Time to first optimal glycemic control and its predictors among type 1 diabetic children in Bahir Dar city public referral hospitals, North West Ethiopia: a retrospective follow up study.

BACKGROUND: Recognizing the level of glycemic control of a client is an important measure/tool to prevent acquiring complications and risk of death from diabetes. However, the other most important variable, which is the time that the patient stayed in that poor glycemic level before reaching optimal glycemic control, has not been studied so far. Therefore, this study aim to estimate time to first optimal glycemic control and identify predictors among type 1 diabetic children in Bahir Dar city public referral hospitals, Northwest, Ethiopia, 2021. METHODS: A Retrospective cohort study was conducted at Bahir Dar city public referral hospitals among a randomly selected sample of 385 patients with type 1 diabetes who were on follow up from January 1, 2016 to February30, 2021.Data were collected by using a data abstraction tool and then entered into Epi-data version 4.6 and exported into STATA 14.0 statistical software. Descriptive statistics, Kaplan Meier plots and median survival times, Log-rank test and Cox-proportional hazard regression were used for reporting the findings of this study. After performing Cox-proportional hazard regression, model goodness-of-fit and assumptions were checked. Finally, the association between independent variables and time to first optimal glycemic control in months was assessed using the multivariable Cox Proportional Hazard model and variables with a p-value < 0.05 were considered as statistically significant. RESULTS: Median survival time to first optimal glycemic control among type 1 diabetic clients was 8 months (95%CI: 6.9-8.9). The first optimal glycemic achievement rate was 8.2 (95%CI: 7.2-9.2) per 100 person/month observation. Factors that affect time to first optimal glycemic control were age > 10-14 years (AHR = 0.32;95%CI = 0.19-0.55), increased weight (AHR = 0.96;95%CI = 0.94-0.99), having primary care giver (AHR = 2.09;95%CI = 1.39-3.13), insulin dose (AHR = 1.05;95%CI = 1.03-1.08), duration of diabetes ≥4 years (AHR = 0.64;95%CI = 0.44-0.94), adherence to diabetic care (AHR = 9.72;95%CI = 6.09-15.51), carbohydrate counting (AHR = 2.43;95%CI = 1.12-5.26), and comorbidity (AHR = 0.72;95%CI = 0.53-0.98). CONCLUSION: The median survival time to first optimal glycemic control in this study was long. Age, weight, primary care giver, insulin dose, duration of diabetes, adherence, and carbohydrate counting, including history of comorbidity were determinant factors. Giving attention for overweight and comorbid illness prevention, increasing either the dose or frequency of insulin during initial treatment; counseling parent (for both the mother and father) about adherence to diabetic care focusing on insulin drugs and how to audit their children's diet as prescription helps to reduce the length of glycemic control.

Incidence of Pneumonia and Predictors Among Human Immunodeficiency Virus Infected Children at Public Health Institutions in the Northwest Part of Ethiopia: Multicenter Retrospective Follow-Up Study.

INTRODUCTION: Pneumonia is an inflammation of the lung parenchymal structure secondary to hematogens spread of pathogens, inhalation, or aspiration. It is also one of the most frequently occurring opportunistic infections in HIV-infected children. In Ethiopia, data on the incidence and predictors of opportunistic infection, especially pneumonia, among HIV-infected children is very limited. Hence, this study aimed to assess the incidence of pneumonia and predictors among HIV-infected children at public health institutions in the Northwest part of Ethiopia. METHODS: An institution-based retrospective cohort study was conducted among 342 HIV-infected children at public health institutions from January 1, 2013 to December 30, 2020. Log rank test was used to compare the survival curves between different explanatory variables. Bivariable Cox proportional hazards regression model was employed for each explanatory variable to check the association with the outcome variable. Variables found to have a p-value of < 0.25 in the bivariable analysis were candidates for the multi-variable proportional hazard model. Cox proportional hazards model was used at 5% level of significance to identify predictors of pneumonia. RESULTS: This study included 342 records of HIV-infected children who started antiretroviral therapy between the periods of January 1, 2013 to December 30, 2020. The overall incidence rate of pneumonia during the follow-up time was 5.57 (95% CI: 4.4, 7.0) per 100 child-years of observation. Those children who did not take cotrimoxazole preventive therapy (AHR: 3, 95% CI: 1.40, 6.44), being underweight at baseline (AHR: 2.6, 95% CI: 1.41, 4.86), having baseline advanced disease (clinical stages III and IV) (AHR: 2.8, 95% CI: 1.30, 6.04), and presenting with recently detected viral load (AHR: 5.9, 95% CI: 2.53, 14.06), were more likely to develop pneumonia. CONCLUSION: Pneumonia incidence rate was high. Providing prophylaxis and nutritional supplementation for those children with baseline advanced disease stage, low weight for age and detectable viral load would reduce pneumonia occurrence.