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Hemoglobin A1c trajectories in the first 18 months after diabetes diagnosis in the SWEET diabetes registry. | LitMetric

AI Article Synopsis

  • Many young people with type 1 diabetes don’t meet target blood sugar levels called HbA1c.
  • The study used data from the SWEET diabetes registry to find out what affects these blood sugar levels in kids diagnosed with diabetes.
  • The results showed that kids in some countries had better blood sugar control than others, especially those with national health insurance, and using tech didn’t seem to help much.

Article Abstract

Aim: A majority of youth with type 1 diabetes do not meet recommended hemoglobin A1c (HbA1c) targets. The SWEET diabetes registry is a multi-national registry of youth with diabetes. We used data from this registry to identify characteristics associated with glycemic control.

Methods: Patients in the SWEET diabetes registry with at least one HbA1c value within 10 days of diagnosis and three follow up measurements in the first 18 months of diagnosis were included (~10% of the SWEET diabetes registry). Locally weighted scatterplot smoothing was used to generate curves of HbA1c. Wilcoxon, Kruskal-Wallis, or χ2-tests were used to calculate differences between groups.

Results: The mean HbA1c of youth in the SWEET diabetes registry is highest at diagnosis and lowest between months 4 and 5 post-diabetes diagnosis. HbA1c continues to increase steadily through the first 18 months of diagnosis. There are no differences in HbA1c trajectories based on sex or use of diabetes technology. Youth in North America/Australia/New Zealand had the highest HbA1c throughout the first 18 months of diagnosis. The trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. Youth from countries with the highest gross domestic product (GDP) had the highest HbA1c throughout the first 18 months of diagnosis.

Conclusions: In this subset of patients, the trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. High GDP and high use of technology did not seem to protect from a higher trajectory.

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Source
http://dx.doi.org/10.1111/pedi.13278DOI Listing

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