Survival Analysis of Diabetes Mellitus Patients Using Parametric, Non-Parametric and Semi-Parametric Approaches: Addis Ababa, Ethiopia (original) (raw)
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2020
Sampling design and sample size determination Th is study is based on retrospective study (i.e. all the eventsexposure had already occurred in the past), which reviews the patient ABSTRACT Diabetes Mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia. The International Diabetes Federation (IDF) suggests that the number of adults living with diabetes worldwide will further expand by 50.7% by 2030. Evidence shows that DM is claiming the lives of more than 4 million people worldwide annually and developing countries account for a substantially high proportion. Similar to other developing countries little is done to quantify the prevalence of chronic diseases and their risk factors in Ethiopia. The general objective of this study has been to model survival of diabetic patients who were under follow-up at Nekemte referral Hospital. This study incorporates secondary data. Of 1953 target population patient 354 are used and randomly selected from the study area. On parametric and semi parametric survival model are used in this study. In this study, a sample of 354 diabetic patients was considered. The medical cards of those patients were reviewed, out of which 160 were female and 194 were male. Among those patients 13.3% and 86.7% were died and censored respectively. The result of the study reveals that a sample of 354 diabetic patients was considered and of those patients was reviewed, out of which 160 were female and 194 were male. Among those patients 13.3% and 86.7% were died and censored respectively. The result of multivariable cox regression model reveals that Survival of diabetic patients was signifi cantly related with body mass index, alcohol use, tobacco use, type of diabetic disease diagnosed, blood pressure, and family history of diabetes mellitus. Therefore, it conclude that Patients involved in risky behaviors such as taking alcohol, smoking cigarette, overweight, high blood pressure, and positive family history of diabetics, have higher death rate. The cox proportional model is fi t the data well. This study recommend that the government and concerned bodies should work on perception about the disease and its signifi cant risk factors, so that patients should be well informed about the disease, early diagnose and to follow up their diabetes mellitus status to minimize the signifi cant risk of death.
Analysis of Reported Cases of Diabetes Disease in Nigeria: A Survival Analysis Approach
International Journal of Sustainable Development and Planning
The goal of this study is to look at the survival time distribution for diabetes patients at the National Hospital Abuja, taking into account a variety of variables. The Kaplan Meier-estimator indicated that there is no statistically significant difference in the distribution of survival time by sex, despite the fact that married patients were seen to live longer than single patients. Patients in urban and rural areas had the same estimated survival distribution after testing. It is observed that the Cox proportional model was significant when tested since the p-value = 0.000 was less than the 0.05 threshold. The distribution of survival time for patients with diabetes is shown to be substantially different for patients of the four age categories included in the study, indicating that the relative risk of patients is based on age. Every patient is predicted to acquire the danger at about the same time, with no sex-related multiplication impact. It was found out that the disease'...
2021
AimThe study aimed to determine the time to recovery of diabetic patients who have been treated in the hospital under follow-up. Subject and MethodsA retrospective cohort study design was carried out. The fast blood glucose level of diabetic patients who are under follow-up in the hospital was measured from 2016 to 2020. One thousand seven hundred diabetic patients were included in the study. Kaplan-Meier, Log-rank test, global test, Schoenfeld residuals, and Cox-PH model were used for statistical analysis.ResultsOut of the total of 1278 patients, 27.4% were censored (withdrawal from follow-up) and 72.6% recovered from the diabetic disease. For sex, the expected hazard is 1.322 times higher in males than female diabetic patients or there is a 32.2% increase in the expected hazard in males relative to female diabetic patients. For Spdrt, The expected hazard is 1.164 times higher in the patients who had taken leute than diabetic patients who took doanied. For regimen, the expected haz...
2018
Diabetes is a complex, chronic illness that occurs either when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin it produces. Globally, 415 million (340-536 million) people have diabetes in 2015 with regional prevalence of 8.8% (7.2-11.4%) by 2040 this figure will expect rise to 642 million (521-829 million) with predicted prevalence rate of 10.4% (8.5-13.5%) and more than 22 million people in the African Region; by 2040 this figure will almost double (IDF, 2015).The statistical result of World health organization estimated that the number of cases of diabetics in Ethiopia to be about 796,000 in 2000, and projected that it would increase to about 1,820,000 by the year 2030 (WHO, Diabetes estimates and Projections, 2003).But,according to the report of international diabetes federation atlas in 2017 there were around 2,567,900 [1,094,000-3,795,400] million diabetes cases in Ethiopia in 2017 (IDF atlas, 2017). The general objective of the ...
Survival Analysis of Diabetes Mellitus Patients Using Semiparametric Approach
Communications in Computer and Information Science
The disease that attacks the human body and often gets special attention is diabetes. Diabetes mellitus is a non-communicable disease that is most commonly suffered by the world's population. Diabetes is a condition that interferes with the body's ability to process glucose in the blood, otherwise known as blood sugar. So, most patients have survival of only a few months. Therefore, research was conducted on the survival of people with diabetes mellitus and factors that affect it during the event. The method used in this study was the cox regression model. The results obtained from this study are three variables that significantly affect the survival of diabetes mellitus patients, namely Genetics, Age, and Diet. Then the variables Genetic, Age, and Diet became part of Cox Proportional Hazard (PH) modeling.
