Startseite Developing a risk assessment tool for identifying individuals at high risk for developing insulin resistance in European adolescents: the HELENA-IR score
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Developing a risk assessment tool for identifying individuals at high risk for developing insulin resistance in European adolescents: the HELENA-IR score

  • Katerina Kondakis ORCID logo EMAIL logo , Evangelia Grammatikaki ORCID logo , Marios Kondakis ORCID logo , Denes Molnar ORCID logo , Sonia Gómez-Martínez , Marcela González-Gross , Anthony Kafatos , Yannis Manios ORCID logo , David Jiménez Pavón ORCID logo , Frédéric Gottrand ORCID logo , Laurent Beghin ORCID logo , Mathilde Kersting , Manuel J. Castillo , Luis A. Moreno ORCID logo und Stefaan De Henauw ORCID logo
Veröffentlicht/Copyright: 22. November 2022
Journal of Pediatric Endocrinology and Metabolism
Aus der Zeitschrift Journal of Pediatric Endocrinology and Metabolism Band 35 Heft 12

Abstract

Objectives

To develop and validate an easy-to-use screening tool for identifying adolescents at high-risk for insulin resistance (IR).

Methods

Α total of 1,053 adolescents (554 females), aged 12.5 to 17.5 years with complete data on glucose and insulin levels were included. Body mass index (BMI), fat mass index (FMI) and the homeostasis model assessment for insulin resistance (HOMA-IR) were calculated. VO2max was predicted using 20 m multi-stage fitness test. The population was randomly separated into two cohorts for the development (n=702) and validation (n=351) of the index, respectively. Factors associated with high HOMA-IR were identified by Spearman correlation in the development cohort; multiple logistic regression was performed for all identified independent factors to develop a score index. Finally, receiver operating characteristic (ROC) analysis was performed in the validation cohort and was used to define the cut-off values that could identify adolescents above the 75th and the 95th percentile for HOMA-IR.

Results

BMI and VO2max significantly identified high HOMA-IR in males; and FMI, TV watching and VO2max in females. The HELENA-IR index scores range from 0 to 29 for males and 0 to 43 for females. The Area Under the Curve, sensitivity and specificity for identifying males above the 75th and 95th of HOMA-IR percentiles were 0.635 (95%CI: 0.542–0.725), 0.513 and 0.735, and 0.714 (95%CI: 0.499–0.728), 0.625 and 0.905, respectively. For females, the corresponding values were 0.632 (95%CI: 0.538–0.725), 0.568 and 0.652, and 0.708 (95%CI: 0.559–0.725), 0.667 and 0.617, respectively. Simple algorithms were created using the index cut-off scores.

Conclusions

Paediatricians or physical education teachers can use easy-to-obtain and non-invasive measures to apply the HELENA-IR score and identify adolescents at high risk for IR, who should be referred for further tests.

Keywords: adolescents; body fatness; insulin resistance; screening tool; type 2 diabetes; VO2max
Corresponding author: Katerina Kondakis, PhDc, Department of Public Health and Primary Care, Faculty of Medicine and Health Sciences, Ghent University, Corneel Heymanslaan 10, P/A UZ 4K3, Ghent, Belgium, E-mail:

Funding source: Sixth Framework Programme

Award Identifier / Grant number: Contract FOOD-CT-2005-007034

Acknowledgments

We gratefully acknowledge all participating adolescents and their parents for their collaboration, and Petra Pickert and Anke Carstensen for their contribution to laboratory work.

  1. Research funding: The HELENA study was financially supported by the European Community Sixth RTD Framework Programme (Contract FOOD-CT-2005-007034).

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Participants and their parents or guardians provided signed informed consent prior to their enrolment in the study.

  5. Ethical approval: The HELENA study adhered to the Declaration of Helsinki and the conventions of the Council of Europe on human rights and biomedicine. All participating countries obtained ethical clearance from the relevant ethical committees and local authorities.

References

1. International Diabetes Federation. IDF diabetes atlas, 10th ed. Brussels, Belgium: International Diabetes Federation; 2021.Suche in Google Scholar

2. International Diabetes Federation. IDF diabetes atlas, 8th ed. Brussels, Belgium: International Diabetes Federation; 2017.Suche in Google Scholar

3. Lynch, JL, Barrientos-Pérez, M, Hafez, M, Jalaludin, MY, Kovarenko, M, Rao, PV, et al.. Country-specific prevalence and incidence of youth-onset type 2 diabetes: a narrative literature review. Ann Nutr Metab 2020;76:289–96. https://doi.org/10.1159/000510499.Suche in Google Scholar PubMed

4. Lawrence, JM, Divers, J, Isom, S, Saydah, S, Imperatore, G, Pihoker, C, et al.. Trends in prevalence of type 1 and type 2 diabetes in children and adolescents in the US, 2001-2017. JAMA 2021;326:717. https://doi.org/10.1001/jama.2021.11165.Suche in Google Scholar PubMed PubMed Central

