Analysis of factors influencing survival time of patients with heart failure

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Abstract

Analysis of factors influencing survival time of patients with heart failure. This paper deals with statistical analysis of some predictors influencing the survival of cardiac dysfunctional cases diagnosed in a specialized medical center with the aim of estimating major contributors of heart failure patients’ period of survival. The design of this research focused on a metropolis where some cohorts were diagnosed over a given period of time. This study used two distinct models of survival analysis to investigate the incidence of heart failure and estimate the relevant factors of the survival of victims. The Kaplan Meier model and the Cox regression model were adopted. The output of the paper was obtained using the SPSS 23.0 to estimate the model parameters yielding the outcomes indicating that the overtime, the potency of surviving heart attack is drastically poor. The survivor function connotes the chances that a patient survives from the time of beginning to sometimes beyond the period. The survival experience of the population under investigation is estimated by the Kaplan Meier method. In the paper, Kaplan Meier estimated the probability of surviving the attack within the cohort group at the point of diagnosis as 0.42 in 2013 which really decayed in 2019 to 0.006 depicting the reduced chances of the patients surviving the attack over the period Cox regression analysis uncovered that using a  0.05, the p-values estimated that age, hypertension and blood pressure contribute to the surviving heart dysfunction inpatients being diagnosed.