McCoy RG, Faust L, Heien HC, Patel S, Caffo B, Ngufor C. Longitudinal trajectories of glycemic control among U.S. Adults with newly diagnosed diabetes.
Diabetes Res Clin Pract 2023;
205:110989. [PMID:
37918637 PMCID:
PMC10842883 DOI:
10.1016/j.diabres.2023.110989]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/27/2023] [Accepted: 10/31/2023] [Indexed: 11/04/2023]
Abstract
AIMS
To identify longitudinal trajectories of glycemic control among adults with newly diagnosed diabetes, overall and by diabetes type.
METHODS
We analyzed claims data from OptumLabs® Data Warehouse for 119,952 adults newly diagnosed diabetes between 2005 and 2018. We applied a novel Mixed Effects Machine Learning model to identify longitudinal trajectories of hemoglobin A1c (HbA1c) over 3 years of follow-up and used multinomial regression to characterize factors associated with each trajectory.
RESULTS
The study population was comprised of 119,952 adults with newly diagnosed diabetes, including 696 (0.58%) with type 1 diabetes. Among patients with type 1 diabetes, 52.6% were diagnosed at very high HbA1c, partially improved, but never achieved control; 32.5% were diagnosed at low HbA1c and deteriorated over time; and 14.9% had stable low HbA1c. Among patients with type 2 diabetes, 67.7% had stable low HbA1c, 14.4% were diagnosed at very high HbA1c, partially improved, but never achieved control; 10.0% were diagnosed at moderately high HbA1c and deteriorated over time; and 4.9% were diagnosed at moderately high HbA1c and improved over time.
CONCLUSIONS
Claims data identified distinct longitudinal trajectories of HbA1c after diabetes diagnosis, which can be used to anticipate challenges and individualize care plans to improve glycemic control.
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