Predictive Factors Of Complications In Diabetic Patients Under Care At The Haho Health District Hospital, Togo, 2020 – 2021

Introduction Diabetes related complications constitute a factor of bad prognosis in diabetic patients and are also responsible of significant loss of life years in populations, especially in low- and middle-income countries. Many factors determine the occurrence of diabetic complications in one patient. The purpose of this study is to determine predictive factors associated to diabetic complications in Haho health district. Methods We conducted a prospective study at Notse hospital. The participants in this cohort were recruited from diagnosed diabetic patients who attended the hospital during 2020 for any purpose. To be included, they must not have at entrance any current diabetic complication and must have their HbA1c available. They were followed-up from 1st september 2020 to 31 august 2021. The screened outcome was the occurrence of any diabetic complication. Any macrovascular, microvascular or metabolic dysfunction attributable to diabetes was considered as diabetic complication. We predicted associated factors to diabetic complications using cox regression model with 95% confidence interval (CI). Results A total of 136 participants were followed-up. The overall incidence rate of diabetic complications was 12.5 cases per 100-person year 95% CI (6.4-18.6). Diabetes duration (p=0.02), non-paid patients’ occupation (p=0.01) and living in rural area (p=0.00) were significantly associated with complications occurrence in bivariate analysis. Living with diabetes for a median duration of two years protected from complications and living in rural area had 4.54 (1.29-15.95) time hazard ratio of developing complications. Conclusion Only few participants in this cohort did not comply to the prescribed protocol and were able to be assessed with alternative designed means. The results found are clinical based one, specific to poor resources settings and easily reproducible and helpful to set a large database to help improve diabetes care in low- and middle-income countries