Predictors of time to first symptomatic recovery of major depressive disordered patients: a case study at Jimma University Medical Center.

BACKGROUND: Major Depressive Disorder is one of the most common mental disorders, and it is the main cause of disability worldwide with a prevalence ranging from 7 to 21%. OBJECTIVE: The goal of this study was to predict the time it took for patients with severe depressive disorders at Jimma University Medical Center to experience their initial symptomatic recovery. STUDY DESIGN: The researchers utilized a prospective study design. METHODS: Patients with major depressive disorder were followed up on at Jimma University Medical Center from September 2018 to August 2020 for this study. The Gamma and Inverse Gaussian frailty distributions were employed with Weibull, Log-logistic, and Log-normal as baseline hazard functions. Akaike Information Criteria were used to choose the best model for describing the data. RESULTS: This study comprised 366 patients, with 54.1% of them experiencing their first symptomatic recovery from a severe depressive disorder. The median time from the onset of symptoms to symptomatic recovery was 7 months. In the study area, there was a clustering effect in terms of time to first symptomatic recovery from major depressive disorder. According to the Log-normal Inverse-Gaussian frailty model, marital status, chewing khat, educational status, work status, substance addiction, and other co-variables were significant predictors of major depressive disorder (p-value < 0.05). CONCLUSION: The best model for describing the time to the first symptomatic recovery of major depressive disorder is the log-normal Inverse-Gaussian frailty model. Being educated and working considerably were the variables that reduces the time to first symptomatic recovery from major depressive disorder; whereas being divorced, chewing khat, substance abused and other co-factors were the variables that significantly extends the time to first symptomatic recovery.

Bivariate Survival Copula Analysis of Glaucoma Patients during Blindness: Glaucoma Cases at Alert Hospital in Addis Ababa City of Ethiopia.

BACKGROUND: Glaucoma is a worldwide problem that causes vision loss and even blindness, with a prevalence rate ranging from 1.9% to 15%. In Ethiopia, glaucoma is the fifth cause of blindness. This study aimed to explore the dependence between blindness of the right and the left eyes of glaucoma patients and assess the effects of the covariates under the dependence structure. STUDY DESIGN: A retrospective cohort study. METHODS: The study population included the glaucoma patients at Alert hospital from January 1, 2018, to December 30, 2021. The copula model was used to estimate the time to the blindness of the right and the left eyes of the glaucoma patients by specifying the dependence between the event times. RESULTS: Out of 537 glaucoma patients, 224 (41.71%) became blind at least in one eye during the follow-up period. The results of the Clayton copula model revealed that factors, such as age, residence, diabetes mellitus, stage of glaucoma, and hypertension are considered the most prognostic factors for blindness in glaucoma patients. The findings also revealed that there was a strong dependence between the time to the blindness of the right and the left eyes in the glaucoma patients (τ = 0.43). CONCLUSION: Based on the obtained results, high age, urban residence, hypertension, diabetes mellitus, and higher stage of glaucoma were factors associated with time to the blindness in the glaucoma patients. There was also a dependence between the right and the left eyes of the glaucoma patients. The results revealed that the Clayton Archimedean copula model was the best statistical model for accurate description of glaucoma patients' datasets.

Time to Diabetic Retinopathy and Its Risk Factors among Diabetes Mellitus Patients in Jimma University Medical Center, Jimma, Southwest Ethiopia.

Background: Diabetic retinopathy is a complication of diabetes, caused by high blood sugar levels damaging the eye. Globally, diabetic retinopathy affects more than 103.12 million people. Diabetic retinopathy is among the leading causes of vision loss at the global level, including in Ethiopia. Therefore, the study aimed to assess the time to develop diabetic retinopathy and identify factors associated with diabetic retinopathy among diabetes patients. Methods: A retrospective study was conducted from September 1, 2021 to January 30, 2022. Data was collected using semistructured questionnaire. The Cox proportional hazard model were used to determine the median time to develop diabetic retinopathy and identify predictors of diabetic retinopathy. Data was analyzed using R software. Results: A total of 373 diabetes patients were included in this study. The prevalence of diabetic retinopathy was 41.3%. The median time was 41 months, ranging from 39 to 73 months. Elder age (HR=3.17, 95%CI: 1.53, 6.58), being male (HR=2.34, 95%CI: 1.35, 6.15), previous family history of diabetes (HR=4.16, 95%CI: 2.19, 8.37), longer duration of diabetes (HR=2.86, 95%CI: 1.41, 5.31) received only insulin therapy (HR=3.91, 95%CI: 1.36, 7.94), and high systolic blood pressure(HR=2.32; 95%CI: 1.12, 4.39) were statistically significant factors related to development of diabetes retinopathy. Conclusions: More than half of diabetic patinets in this study were developed retinopathy diabetes within a few months of being diagnosed. As a result, we advocate that the best way to preserve our vision from diabetic retinopathy is to maintain our diabetes under control, and the high-risk population receive early screening for diabetes.

Modeling Time to Cure of Deep Vein Thrombosis Using Cox Proportional Model in Southwest of Ethiopia.

Background: Globally, there are about 10 million cases of deep vein thrombosis every year, and it is the third leading cardiovascular disease after myocardial infarction and stroke. The objective of the study is to assess risk factors of time to cure patients of deep vein thrombosis in southwest Ethiopia. Methods: A retrospective cohort study design was used. The study population was deep vein thrombosis patients at purposively selected hospitals in Southwest Ethiopia from January 2017 to December 2020. Cox proportional hazard model was used to identify risk factors associated with deep vein thrombosis. Results: Out of the total 1068 registered as deep vein thrombosis patients, 263(24.6%) were cured during the study period, and 805(75.4%) were censored. Results of the Cox proportional hazard model show that; age, gender, family history of deep vein thrombosis, smoking status, immobilize and alcohol consumption were factors associated with deep vein thrombosis (p-value<0.05). Conclusion: The patients with a family history of deep vein thrombosis, prolonged immobilization, greater the 50 years, smoking cigarettes, female (non-pregnant) and alcohol users had a longer curing time of deep vein thrombosis compared to others.