metabolic dysfunction group (- 30.1 ± 18.5 vs. - 23.4 ± 15.5 °/ms) but not in controls (- 38.1 ± 23.6 vs. - 42.2 ± 23.0 °/ms), being significantly different between the groups at the 3-month time point (p < 0.05). In conclusion, whereas E/A ratio and E/Em ratio did not change significantly after 3 months of metabolic dysfunction, peak untwisting velocity was significantly decreased. Hence, peak untwisting velocity may serve as an important marker to detect early changes of LV diastolic dysfunction. |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 5 | 26% |
| Student > Ph. D. Student | 4 | 21% |
| Researcher | 3 | 16% |
| Student > Doctoral Student | 1 | 5% |
| Student > Postgraduate | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 42% |
| Biochemistry, Genetics and Molecular Biology | 2 | 11% |
| Nursing and Health Professions | 1 | 5% |
| Economics, Econometrics and Finance | 1 | 5% |
| Materials Science | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 6 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 December 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from The International Journal of Cardiovascular Imaging
#1,460
of 2,012 outputs
Outputs of similar age
#383,683
of 443,738 outputs
Outputs of similar age from The International Journal of Cardiovascular Imaging
#33
of 42 outputs
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