Type 2 Diabetes in High-risk Youth: Improving Identification and Interventions in Community Health with a Decade of Quality Improvement Efforts.

INTRODUCTION: This manuscript describes quality improvement interventions with aims (1) to increase identification and follow-up testing of youth with prediabetes and type 2 diabetes (T2D) and (2) to improve outcomes for youth with prediabetes and low-range T2D (HbA1c 6.5-6.9%). METHODS: Interventions included (a) dissemination of evidence-based guidelines and (b) creation of in-house weight management (WM) programs and programs to increase prediabetes follow-up testing and T2D self-management. Data from the electronic health record are presented. RESULTS: Between 2009-2020, T2D screening for obese youth increased from 24% to 76%. Two WM programs served 2,726 unique youth for 11,110 billable visits. Youth with prediabetes seen in WM clinic had a lower risk of developing T2D if they attended three or more visits. Teaching self-monitoring blood glucose showed promise for improving HbA1c outcomes in youth with low-range T2D. CONCLUSIONS: Interventions have increased identification, access to preventive services, and treatment for youth with prediabetes and T2D.

Longitudinal follow up of dysglycemia in overweight and obese pediatric patients.

OBJECTIVE: To examine factors related to progression of dysglycemia in overweight and obese youth in a large primary care setting. RESEARCH DESIGN AND METHODS: 10- to 18-year-old youth with body mass index (BMI) > 85 percentile and first-time A1c 5.7%-7.9% (39-63 mmol/mol) were identified retrospectively through electronic medical records (EMR). Levels of dysglycemia were defined as low-range prediabetes (LRPD; A1c 5.7%-5.9% [39-41 mmol/mol]), high-range prediabetes (HRPD; A1c 6.0%-6.4% [42-46 mmol/mol]), or diabetes-range (A1c 6.5%-7.9% [48 mmol/mol]). Follow-up A1c and BMI were extracted from the EMR. Follow up was truncated at the time of initiation of diabetes medication. RESULTS: Of 11 000 youth, 547 were identified with baseline dysglycemia (mean age 14.5 ± 2.2 years, 70% Hispanic, 23% non-Hispanic Black, 7% other). Of these, 206 had LRPD, 282 HRPD, and 59 diabetes. Follow-up A1c was available in 420 (77%), with median follow up of 12-22 months depending on A1c category. At follow-up testing, the percent with diabetes-range A1c was 4% in youth with baseline LRPD, 8% in youth with baseline HRPD, and 33% in youth with baseline diabetes-range A1c. There was a linear association between BMI increase and worsening A1c for LRPD (P < .001) and HRPD (P = .003). CONCLUSIONS: Most adolescents with an initial prediabetes or diabetes-range A1c did not have a diabetes-range A1c on follow up. Moreover, prediabetes-range A1c values do not all convey equal risk for the development of diabetes, with lower rates of progression for youth with initial A1c <6%. In youth with prediabetes-range A1c, BMI stabilization was associated with improvement of glycemia.

Presence of the metabolic syndrome in obese adolescents predicts impaired glucose tolerance and nonalcoholic fatty liver disease.

PURPOSE: To evaluate whether the presence of metabolic syndrome (MS) in obese adolescents is associated with other comorbidities of obesity METHODS: A total of 85 obese teens (70% female and 30% male) with fasting insulin >25 microU/ml and family history of type 2 diabetes mellitus and/or acanthosis nigricans were studied. Mean age was 15.8 +/- 1.7 years and body mass index (BMI) was 39.3 +/- 6.6 kg/m(2). Of the subjects, 54% were Hispanic and 35% black, 5% white, 5% American Indian, and 1% Asian. Laboratory analysis included fasting lipids, glucose, gamma-glutamyl transpeptidase (GGT), and oral glucose tolerance testing. Additional liver transaminase levels were determined and liver ultrasound (US) was performed to evaluate the presence and severity of fatty liver. RESULTS: All subjects met MS criteria for children for waist circumference, 49% for blood pressure, 54% for high-density lipoprotein, 54% for triglycerides, and 20% for impaired fasting glucose (IFG) or impaired glucose tolerance [IGT]). In all, 47 subjects had three or more MS criteria. BMI was no different between groups with and without MS. Subjects with three or more MS criteria were more likely to have IGT (p = .004), elevated alanine aminotransferase (p = .039), elevated GGT (p = .036), fatty liver on US (p < .001), and more severe fatty liver (p = .001). CONCLUSIONS: Abnormal glucose regulation and evidence of nonalcoholic fatty liver disease (NAFLD) were more common in subjects meeting three criteria for MS than in those meeting fewer criteria. The identification of MS provides value to the primary care provider. Those patients meeting criteria for MS should be evaluated for glucose intolerance and NAFLD.