May 15, 2025 Journal article Open Access

BY: KUBSA GUYO (BSc)

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    <dct:title>TIME TO FIRST OPTIMAL GLYCEMIC CONTROL AND ITS PREDICTORS AMONG TYPE 1 DIABETES CHILDREN AND ADOLESCENTS FOLLOW-UP AT PUBLIC HOSPITALS IN BORENA ZONE, OROMIA, SOUTHERN ETHIOPIA, 2024.</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2025</dct:issued>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2025-05-15</dct:issued>
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    <dct:description>&lt;p&gt;Background: Glycemic control refers to the level of blood sugar in diabetes patients. Recognizing a patient&amp;#39;s level of glycemic control is an important measure to avoid complications and the risk of death from diabetes. However, the other most important variable, which is the time that the patient stayed at that suboptimal glycemic level before reaching optimal glycemic control, has not been studied so far, including both children and adolescents globally, as the author searches. Objective: To determine the time to first optimal glycemic control and its predictors among type 1 diabetes children and adolescents follow-up at public hospitals in Borena zone, Ethiopia, 2024. Methods: A hospital-based retrospective cohort study was conducted from June 25 to July 25, 2024, among 383 type 1 diabetes children and adolescents attending at public hospitals in the Borena zone, Ethiopia. A simple random sampling technique was used to select two hospitals. Medical record numbers were obtained from patient register logbooks. Then data was collected from patients&amp;#39; cards from January 1st, 2019, to January 31st, 2024, by using a simple random sampling method with a pretested checklist in each selected hospital. Data was collected using a data abstraction tool, then entered into Epi-data 4.6 and analyzed using Stata version 15. The Kaplan-Meier survival curve, along with log-rank tests, was used to estimate and compare survival times. A bivariate Cox regression model was used to select variables for the final model at a p value &amp;le; 0.25. Multivariable Cox regression was used to identify predictors of time to first optimal glycemic control. The adjusted hazards ratio with a 95% confidence interval and a p-value &amp;lt;0.05 was used to determine statistical significance. Results: The final analysis included 373 study participants, with a response rate of 97.3%. Median survival time to first optimal glycemic control among type 1 diabetic patients was 14.3 months (95%CI: 13-17). The first optimal glycemic achievement rate was 4.42 (95%CI: 3.8-5.1) per 100 person-month observation. Factors that affect time to first optimal glycemic control were the absence of health insurance (AHR: 0.566, 95%CI: 0.356-0.90), comorbidity (AHR: 0.654, 95%CI: 0.45-0.94), type of current insulin regimen (AHR: 3.76, 95%CI: 1.48-9.56), &amp;le;4 follow-ups (AHR: 0.63, 95%CI: 0.42-0.95), and diabetic ketoacidosis (AHR: 0.53, 95%CI: 0.37-0.78). Conclusion and Recommendation: Median survival time to first optimal glycemic control among type 1 diabetic patients was much longer. Which indicates that patients are being unprotected for complications. Absence of health insurance, diabetic ketoacidosis, type of current insulin regimen, &amp;le;4 follow-up frequency, and comorbidity were independent predictors of time to optimal glycemic control. Therefore, diabetic care should be strengthened to shorten time to first optimal glycemic control. Hence, it should be better to give special attention to patients with identified predictors.&lt;/p&gt;</dct:description>
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