Predicting Survival of Heart Failure Patients Using the Cox Proportional Hazards Model

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Abstract Background: Cardiovascular diseases kill approximately 17 million people globally every year, and they mainly exhibit as myocardial infarctions and heart failures. The main purpose of this study was to predict the survival of heart failure patients using the Cox Proportional Hazards Model. Method: In this paper, we analyze a dataset of 299 patients with heart failure collected in 2015, of whom 105 were women and 194 were men aged between 40 and 95 years old. With the support of the RStudio statistical Programme, the Cox Proportional Hazards Model was estimated to determine the survival of heart failure patients. Results: Each additional year of patient age increases the hazard (HR = 1.0446; p-value = 8.41e-07). As a result, survival decreases as the age of the heart patient increases. Most importantly, heart failure patients with hypertension (high blood pressure) had a worse survival than patients without hypertension (HR = 1.5948; p-value = 0.0284). Furthermore, when all other factors were held constant, increased ejection fraction was found to decrease the hazard (HR = 0.9495; p-value = 2.57 e-07) and improve survival, whereas increased creatinine was found to increase the hazard (HR = 1.4167; p-value = 1.05 e-07), hence reducing survival. Conclusions: These findings are expected to underscore the significance of the studied factors in predicting mortality from heart failure in Pakistan. Given the vital role of the heart, predicting heart failure remains a priority for medical practitioners and physicians, highlighting the importance of advancing predictive models for effective management.

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