Quantification of mitral regurgitation in anatolian shepherd dogs with asymptomatic degenerative mitral valve disease

WOS: 000385716600007
Degenerative mitral valvular disease (DMVD) is the most frequent cardiac disease, causing mitral regurgitation (MR) in dogs. The purpose of this study was to compare the ratio of the regurgitant jet area (RJA) to the left atrial area (LAA) (RJA/LAA) with subtracting method to quantify regurgitant volume (RegV) and regurgitant fraction (RF) in asymptomatic Anatolian Shepherd Dogs (ASHs) with DMVD. Thirty-eight ASHs with DMVD were used as experimental group. The control group consisted of 35 healthy ASHs. In 38 ASHs with DMVD (20 B1 dogs and 18 B2 dogs), the severity of MR was assessed by RJA/LAA and subtraction method. No differences were noted between the assays measuring the severity of MR by chi 2 analysis. The observed agreement between the assays was 81% for RJA/LAA vs RegV and was 73% for RJA/LAA vs RF, and the kappa statistic values for RJA/LAA vs RegV and for RJA/LAA vs RF were 0.63 (substantial agreement) and 0.50 (moderate agreement), respectively. Our results indicate that each quantification method was valuable to estimate the acuteness of the disease in ASHs with MR and all were in good accordance with the echocardiographic heart size and N-terminal Pro-Brain Natriuretic Peptide (NT-proBNP) measurements. Therefore, the each of these non-invasive methods may be functional to serially estimate the acuteness of MR in DMVD in order to monitor the progression of disease. Future studies have to evaluate, if these will be useful to anticipate the risk or time of decompensation in asymptomatic dogs. (C) 2016 PVJ. All rights reserved
Scientific and Technical Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK); Selcuk University Scientific Research Project Council (SUBAP)
This study was supported by both The Scientific and Technical Research Council of Turkey (TUBITAK) and Selcuk University Scientific Research Project Council (SUBAP). We are thankful to Dr. Seref Inal for his excellent assistance to statistical analyses.