Background: In the United States, obesity impacts the health of over 20% of adolescents. As more data emerges on obesity and the associated adipose tissue dysfunction, updated screening and treatment guidelines for obesity and its related comorbidities have been published. (See Table 1). However, it is unclear if providers are adhering to these guidelines. Methods: We leveraged the TriNetX Research Network platform, a global federated network of electronic medical record data, to identify current national practice patterns for screening for lipid dysfunction, liver function abnormalities, and insulin resistance, and prescribing of anti-obesity medications. Additionally, we reviewed the prescription patterns of FDA approved and off-label anti-obesity medications. Our cohort was defined as patients 14–18 years old, with three outpatient encounters between Jan 1, 2017 and March 1, 2020, and obesity, defined as BMI>30 or greater than the 95th percentile recorded on 3 separate outpatient encounters. The date cutoff was set in order to avoid the potential confounding effects of COVID-19 global pandemic. Exclusion criteria included a diagnostic code for lipid dysfunction, fatty liver, or insulin resistance prior to Jan 1, 2017 as well as any diagnosis of type 1 Diabetes. Screening for comorbidity of lipid dysfunction, fatty liver, and insulin resistance were defined by the presence of a total cholesterol, ALT, and Hgb A1C respectively. Results: The cohort included 31,017 patients that met all inclusion and exclusion criteria. The mean age of patients was 16. 56% of patient had an ICD-10 code of obesity in the chart. Screening rates for lipid dysfunction (Total Cholesterol), insulin resistance (Hgb A1c), and fatty liver (ALT) were 44%, 54%, and 41% respectively. Only 31% of patients were screened for all 3. When screened, 28% of patients had a Hgb A1C >5.7%, 22% had an ALT >45, and 13% had a total cholesterol >200. 9% of patients had prescriptions of anti-obesity medication including (Orlistat, Phentermine, Topiramate, Metformin, Liraglutide). The two most used medication were Metformin and Topiramate. However, when excluding individuals with ICD-10 codes for migraines (G40, G43, G44), prevalence of topiramate prescription decreased from 4% to 1%. Conclusion: Screening for obesity comorbidities continues to fall short of recommendations. Screening rates in our study occurred at about the same rates as previously reported in the literature (50-60% for diabetes, 38-40% for lipid dysfunction, and 2-56% for liver disease). There is evidence to support the use of anti-obesity medications in pediatric patients; however, we found that anti-obesity medication prescriptions remain limited nationally. To our knowledge, this is one of the largest studies to evaluate this issue in children. Further studies are warranted to explore the causes of low screening and treatment rates in adolescents with obesity and inform interventions.

Recommendations for Screening for Obesity Related Comorbidities and Initiation of Anti-Obesity Medications

Recommendations for Screening for Obesity Related Comorbidities and Initiation of Anti-Obesity Medications

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Demographics and Results

Demographics and Results

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