Evaluating Determinants Of Survival Time In Heart Failure Patients Using Cox Proportional Hazards Regression

Abstract

Heart failure represents a severe chronic cardiovascular disorder and remains a major contributor to global mortality rates. Identifying specific risk factors that impact patient survivability is crucial for enhancing clinical interventions. This research investigates the determinants influencing the survival duration of heart failure patients by applying the Cox Proportional Hazards (Cox PH) regression approach. The primary objective of this study is to provide information on the main causes of heart failure and the factors that can influence the condition. Utilizing a secondary dataset of 299 patient records sourced from Kaggle, the study analyzed several variables, including age, gender, anemia, diabetes, smoking habits, and hypertension. The analytical findings reveal that age serves as the most critical determinant; individuals older than 65 face a 2.04 times greater mortality risk than younger cohorts. Furthermore, comorbidities such as anemia and hypertension significantly elevate this risk, presenting hazard ratios of 1.44 and 1.46, respectively. These outcomes emphasize the critical role of age and pre-existing medical conditions in the prognosis of heart failure, offering valuable perspectives for medical practitioners to design targeted therapeutic strategies that prolong patient survival.