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논문 기본 정보

자료유형
학술저널
저자정보
Nieto Teresa (St. Agnes Academy Houston TX USA) Castillo Beatriz (Baylor College of Medicine School of Medicine Houston TX USA) Nieto Jacobo (Rice University Houston TX USA) Redondo Maria J. (Baylor College of Medicine Texas Children’s Hospital Houston TX USA)
저널정보
대한소아내분비학회 Annals of Pediatirc Endocrinology & Metabolism Annals of Pediatric Endocrinology & Metabolism 제27권 제2호
발행연도
2022.6
수록면
121 - 125 (5page)
DOI
10.6065/apem.2142170.085

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Purpose: Type 1 diabetes (T1D) is the most common type of diabetes in children, but the frequency of type 2 diabetes (T2D) is increasing rapidly. Classification of diabetes is based on a constellation of features that vary by type. We aimed to compare demographic, clinical, and laboratory characteristics at diagnosis of pediatric T1D and T2D.Methods: We studied children who visited a large academic hospital in Houston, Texas (USA) with a new diagnosis of T2D (n=753) or T1D (n=758). We compared age, sex, race/ethnicity, presence of obesity, glucose, hemoglobin A1c, islet autoantibody positivity, C-peptide, and presence of diabetic ketoacidosis (DKA) at diabetes diagnosis.Results: At diagnosis, children with T2D, compared with those with T1D, were older (13.6 years vs. 9.7 years), more likely female (63.2% vs. 47.8%), of racial/ethnic minority (91.1% vs. 42.3%), and obese (90.9% vs. 19.4%) and were less likely to have DKA (7.8% vs. 35.0%) and diabetes autoantibodies (5.5% vs. 95.4%). Children with T2D also had significantly lower glucose, lower hemoglobin A1c and lower C-peptide level (all comparisons, p<0.0001). In multiple logistic regression analysis, older age, racial/ethnic minority, obesity, higher C-peptide, and negative islet autoantibodies were independently associated with T2D (all, p<0.05), while sex, glucose, hemoglobin A1c, and DKA were not (model p<0.0001).Conclusion: There are important demographic, clinical, and laboratory differences between T1D and T2D in children. However, none of the characteristics were unique to either diabetes type, which poses challenges to diabetes classification at diagnosis.

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