Jennifer L Sherr1, Anke Schwandt2,3, Helen Phelan4,5, Mark A Clements6,7, Reinhard W Holl2,3, Paul Z Benitez-Aguirre5,8, Kellee M Miller9, Joachim Woelfle10, Thomas Dover11,12, David M Maahs13,14, Elke Fröhlich-Reiterer15, Maria E Craig5,8. 1. Division of Pediatric Endocrinology, Department of Pediatrics, Yale School of Medicine, Yale University, New Haven, Connecticut jennifer.sherr@yale.edu. 2. Institute of Epidemiology and Medical Biometry, Zentralinstitut für Biomedizinische Technik, Ulm University, Ulm, Germany. 3. German Centre for Diabetes Research, Munich-Neuherberg, Germany. 4. John Hunter Children's Hospital, Newcastle, Australia. 5. Division of Child and Adolescent Health, The University of Sydney, Sydney, Australia. 6. Children's Mercy Hospital, Kansas City, Missouri. 7. Department of Pediatrics, University of Missouri-Kansas City, Kansas City, Missouri. 8. Children's Hospital at Westmead, Sydney, Australia. 9. Jaeb Center for Health Research, Tampa, Florida. 10. Children's Hospital, University of Erlangen, Erlangen, Germany. 11. Ipswich Hospital, Brisbane, Australia. 12. Mater Hospitals, Brisbane, Australia. 13. Stanford Diabetes Research Center. 14. Division of Endocrinology and Diabetes, Department of Pediatrics, School of Medicine, Stanford University, Stanford, California. 15. Department of Pediatrics and Adolescent Medicine, Medical University of Graz, Graz, Austria.
Abstract
OBJECTIVES: Distinct hemoglobin A1c (HbA1c) trajectories during puberty are identified in youth with established type 1 diabetes (T1D). We used data from 3 international registries to evaluate whether distinct HbA1c trajectories occur from T1D onset. METHODS: Participants were <18 years old at diagnosis with at least 1 HbA1c measured within 12 months post diagnosis, along with ≥3 duration-year-aggregated HbA1c values over 10 years of follow-up. Participants from the Australasian Diabetes Data Network (n = 7292), the German-Austrian-Luxembourgian-Swiss diabetes prospective follow-up initiative (Diabetes Patienten Verlaufsdokumentation) (n = 39 226) and the US-based Type 1 Diabetes Exchange Clinic Registry (n = 3704) were included. With group-based trajectory modeling, we identified unique HbA1c patterns from the onset of T1D. RESULTS: Five distinct trajectories occurred in all 3 registries, with similar patterns of proportions by group. More than 50% had stable HbA1c categorized as being either low stable or intermediate stable. Conversely, ∼15% in each registry were characterized by stable HbA1c >8.0% (high stable), and ∼11% had values that began at or near the target but then increased (target increase). Only ∼5% of youth were above the target from diagnosis, with an increasing HbA1c trajectory over time (high increase). This group differed from others, with higher rates of minority status and an older age at diagnosis across all 3 registries (P ≤ .001). CONCLUSIONS: Similar postdiagnostic HbA1c patterns were observed across 3 international registries. Identifying the youth at the greatest risk for deterioration in HbA1c over time may allow clinicians to intervene early, and more aggressively, to avert increasing HbA1c.
OBJECTIVES: Distinct hemoglobin A1c (HbA1c) trajectories during puberty are identified in youth with established type 1 diabetes (T1D). We used data from 3 international registries to evaluate whether distinct HbA1c trajectories occur from T1D onset. METHODS: Participants were <18 years old at diagnosis with at least 1 HbA1c measured within 12 months post diagnosis, along with ≥3 duration-year-aggregated HbA1c values over 10 years of follow-up. Participants from the Australasian Diabetes Data Network (n = 7292), the German-Austrian-Luxembourgian-Swiss diabetes prospective follow-up initiative (Diabetes Patienten Verlaufsdokumentation) (n = 39 226) and the US-based Type 1 Diabetes Exchange Clinic Registry (n = 3704) were included. With group-based trajectory modeling, we identified unique HbA1c patterns from the onset of T1D. RESULTS: Five distinct trajectories occurred in all 3 registries, with similar patterns of proportions by group. More than 50% had stable HbA1c categorized as being either low stable or intermediate stable. Conversely, ∼15% in each registry were characterized by stable HbA1c >8.0% (high stable), and ∼11% had values that began at or near the target but then increased (target increase). Only ∼5% of youth were above the target from diagnosis, with an increasing HbA1c trajectory over time (high increase). This group differed from others, with higher rates of minority status and an older age at diagnosis across all 3 registries (P ≤ .001). CONCLUSIONS: Similar postdiagnostic HbA1c patterns were observed across 3 international registries. Identifying the youth at the greatest risk for deterioration in HbA1c over time may allow clinicians to intervene early, and more aggressively, to avert increasing HbA1c.
Authors: Roy W Beck; Crystal G Connor; Deborah M Mullen; David M Wesley; Richard M Bergenstal Journal: Diabetes Care Date: 2017-08 Impact factor: 19.112
Authors: Helen Clapin; Helen Phelan; Loren Bruns; Richard Sinnott; Peter Colman; Maria Craig; Timothy Jones Journal: J Diabetes Sci Technol Date: 2016-08-22