The Relationship of Risk Factors with the Incidence of Diabetic Ulcers in Patients with Type 2 Diabetes Mellitus at RSUD UNDATA
Background: Type 2 diabetes mellitus |is a metabolic disease that can cause various complications, one of which |is diabetic ulcer. The |incidence of diabetic ulcers |in patients with type 2 diabetes mellitus at RSUD Undata |is still relatively high. Risk factors such as age, duration of diabetes, gender, smoking, hypertension, hyperglycemia, and obesity are thought to contribute to the |incidence of diabetic ulcers. Objective: This study aims to determine the relationship between risk factors and the |incidence of diabetic ulcers |in patient’s with type 2 diabetes mellitus at RSUD Undata. Methods: This study used an observational analytic quantitative design with a cross-sectional method. The study sample consisted of 45 patients with type 2 diabetes mellitus who were admitted to RSUD Undata |in the period December 2024 to February 2025. Data were collected using a total sampling model through |interviews and medical records, then analyzed using the chi-square test to determine the relationship between the |independent and dependent variables. Results: The results showed that there was no significant relationship between age (p=0.705), duration of diabetes (p=0.092), gender (p=0.833), smoking (p=0.363), hypertension (p=0.832), hyperglycemia (p=0.064), and body mass |index (p=0.348) with the |incidence of diabetic ulcers |in patients with type 2 diabetes mellitus. Conclusion: There |is no significant relationship between the risk factors studied and the |incidence of diabetic ulcers |in patients with type 2 diabetes mellitus at RSUD Undata. Further research with a larger population and longitudinal design is needed to obtain more accurate results.
Authors
- Mohammad Masood-ul-Hassan Nuri
- Ketut Suarayasa
Publication Details
- Journal
- International Journal of Innovative Research in Multidisciplinary Education
- Published
- 2025-06-20
- DOI
- https://doi.org/10.58806/ijirme.2025.v4i6n05
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00