Abstract

Cardiovascular diseases (CVD) represent a leading cause of global mortality, necessitating proactive identification of risk factors for preventive strategies. This study aimed to uncover prognostic factors influencing cardiovascular patient survival. This study, which used a sample size of 410, showed how to analyze data using simple random sampling. It was conducted at the Tikur Anbessa Specialist Hospital in Addis Ababa, Ethiopia, between September 2012 and April 2016. The Cox PH and stratified Cox regression models were used for the analysis. Findings disclosed a patient cohort where 200 patients (48.8%) persisted through subsequent evaluation, while 210 patients (51.2%) succumbed. Blood pressure (BP), specific CVD, and education levels (EL) exhibited nonproportionalities in scaled Schoenfeld residuals (P < 0.001), prompting necessary stratification. Inadequacies in the Cox proportional hazards model led to favoring the stratified Cox model. Notably, EL, BP, cholesterol level (CL), alcohol use (AU), smoking use (SU), and pulse rate (PR) exhibited statistical significance (P < 0.001). Acceptability of the absence of interaction in the model, with disease types as strata, was established. Different cardiovascular conditions served as distinct groups, where EL, AU, BP, PR, CL, and SU emerged as variables with statistically substantiated significance associated with the mortality of patients with CVD. Implications stress the imperative of widespread awareness among policymakers and the public concerning cardiovascular disease incidence. Such awareness is pivotal in mitigating identified risk factors, guiding more effective healthcare interventions tailored to the multifaceted challenges posed by cardiovascular health.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call