Variabilidad de glucosa y hemoglobina glicosilada en pacientes atendidos Hospital del Dia Instituto Ecuatoriano de Seguridad Social Jipijapa, 2023
Glucose variability and glycosylated hemoglobin are key indicators in the evaluation and management of pathologies. Glucose variability refers to fluctuations in blood glucose levels over time, while glycosylated hemoglobin reflects average glycemic control over the last three months. The objective of the study was to analyze glucose variability and glycosylated hemoglobin in patients treated at the Day Hospital of the Ecuadorian Social Security Institute in Jipijapa. It was developed using a quantitative approach with a retrospective design. The study population consisted of all patients treated during 2023. The data collected were analyzed and processed using specialized statistical software, and the relationship between glucose variability and glycosylated hemoglobin was determined using Pearson's correlation coefficient. Among the main results, a higher prevalence of elevated basal glucose and diabetes was found in older adults, especially in females. Glycosylated hemoglobin shows a high proportion of prediabetes and diabetes, with a predominance in females. Although age slightly influences glucose variability, it does not affect hemoglobin variability. The correlation between glucose variability and hemoglobin highlights the importance of metabolic control. In conclusion, elevated basal glucose and diabetes increase with age, especially in adults aged 51 to 70 and in women, highlighting the need for monitoring and prevention.
Authors
- William Antonio Lino-Villacreses (ORCID: https://orcid.org/0000-0001-5613-9958)
- Jhon Andrés Cedeño-Andrade (ORCID: https://orcid.org/0000-0003-2918-343X)
- Glenn Jesús Torres-Dueñas (ORCID: https://orcid.org/0009-0008-4787-0034)
Institutions
- Universidad Estatal del Sur de Manabi (EC)
Publication Details
- Journal
- Multidisciplinary Latin American Journal (MLAJ)
- Published
- 2025-07-30
- DOI
- https://doi.org/10.62131/mlaj-v3-n2-032
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00