Abstract
Congestive heart failure is a complex clinical syndrome of functional or structural impairment in the heart. Nowadays heart failure is common and increasing in the world and researches on this area is limited. Therefore the aim of the present study was to analyze and quantify the impact of modelling heart failure survival allowing for covariates with time varying effects known to be independent predictors of overall mortality in this clinical setting. A retrospective cohort study was conducted on CHF patients who were on treatment follow up at both WGH and DRH from January 1, 2010 to December 30, 2016. A total of 487 patients were selected by using simple random sampling from the patient's medical record. Semi parametric, parametric PH models and AFT models was employed to identify the best model which shown as the real causation of factors with the outcome of CHF which is death. The Weibull accelerated failure time model result showed that the risk factors related to accelerating or decelerating the lifespan were age (TR=0.962, p=0.000), Residence (rural) (TR=1.24, p=0.019), Nutritional (Poor) (TR=0.582, p=0.000), Smoking (TR=0.774, p=0.005), Alcoholism (TR=1.394, p=0.010), Diabetes mellitus (TR=0.49, p=0.000), Hypertension (TR=0.079, p=0.019), Stroke (TR=0.799, p=0.014), Coronary Artery disease (TR=0.276, p=0.012), Tuberculosis bacillus (TR=0.103, p=0.000) as a co morbidity and the interaction between age and Tuberculosis bacillus (p=0.000), age and Coronary artery disease (p=0.041), Diabetes mellitus with Hypertension (p=0.000), Hypertension with Nutritional status (p=0.000) and age with time (p=0.000) were found statistically significant. The Weibull accelerated failure time model performed better explain the effect of predictors than other Cox and parametric PH models. Thus, researchers should use parametric AFT models to see regression varying effect covariates. Frequent monitoring and follow up of Patients with heart failure should be adopted.
Highlights
Heart failure is often used to mean chronic heart failure or congestive heart failure (CHF)
The Accelerated Failure Time (AFT) model which is another alternative of the Cox proportional hazards (PH) model when the PH assumption is violate
This study is based on a CHF data set derived from a fiveyear retrospective cohort study of patients CHF follow up in the Woldia general and Dessie referral hospital, Northen Ethiopia with an aim of investigating the comparative performance of Cox and parametric models in a survival analysis of time-to death with CHF data
Summary
Heart failure is often used to mean chronic heart failure or congestive heart failure (CHF). It is impossible to define Heart Failure by a single term as a result it is defined as a complex clinical syndrome in which there is a functional or structural impairment in the heart. This can result from any functional or structural cardiac disorder and it impairs the ventricle’s ability to fill with or eject blood and to deliver oxygenated blood corresponding to the requirements of the metabolizing tissues of the body and/or doing so at increased filling pressures [1]. Heart failure is a major clinical problem worldwide, reaching an epidemic level in the developed world with no known cure at this time. 26 million people worldwide are living with heart failure, and nearly 1 million
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