title: Prognostic accuracy of continuous glucose monitoring in the prediction of diabetes mellitus in children with incidental hyperglycemia: receiver operating characteristic analysis.
abstract: OBJECTIVE
  The purpose of this study is to evaluate continuous glucose monitoring (CGM) in predicting diabetes mellitus in children with incident hyperglycemia (IH) and negativity for some insular autoantibodies.
  
  
  METHODS
  Thirty-one autoantibody-negative children who presented at our center with IH underwent a baseline assessment and were followed up for 23.8 months (range, 6-48 months). At the end of the follow-up, we compared the receiver operating characteristic (ROC) areas under the curve (AUCs) of metabolic markers from 17 children who developed diabetes (Group A; n=17) and 14 children who did not develop diabetes (Group B; n=14).
  
  
  RESULTS
  Only two oral glucose tolerance test (OGTT)-derived markers and three CGM-derived markers showed a good prognostic performance, with ROC AUCs indicating significant results (P<0.0001) for the following markers: 2-h glucose, OGTT (0.813; 95% confidence interval [CI] 0.621-0.954); AUC glucose, OGTT (0.832; 95% CI 0.611-0.950); CGM glucose measurement peak (0.803; 95% CI 0.621-0.923); percentage of CGM glucose measurements inside the range 70-125 mg/dL (0.866; 95% CI 0.695-0.961); and percentage of CGM measurements ≥126 mg/dL (0.889; 95% CI 0.724-0.973). The combination of the OGTT-derived markers did not increase the predictive value, but the combination of CGM markers with each other or with the OGTT markers yielded higher ROC AUCs (ranging from 0.828 to 0.945).
  
  
  CONCLUSIONS
  This is the first study showing that CGM is useful in predicting diabetes mellitus in children with IH.
authors.affiliation: Regional Reference Center for Diabetology and Insulin Pumps, Department of Internal Medicine and Diabetology, Hospital of Partinico, Palermo, Italy. davide.brancato@libero.it
authors.forename: Davide
authors.initials: D
authors.lastname: Brancato
authors.forename: Gabriella
authors.initials: G
authors.lastname: Saura
authors.forename: Mattia
authors.initials: M
authors.lastname: Fleres
authors.forename: Lidia
authors.initials: L
authors.lastname: Ferrara
authors.forename: Alessandro
authors.initials: A
authors.lastname: Scorsone
authors.forename: Vito
authors.initials: V
authors.lastname: Aiello
authors.forename: Anna
authors.initials: A
authors.lastname: Di Noto
authors.forename: Lucia
authors.initials: L
authors.lastname: Spano
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Provenzano
mesh_terms: D001323:Autoantibodies / Q000032:analysis; D015415:Biomarkers / Q000097:blood / Q000378:metabolism; D001786:Blood Glucose / Q000032:analysis; D002648:Child; D002675:Child, Preschool; D003920:Diabetes Mellitus / Q000097:blood / Q000175:diagnosis* / Q000276:immunology / Q000378:metabolism; D042241:Early Diagnosis; D045604:Extracellular Fluid / Q000378:metabolism*; D005260:Female; D005500:Follow-Up Studies; D005947:Glucose / Q000378:metabolism*; D005951:Glucose Tolerance Test; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D006943:Hyperglycemia / Q000209:etiology*; D033162:Incidental Findings; D007223:Infant; D008297:Male; D018670:Monitoring, Ambulatory; D011237:Predictive Value of Tests; D012372:ROC Curve
chemical_list: D001323:Autoantibodies; D015415:Biomarkers; D001786:Blood Glucose; D005947:Glucose; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human