• Je něco špatně v tomto záznamu ?

New Imaging Markers of Clinical Outcome in Asymptomatic Patients with Severe Aortic Regurgitation

R. Kočková, H. Línková, Z. Hlubocká, A. Pravečková, A. Polednová, L. Súkupová, M. Bláha, J. Malý, E. Honsová, D. Sedmera, M. Pěnička,

. 2019 ; 8 (10) : . [pub] 20191011

Jazyk angličtina Země Švýcarsko

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc19044215

Grantová podpora
17-28265A Ministerstvo Zdravotnictví Ceské Republiky

Background: Determining the value of new imaging markers to predict aortic valve (AV) surgery in asymptomatic patients with severe aortic regurgitation (AR) in a prospective, observational, multicenter study. Methods: Consecutive patients with chronic severe AR were enrolled between 2015-2018. Baseline examination included echocardiography (ECHO) with 2- and 3-dimensional (2D and 3D) vena contracta area (VCA), and magnetic resonance imaging (MRI) with regurgitant volume (RV) and fraction (RF) analyzed in CoreLab. Results: The mean follow-up was 587 days (interquartile range (IQR) 296-901) in a total of 104 patients. Twenty patients underwent AV surgery. Baseline clinical and laboratory data did not differ between surgically and medically treated patients. Surgically treated patients had larger left ventricular (LV) dimension, end-diastolic volume (all p < 0.05), and the LV ejection fraction was similar. The surgical group showed higher prevalence of severe AR (70% vs. 40%, p = 0.02). Out of all imaging markers 3D VCA, MRI-derived RV and RF were identified as the strongest independent predictors of AV surgery (all p < 0.001). Conclusions: Parameters related to LV morphology and function showed moderate accuracy to identify patients in need of early AV surgery at the early stage of the disease. 3D ECHO-derived VCA and MRI-derived RV and RF showed high accuracy and excellent sensitivity to identify patients in need of early surgery.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc19044215
003      
CZ-PrNML
005      
20200109095609.0
007      
ta
008      
200107s2019 sz f 000 0|eng||
009      
AR
024    7_
$a 10.3390/jcm8101654 $2 doi
035    __
$a (PubMed)31614523
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a sz
100    1_
$a Kočková, Radka $u Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague 14021, Czech Republic. radka.kockova@ikem.cz. Faculty of Medicine in Hradec Králové, Charles University, Šimkova 870, Hradec Králové 500 03, Czech Republic. radka.kockova@ikem.cz.
245    10
$a New Imaging Markers of Clinical Outcome in Asymptomatic Patients with Severe Aortic Regurgitation / $c R. Kočková, H. Línková, Z. Hlubocká, A. Pravečková, A. Polednová, L. Súkupová, M. Bláha, J. Malý, E. Honsová, D. Sedmera, M. Pěnička,
520    9_
$a Background: Determining the value of new imaging markers to predict aortic valve (AV) surgery in asymptomatic patients with severe aortic regurgitation (AR) in a prospective, observational, multicenter study. Methods: Consecutive patients with chronic severe AR were enrolled between 2015-2018. Baseline examination included echocardiography (ECHO) with 2- and 3-dimensional (2D and 3D) vena contracta area (VCA), and magnetic resonance imaging (MRI) with regurgitant volume (RV) and fraction (RF) analyzed in CoreLab. Results: The mean follow-up was 587 days (interquartile range (IQR) 296-901) in a total of 104 patients. Twenty patients underwent AV surgery. Baseline clinical and laboratory data did not differ between surgically and medically treated patients. Surgically treated patients had larger left ventricular (LV) dimension, end-diastolic volume (all p < 0.05), and the LV ejection fraction was similar. The surgical group showed higher prevalence of severe AR (70% vs. 40%, p = 0.02). Out of all imaging markers 3D VCA, MRI-derived RV and RF were identified as the strongest independent predictors of AV surgery (all p < 0.001). Conclusions: Parameters related to LV morphology and function showed moderate accuracy to identify patients in need of early AV surgery at the early stage of the disease. 3D ECHO-derived VCA and MRI-derived RV and RF showed high accuracy and excellent sensitivity to identify patients in need of early surgery.
655    _2
$a časopisecké články $7 D016428
700    1_
$a Línková, Hana $u Department of Cardiology, Royal Vinohrady University Hospital, Prague 10034, Czech Republic. hana.linkova@fnkv.cz.
700    1_
$a Hlubocká, Zuzana $u Department of Cardiology, General University Hospital, Prague 12808, Czech Republic. zuzana.hlubocka@vfn.cz.
700    1_
$a Pravečková, Alena $u Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague 14021, Czech Republic. alena.praveckova@ikem.cz.
700    1_
$a Polednová, Andrea $u Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague 14021, Czech Republic. andrea.polednova@ikem.cz.
700    1_
$a Súkupová, Lucie $u Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague 14021, Czech Republic. lucie.sukupova@gmail.com.
700    1_
$a Bláha, Martin $u Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague 14021, Czech Republic. martin.blaha@ikem.cz.
700    1_
$a Malý, Jiří $u Department of Cardiothoracic surgery, Institute for Clinical and Experimental Medicine, Prague 14021, Czech Republic. jiri.maly@ikem.cz.
700    1_
$a Honsová, Eva $u Institute for Clinical and Experimental Medicine, Clinical and Transplant Pathology Centre, Prague 14021, Czech Republic. eva.honsova@ikem.cz.
700    1_
$a Sedmera, David $u First Faculty of Medicine, Institute of Anatomy, Charles University in Prague, Prague 12800, Czech Republic. david.sedmera@lf1.cuni.cz.
700    1_
$a Pěnička, Martin $u Cardiovascular Center Aalst, OLV Clinic, 9300, Belgium. martin.penicka@olvz-aalst.be.
773    0_
$w MED00195462 $t Journal of clinical medicine $x 2077-0383 $g Roč. 8, č. 10 (2019)
856    41
$u https://pubmed.ncbi.nlm.nih.gov/31614523 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y a $z 0
990    __
$a 20200107 $b ABA008
991    __
$a 20200109095938 $b ABA008
999    __
$a ind $b bmc $g 1480804 $s 1082885
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2019 $b 8 $c 10 $e 20191011 $i 2077-0383 $m Journal of clinical medicine $n J Clin Med $x MED00195462
GRA    __
$a 17-28265A $p Ministerstvo Zdravotnictví Ceské Republiky
LZP    __
$a Pubmed-20200107

Najít záznam

Citační ukazatele

Možnosti archivace