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Parameters related to diagnosing hypertrophic cardiomyopathy in cats
Nonn Tantitamtaworn1, Issaree Adisaisakundet1, Kuerboon Chairit1
1Sixth year Veterinary Student, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand.
Insights
This study developed a formula to help veterinarians screen cats for hypertrophic cardiomyopathy (HCM). The model accurately identifies normal cats, aiding in early detection of feline cardiac disease.
Area of Science:
- Veterinary Cardiology
- Feline Medicine
- Diagnostic Biomarkers
Background:
- General practitioners require initial diagnostic markers to identify cats potentially suffering from cardiac disease, especially hypertrophic cardiomyopathy (HCM).
- Early identification of feline cardiac conditions is crucial for timely intervention and improved patient outcomes.
Purpose of the Study:
- To investigate key indicators suggestive of feline cardiac disease, with a specific focus on hypertrophic cardiomyopathy (HCM).
- To develop a predictive model for assessing the likelihood of HCM in cats based on clinical parameters.
Main Methods:
- A retrospective study involving 354 cats was conducted.
- Clinical parameters, including heart sound and left atrial (LA) size, were analyzed to identify significant predictors of cardiac disease.
- A predictive formula was developed using statistical analysis and validated on a separate dataset.
Main Results:
- A predictive formula (Y₁ = -3.637 + 2.448 (LA size) + 2.683 (murmur) + 1.274 (gallop)) was established, demonstrating an area under the ROC curve of 0.889.
- The model achieved 40% accuracy but demonstrated a high capability of correctly identifying 90% of truly normal cats.
- Heart sound and LA size emerged as the most significant parameters in predicting the likelihood of HCM.
Conclusions:
- The developed model can assist veterinarians in differentiating normal cats from those suspected of having HCM, facilitating more targeted diagnostic approaches.
- While the model aids in screening, echocardiography remains the definitive diagnostic standard for feline cardiac diseases.
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.
