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A risk score for identifying overweight adolescents with dysglycemia in primary care settings1)

  • Joyce M. Lee EMAIL logo , Achamyeleh Gebremariam , Susan J. Woolford , Beth A. Tarini , Melissa A. Valerio , Surair Bashir , Ashley J. Eason , Preciosa Y. Choi und James G. Gurney
Veröffentlicht/Copyright: 25. Februar 2013
Journal of Pediatric Endocrinology and Metabolism
Aus der Zeitschrift Journal of Pediatric Endocrinology and Metabolism Band 26 Heft 5-6

Abstract

Objective: To develop a clinical risk scoring system for identifying adolescents with dysglycemia (prediabetes or diabetes) who need further confirmatory testing and to determine whether the addition of non-fasting tests would improve the prediction of dysglycemia.

Study Design: A sample of 176 overweight and obese adolescents (10–17 years) had a history/physical exam, a 2-h oral glucose tolerance test, and non-fasting tests [hemoglobin A1c, 1-h glucose challenge test (GCT), and random glucose test] performed. Given the low number of children with diabetes, we created several risk scoring systems combining the clinical characteristics with non-fasting tests for identifying adolescents with dysglycemia and compared the test performance.

Results: Sixty percent of participants were white and 32% were black; 39.2% had prediabetes and 1.1% had diabetes. A basic model including demographics, body mass index percentile, family history of diabetes, and acanthosis nigricans had reasonable test performance [area under the curve (AUC), 0.75; 95% confidence interval (95% CI), 0.68–0.82]. The addition of random glucose (AUC, 0.81; 95% CI, 0.75–0.87) or 1-h GCT (AUC, 0.82; 95% CI, 0.75–0.88) to the basic model significantly improved the predictive capacity, but the addition of hemoglobin A1c did not (AUC, 0.76; 95% CI, 0.68–0.83). The clinical score thresholds to consider for the basic plus random glucose model are total score cutoffs of 60 or 65 (sensitivity 86% and 65% and specificity 60% and 78%, respectively) and for the basic plus 1-h GCT model are total score cutoffs of 50 or 55 (sensitivity 87% and 73% and specificity 59% and 76%, respectively).

Conclusions: Pending a validation in additional populations, a risk score combining the clinical characteristics with non-fasting test results may be a useful tool for identifying children with dysglycemia in the primary care setting.

Keywords: adolescents; prediabetes; risk score
Corresponding author: Joyce M. Lee, Pediatric Endocrinology and Health Services Research, Child Health Evaluation and Research (CHEAR) Unit, University of Michigan, 300 NIB, Room 6E18, Campus Box 5456, Ann Arbor, 48109-5456 MI, Phone: +1-734-615-3139, Fax: +1-734-615-5153

Conflict of interest statement

Financial disclosure/conflict of interest: All authors have nothing to disclose.

Appendix Table 1

Comparison of risk scoring systems and test performance for each model.

Basic modelADA modelBasic model+1-h GCTBasic model+random glucoseBasic model+HbA1cBasic model+1-h GCT+HbA1cBasic model+random glucose+HbA1c
AUC (95% CI)0.75

(0.68–0.82)		0.76

(0.69–0.83)		0.82

(0.75–0.88)		0.81

(0.75–0.87)		0.76

(0.68–0.83)		0.82

(0.76–0.88)		0.82

(0.76–0.88)
Age, years
 10–110000000
 12–133222222
 14–155545544
 16–178767767
Sex
 Female0000000
 Male9911810119
Race
 White0000000
 Non-white3243242
BMI percentile
 85–890000000
 90–9414141113131012
 ≥9528292225262123
Family history
 No0000000
 Yes, grandparents6676776
 Yes, parents/siblings13131312131313
Acanthosis nigricans
 No0000000
 Yes22211823221823
Self-report of low cholesterol
 No0
 Yes4
Self-report of PCOS
 No0
 Yes11
Maternal history of diabetes during pregnancy
 No0
 Yes4
1-h GCT, mg/dL
 60–6900
 70–7933
 80–8966
 90–99109
 100–1091312
 110–1191616
 120–1291919
 130–1392222
 140–1492525
 150–1592928
 160–1693231
 ≥1703534
Random glucose, mg/dL
 50–5900
 60–6955
 70–791111
 80–891616
 90–992121
 100–1092726
 110–1193232
 120–1293837
 130–1394342
 ≥1404847
HbA1c, %
 4.3–4.5000
 4.6–4.8111
 4.9–5.1312
 5.2–5.4312
 5.5–5.7423
 5.8–6.0634
 6.1–6.3735
 6.4–6.6946
 6.7–6.91057
 ≥7.01158
Total score8310010912691112132
Appendix Table 2A

Test characteristics of the ADA model.

ThresholdSensitivity, %Specificity, %Positive likelihood ratioNegative likelihood ratioPositive predictive value, %Negative predictive value, %
510001.00–40–
1510011.010.0041100
2010041.040.0041100
25100101.120.0043100
3099151.160.094494
3597221.240.134692
4093351.440.204988
4579632.120.345981
5065712.270.496175
5544873.270.656969
6024944.190.817465
6517975.920.868063
7011100–0.8910063
757100–0.9310061
803100–0.9710060
851100–0.9910060
Appendix Table 2B

Test characteristics of the basic plus HbA1c model.

