Work

Advance Modalities in Diagnosis and Prediction of Canine Cardiac Diseases

Year: 2025
Type: article
Abstract: Background: Cardiomyopathy is a significant health concern in dogs, affecting their heart function and overall well-being. This study aimed to explore the prevalence of cardiomyopathies, the role of thoracic radiographs in detecting cardiac diseases and the use of electrocardiographic and echocardiographic findings to understand the condition better. Methods: A total of 40 client-owned dogs were included in this study, categorized into three groups based on their clinical condition: 18 dogs with a normal heart size (Group 1), 14 dogs in the preclinical stage of cardiomyopathy (Group 2) and 8 dogs with confirmed clinical cardiomyopathy (Group 3). Group 3 exhibited significantly higher VHS and CTR values, suggesting advanced heart disease. Echocardiographic measurements, including the Right Parasternal Short Axis (RPS) views, showed an increase in left atrial size and left atrial to aortic ratio (LA/Ao) in Groups 2 and 3. Result: M-mode echocardiography revealed a decrease in ejection fraction (EF%) and fractional shortening (FS%) in the clinical group, pointing to poor heart function. Additionally, End-Point Septal Separation (EPSS) was significantly elevated in Group 3, indicating left ventricular dysfunction. The study concludes that regular monitoring of heart size through radiographs and echocardiographic parameters is essential for early detection and management of cardiomyopathies in dogs. The findings suggest that older dogs, particularly male dogs and certain breeds, are at higher risk of developing cardiomyopathies. Early detection using these diagnostic tools can improve the prognosis by allowing for timely intervention. This research emphasizes the importance of using a combination of radiographic, electrocardiographic and echocardiographic evaluations in managing and understanding cardiomyopathy in dogs.
Authors: Patil Prasad Sarjerao, Anjan Kumar Sahoo, Jayakrushna Das, Aditya prasad Acharya, Sudhamayee Meher, Jagyaseni Meher
Language: English
Field: Medicine
Open Access status: hybrid
OpenAlex ID: W4413809084
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