Parameters related to diagnosing hypertrophic cardiomyopathy in cats.

Abstract

Background: The initial diagnostic markers are important for general practitioners to identify cats suspected of having cardiac disease, particularly hypertrophic cardiomyopathy (HCM).

Aim: The aim of this study is to investigate the indicators that suggest feline cardiac disease, especially HCM.

Methods: This is a retrospective study, using the data from 354 cats, to identify various clinical parameters that indicate the presence of cardiac disease in cats in order to develop a model to predict the likelihood of HCM in cats. Among all the parameters gathered, heart sound and LA size are the most significant in predicting the likelihood of HCM in cats.

Results: After undergoing statistical analysis, we created a formula that could help screen cats with HCM and normal cats before further diagnosis, such as echocardiography. The formula Y₁ = -3.637 +2.448 (LA size) +2.683 (murmur) +1.274 (gallop) is the fittest model with an area under curve from the ROC analysis of 0.889. A new set of data was used to validate the model. This predictive model has 40% accuracy but correctly predicts 90% of the truly normal cats, making this model beneficial in helping veterinarians exclude truly normal cats from cats suspected of having HCM.

Conclusion: The model may assist in distinguishing normal cats from those suspected of having HCM. Further diagnosis with echocardiography remains the gold standard for the final diagnosis of cardiac diseases in cats.