Algorithm-based cholesterol monitoring in children with type 1 diabetes

Abstract

Objective: To facilitate child-specific and diabetes-related cholesterol control, we developed a monitoring algorithm derived from population-based reference values.

Study design: Low-density lipoprotein (LDL)-, non-high-density lipoprotein (HDL)-, and HDL cholesterol percentile values were calculated for children with type 1 diabetes (T1D) and their peers without T1D within algorithm-based categories of sex, age: 1-10 vs >10-<18 years, body mass index: <90th vs ≥90th percentile, and hemoglobin A1c <6%, 6%-<7.5%, 7.5%-9%, >9%. Analyses included 26 147 patients sampled from a German/Austrian population-based registry for T1D (Diabetes Documentation and Quality Management System) and 14 057 peers without diabetes participating in the national Health Interview and Examination Survey for Children and Adolescents in Germany.

Results: Reference percentile values for cholesterol were derived as a diagnostic algorithm aimed at supporting long-term cholesterol control. Taking account of a patient's sex, age-group, weight-, and hemoglobin A1c-category, the flowcharts of the algorithm developed separately for LDL-, non-HDL-, and HDL cholesterol allow comparing his/her cholesterol levels with population-based reference percentile values of peers without T1D.

Conclusions: The population-based algorithmic approach applied to LDL-, non-HDL-, and HDL cholesterol allows referencing children with T1D with regard to their peers without T1D and, if necessary, suggests corrections of glycemic control to optimize long-term cholesterol levels.