This paper answers the following questions: Are there differences in the heart failure time by categorical covariates in the study?
What are the factors associated with survival heart failure time?
Although recent breakthroughs in the care of heart failures (HF) have improved outcomes, owing to the growing evidence base for drugs, implantable devices, and thus the organization of cardiac failure patient follow-up, patients still face an elevated risk of hospitalization and mortality. Identifying the effect factors of HF was critical in order to improve outcomes for patients with HF and, ultimately, save their lives. In Ethiopia, adequate studies to describe the rates of death in hospitalized patients with HF were not conducted.
Inhaltsverzeichnis (Table of Contents)
- Introduction
- Background of study
- Statement of problem
- General objective
- Specific objective
- Significance of the study
- Literature Review
- Overview of health failure
- Health System
- Risk Factors
- Methodology
- Data description and source of data
- Study Variables
- Response Variables
- Independent Variables
- Method of Data Analysis
- Kaplan-Meier estimator method
- Regression Models for Survival Data
- The Cox Proportional Hazards Regression Model
- Estimation of Parameters in proportional hazard model
- Parametric survival Models
- Model selection
- Model diagnostics for Cox PH model
- Results and Discussion
- Descriptive Statistics
- Analysis of survival data
- Kaplan-Meier estimates and log-rank tests
- Results of the Cox proportional hazards model
- Interpretation of the results
- Model Diagnostics
- Assessment of the proportional hazards assumption
- Assessment of Influential Observations
- Comparing Parametric Models
- Conclusions and Recommendations
- Conclusions
- Recommendations
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This study investigates the factors affecting heart failure patients and their survival time. It aims to assess these factors, estimate and interpret the survival and hazard functions, and identify associations between the duration of heart failure and predictor variables.
- Factors affecting heart failure patients.
- Survival and hazard functions of patients with heart failure.
- Association between duration of heart failure and predictors.
- Appropriate model fitting for survival analysis.
- Impact of heart failure on patient prognosis and healthcare systems.
Zusammenfassung der Kapitel (Chapter Summaries)
- Introduction: This chapter provides background information on heart failure (HF), highlighting its global impact on patients and healthcare systems. It also defines the study's objective, specific objectives, and its significance.
- Literature Review: This chapter delves into the existing literature on HF, focusing on the overview of HF, the health system, and risk factors associated with the condition.
- Methodology: This chapter outlines the study design, data description, and source of data. It details the study variables, including response and independent variables, and explains the methods used for data analysis. The chapter discusses Kaplan-Meier estimator methods and regression models for survival data, including the Cox Proportional Hazards Regression Model and parametric survival models. It also covers model selection and diagnostics.
- Results and Discussion: This chapter presents the findings of the study. It includes descriptive statistics, analysis of survival data, Kaplan-Meier estimates, and log-rank tests. It also discusses the results of the Cox proportional hazards model, interpretation of the results, model diagnostics, and comparing parametric models.
Schlüsselwörter (Keywords)
This study focuses on survival analysis, heart failure, risk factors, Cox proportional hazards model, Kaplan-Meier estimator, parametric survival models, model diagnostics, and patient outcomes.
- Quote paper
- Galgalo Jaba (Author), 2023, Heart Failure Patients at Arbaminch General Hospital, Munich, GRIN Verlag, https://www.hausarbeiten.de/document/1318005