Background: Diabetes is one of the most widespread chronic disease. In Ethiopia, it has been endemic and it is widely distributed. The aim of this paper was to address the determinant factors of diabetes patients blood glucose level over time with respect to different covariates. Methods: Institution based longitudinal retrospective study was done to explore the factors affecting the change of blood glucoseof diabetes patients by taking the routinely collected information from the patients card at FelegeHiwot referral hospital, Bahir Dar, Ethiopia. To analyze the data, generalized estimating equation was used and data was entered in SPSS version21 and analyzed with SAS 9.2. Results: Records of 180 diabetic patients enrolled from 2014 September to 2015 August were analyzed. The results revealed that the blood glucose level (mg/dl)was decreased over time, there is an interaction effect between the treatment sex and follow up time and the rate is statistically different for male and female diabetic patients. Conclusions: The blood glucose rate of change of female is less than that of males; this may be due to different reasons like, maternity, stress and hormonal changes. The blood glucose is decreasing overtime if diabetic patients adhered properly. Background Diabetes is a group of diseases characterized by high blood glucose (blood sugar). When a person has diabetes, the body either does not produce enough insulin or is unable to use its own insulin effectively. Glucose builds up in the blood and causes a condition that, if not controlled, can lead to serious health complications and even death. The risk of death for a person with diabetes is twice the risk of a person of similar age who does not have diabetes[1]. Diabetes, a lifelong disease that increases sugar levels in the blood, affects over 366 million people in the globe. Paul Madden, Project Hope's senior advisor for non-communicable diseases, reported thatthe disease is rapidly spreading throughout sub-Saharan Africa, and even other developing countries around the world, mainlybecause of lifestyle changes. The prevalence of diabetic in the world was estimated to be 4% in the year 1995 and estimated to be 5.4% by the year 2025. Abouteighty percent of diabetes deaths occur in low and middle income countries. At 2011, around fourteen million adults in the Africa Region are estimated to have diabetes, with a regional prevalence of 3.8%[1].
Cox Proportional Hazard Regression Survival Analysis for Type 2 DiabeteS Mellitus
2021
One of the most widely used methods of survival analysis is Cox proportional hazard regression. It is a semiparametric regression used to investigate the effects of a number of variables on the dependent variable based on survival time. Using the Cox proportional hazard regression method, this study aims to estimate the factors that influence the survival of patients with type 2 diabetes mellitus. The estimated parameter values, as well as the Cox Regression equation model, were also investigated. A total of 1293 diabetic patients with type 2 diabetes were studied, with data taken from medical records at PKU Muhammadiyah Hospital in Yogyakarta, Indonesia. These variables have regression coefficients of 1.36, 1.59,-0.63, 0.11, and 0.51, respectively. Furthermore, the results showed the hazard ratio for female patients was 1.16 times male patients. Patients on insulin treatment had a 4.92-fold higher risk of death than those on other therapy profiles. Patients with normal blood sugar levels (GDS 140 mg/dl) had a 1.12 times higher risk of death than those with other blood glucose levels. Type 2 diabetes mellitus is a challenge for many Indonesians, in addition to being a deadly condition that was initially difficult to diagnose. As a result, patient survival analysis is needed to reduce the patient's risk of death.
PLOS ONE, 2019
To estimate time to first optimal glycaemic control and identify prognostic factors among type 2 diabetes mellitus (T2DM) patients attending diabetes clinic of public teaching hospitals in Addis Ababa, Ethiopia. Methods A retrospective chart review study was conducted at diabetes clinic of Addis Ababa's public teaching hospitals among a randomly selected sample of 685 charts of patients with T2DMwho were on follow up from January 1, 2013 to June 30, 2017. Data was collected using data abstraction tool. Descriptive statistics, Kaplan Meier plots, median survival time, Log-rank test and Cox proportional hazard survival models were used for analysis. Results Median time to first optimal glycaemic control among the study population was 9.5 months. Factors that affect time to first optimal glycaemic control were age group (HR = 0.635, 95%
BMC Endocrine Disorders, 2021
Type 2 Diabetes (T2D) represents one of the leading causes for hospital admissions and outpatient visits. Hence, T2D continuously imposes a significant burden to healthcare systems. The aim of this study was to assess predictors of hospital admission, readmission rates, and length of hospital stay among T2D patients in government hospitals of Eastern Ethiopia from 2013 to 2017. This study utilized retrospective data from a cohort of T2D patients following their treatment in government hospitals in Harari regional state of Ethiopia. Predictor of hospital admission was determined using parametric survival analysis methods. The readmission rate and length of hospital stay were determined by Poisson regression and mixed effect Poisson regression, respectively. All association were performed at 95% confidence level. Significance of association with determinants was reported using the hazard rate for hospital admission, and the incidence rate for readmission and length of hospital stay. O...
Prognostic indices of diabetes mortality
Ethnicity & disease, 2007
Diabetes mellitus is an important cause of morbidity and mortality worldwide and the burden associated with it is felt more in developing countries. Communicable diseases, as opposed to non-communicable diseases, remain a top priority in developing countries like Nigeria. This report sets out to highlight the current status of diabetes-related hospitalizations in Nigeria and also to make comparisons with past reports. This goal will be achieved primarily by determining the prognostic factors associated with diabetes mortality and also noting the duration of hospital stay for the major causes of diabetes deaths. From January through December 2006, subjects with diabetes mellitus (DM) in a tertiary hospital in Nigeria were prospectively studied after admission to assess their shortterm outcome which was defined as death. The total mortality, causes of death, associated complications and duration of hospital stay were noted. The predictive factors for DM morbidity were evaluated using ...