ThresholdSensitivity, %Specificity, %Positive likelihood ratioNegative likelihood ratioPositive predictive value, %Negative predictive value, %
510001.00–40–
1010011.010.0041100
1510031.030.0041100
2010051.050.0041100
25100111.130.0043100
3097151.150.184489
3597261.310.114793
4087451.580.285284
4572631.930.455777
5054792.550.596372
5538935.700.667969
6020976.900.838264
6514987.390.888363
7010100–0.9010062
757100–0.9310061
803100–0.9710060
Appendix Table 2C

Test characteristics of the basic plus 1-h GCT plus HbA1c model.

ThresholdSensitivity, %Specificity, %Positive likelihood ratioNegative likelihood ratioPositive predictive value, %Negative predictive value, %
1510001.00–40–
2010041.040.0041100
2510081.080.0042100
3099101.090.154291
3599171.190.084595
4094261.270.224687
4593421.600.175290
5087541.910.235686
5575773.270.336982
6059864.140.487476
6546926.100.588072
70349711.830.688968
75209920.700.819365
8013100–0.8710063
858100–0.9210062
907100–0.9310061
956100–0.9410061
1001100–0.9910060
Appendix Table 2D

Test characteristics of the basic plus random glucose plus HbA1c model.

ThresholdSensitivity, %Specificity, %Positive likelihood ratioNegative likelihood ratioPositive predictive value, %Negative predictive value, %
1510001.00–40–
2010011.010.0041100
2510031.030.0041100
3010051.050.0041100
3510061.060.0042100
4010081.080.0042100
45100181.220.0045100
5099311.440.044997
5594451.710.135492
6086592.100.245986
6570783.210.386880
7049883.980.587372
7539925.180.667869
8028979.860.748767
85209810.350.828864
9014987.390.888363
956995.920.958061
1006100–0.9410061
1153100–0.9710060
1251100–0.9910060
  1. 1)

    Grant support: This study was funded by the National Institute of Diabetes and Digestive and Kidney Diseases (K08-DK-082386), Clinical Sciences Scholars Program, Michigan Clinical Research Unit (UL1RR024986), Michigan Institute for Clinical and Health Research (UL1RR024986), Michigan Diabetes Research and Training Center (5P60-DK-20572), Blue Cross Blue Shield Foundation of Michigan, and Elizabeth Kennedy Award/Elizabeth Crosby Funds/Office of the Vice President for Research from the University of Michigan.

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Received: 2012-8-7
Accepted: 2013-1-18
Published Online: 2013-02-25
Published in Print: 2013-05-01

©2013 by Walter de Gruyter Berlin Boston

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https://doi.org/10.1515/jpem-2012-0259
Schlagwörter für diesen Artikel
adolescents; prediabetes; risk score

Artikel in diesem Heft

  1. Masthead
  2. Masthead
  3. Editorial
  4. Success has many fathers, failure is orphan
  5. Review Article
  6. Normosmic idiopathic hypogonadotropic hypogonadism: update on the genetic background and future challenges
  7. Original Articles
  8. Temporary brittle bone disease: association with intracranial bleeding
  9. Asymmetric dimethylarginine (ADMA) and L-arginine levels in children with glycogen storage disease type I
  10. Application of liquid chromatography-tandem mass spectrometry in the diagnosis and follow-up of maple syrup urine disease in a Chinese population
  11. The role of uncoupling protein 2 and 3 genes polymorphism and energy expenditure in obese Indonesian children
  12. Thyroid dysfunctions of prematurity and their impacts on neurodevelopmental outcome1)
  13. Frequency of the E23K polymorphism of the KCNJ11 gene in children born small for gestational age and its influence on auxological and metabolic parameters in the prepubertal period
  14. Reference intervals for serum thyroid hormones in preterm hospitalized infants1)
  15. The clinical and biochemical presentation of vitamin D deficiency and insufficiency in children and adolescents
  16. A risk score for identifying overweight adolescents with dysglycemia in primary care settings1)
  17. Thyroid function and morphology in overweight and obese children and adolescents in a Chinese population
  18. Propionic acidaemia: demographic characteristics and complicationsa
  19. Negative correlation between serum IL-6 level and cardiorespiratory fitness in 10- to 11-year-old boys with increased BMI
  20. Penile length and genital anomalies in Egyptian male newborns: epidemiology and influence of endocrine disruptors
  21. Efficacy of vitamin D loading doses on serum 25-hydroxy vitamin D levels in school going adolescents: an open label non-randomized prospective trial
  22. Characteristics of infants admitted with hypoglycemia to a neonatal unit
  23. Increasing thyroid-stimulating hormone is associated with impaired glucose metabolism in euthyroid obese children and adolescents
  24. The role of FTO genotype on eating behavior in obese Sardinian children and adolescents
  25. Prevalence of multiple forms of autoimmunity in Egyptian patients with Turner syndrome: relation to karyotype
  26. A novel DAX-1 mutation presented with precocious puberty and hypogonadotropic hypogonadism in different members of a large pedigree
  27. Patient Reports
  28. Pseudohypoparathyroidism type Ia: a novel GNAS mutation in a Brazilian boy presenting with an early primary hypothyroidism
  29. Diabetic ketoacidosis with cerebral hemorrhage and alpha coma in an adolescent female
  30. A novel mutation in thyrotropin (thyroid-stimulating hormone) gene in congenital hypothyroidism
  31. Citric acid as the last therapeutic approach in an acute life-threatening metabolic decompensation of propionic acidaemia
  32. A case of autosomal dominant osteopetrosis type II with a novel TCIRG1 gene mutation
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  39. Letters to the Editors
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