Background/Purpose: This study aims to retrospectively analyze existing data to assess the prevalence and intensity of insulin resistance among adults with autoimmune thyroiditis, a condition marked by the body's immune response against its thyroid gland, including Hashimoto's thyroiditis. Insulin resistance, characterized by the body's inadequate response to insulin, complicates blood sugar regulation. This research seeks to explore historical health records of individuals diagnosed with autoimmune thyroiditis to identify potential correlations with insulin resistance.
Methods: Our approach involves a comprehensive review of previous medical records, with a focus on evaluating insulin levels, HbA1c values (an indicator of blood sugar regulation), and other pertinent health markers in patients with autoimmune thyroiditis. Data analysis was conducted using SPSS version 26, a software extensively employed in social sciences for statistical computations. The distribution normality was verified through the Shapiro-Wilks test and Box Plot diagrams. Correlation between variables was determined using either Pearson or Spearman's correlation analysis.
Results: Our statistical analysis uncovered a significant correlation between higher Insulin Resistance (HOMA-IR) scores and increased levels of blood glucose and insulin, with p-values indicating strong positive relationships (p<0.01 for both variables). Additionally, a moderate positive correlation was observed between Insulin Resistance (HOMA-IR) scores and both HbA1c levels and HbA1c (IFCC) measurements, reinforcing the association between insulin resistance and long-term glucose regulation markers.
Conclusion: The findings from this study illuminate the extent and impact of insulin resistance among those with autoimmune thyroiditis, highlighting the potential for these insights to revolutionize diagnosis and treatment paradigms. By establishing a clearer understanding of these associations, our goal is to improve clinical strategies, setting the stage for further research that could lead to enhanced treatment outcomes for individuals grappling with these health challenges.
Primary Language | English |
---|---|
Subjects | Bioinformatics and Computational Biology (Other), Biochemistry and Cell Biology (Other) |
Journal Section | Clinical Research |
Authors | |
Early Pub Date | December 10, 2024 |
Publication Date | |
Submission Date | May 31, 2024 |
Acceptance Date | September 26, 2024 |
Published in Issue | Year 2025Issue: Kabul Edilen Makaleler |