5. Chen, Y, Wang, T, Liu, X, Shankar, RR. Prevalence of type 1 and type 2 diabetes among US pediatric population in the MarketScan Multi‐State Database, 2002 to 2016. Pediatr Diabetes 2019;20:523–9. https://doi.org/10.1111/pedi.12842.Suche in Google Scholar PubMed

6. Shulman, R, Slater, M, Khan, S, Jones, C, Walker, JD, Jacklin, K, et al.. Prevalence, incidence and outcomes of diabetes in Ontario First Nations children: a longitudinal population-based cohort study. CMAJ Open 2020;8:E48–55. https://doi.org/10.9778/cmajo.20190226.Suche in Google Scholar PubMed PubMed Central

7. Koutny, F, Weghuber, D, Bollow, E, Greber-Platzer, S, Hartmann, K, Körner, A, et al.. Prevalence of prediabetes and type 2 diabetes in children with obesity and increased transaminases in European German-speaking countries. Analysis of the APV initiative. Pediatr Obes 2020;15:e12601. https://doi.org/10.1111/ijpo.12601.Suche in Google Scholar PubMed PubMed Central

8. Klingensmith, GJ, Lanzinger, S, Tamborlane, WV, Hofer, SE, Cheng, P, de Beaufort, C, et al.. Adolescent type 2 diabetes: comparing the pediatric diabetes consortium and Germany/Austria/luxemburg pediatric diabetes prospective registries. Pediatr Diabetes 2018;19:1156–63. https://doi.org/10.1111/pedi.12712.Suche in Google Scholar PubMed

9. Diabetes Canada Clinical Practice Guidelines Expert Committee. Ekoe, J-M, Goldenberg, R, Katz, P. Screening for diabetes in adults. Can J Diabetes 2018;42(1 Suppl):S16–9. https://doi.org/10.1016/j.jcjd.2017.10.004.Suche in Google Scholar PubMed

10. Gilmer, TP, O’Connor, PJ. The growing importance of diabetes screening. Diabetes Care 2010;33:1695–7. https://doi.org/10.2337/dc10-0855.Suche in Google Scholar PubMed PubMed Central

11. American Diabetes Association. 12. Children and adolescents: standards of medical care in diabetes—2018. Diabetes Care 2018;41:S126–36. https://doi.org/10.2337/dc18-S012.Suche in Google Scholar PubMed

12. Barkai, L, Kiss, Z, Rokszin, G, Abonyi-Tóth, Z, Jermendy, G, Wittmann, I, et al.. Changes in the incidence and prevalence of type 1 and type 2 diabetes among 2 million children and adolescents in Hungary between 2001 and 2016 – a nationwide population-based study. Arch Med Sci 2020;16:34–41. https://doi.org/10.5114/aoms.2019.88406.Suche in Google Scholar PubMed PubMed Central

13. Neu, A, Feldhahn, L, Ehehalt, S, Ziegler, J, Rothe, U, Rosenbauer, J, et al.. No change in type 2 diabetes prevalence in children and adolescents over 10 years: update of a population-based survey in South Germany. Pediatr Diabetes 2018;19:637–9. https://doi.org/10.1111/pedi.12622.Suche in Google Scholar PubMed

14. Candler, TP, Mahmoud, O, Lynn, RM, Majbar, AA, Barrett, TG, Shield, JPH. Continuing rise of Type 2 diabetes incidence in children and young people in the UK. Diabet Med 2018;35:737–44. https://doi.org/10.1111/dme.13609.Suche in Google Scholar PubMed PubMed Central

15. Demmer, RT, Zuk, AM, Rosenbaum, M, Desvarieux, M. Prevalence of diagnosed and undiagnosed type 2 diabetes mellitus among US adolescents: results from the continuous NHANES, 1999-2010. Am J Epidemiol 2013;178:1106–13. https://doi.org/10.1093/aje/kwt088.Suche in Google Scholar PubMed PubMed Central

16. Ramos Salas, X, Buoncristiano, M, Williams, J, Kebbe, M, Spinelli, A, Nardone, P, et al.. Parental perceptions of children’s weight status in 22 countries: the WHO European childhood obesity surveillance initiative: COSI 2015/2017. Obes Facts 2021;14:658–74. https://doi.org/10.1159/000517586.Suche in Google Scholar PubMed PubMed Central

17. Xiang, AH, Wang, C, Peters, RK, Trigo, E, Kjos, SL, Buchanan, TA. Coordinate changes in plasma glucose and pancreatic β-cell function in latino women at high risk for type 2 diabetes. Diabetes 2006;55:1074–9. https://doi.org/10.2337/diabetes.55.04.06.db05-1109.Suche in Google Scholar PubMed

18. Rutter, MK, Meigs, JB, Sullivan, LM, D’Agostino, RB, Wilson, PW. Insulin resistance, the metabolic syndrome, and incident cardiovascular events in the framingham offspring study. Diabetes 2005;54:3252–7. https://doi.org/10.2337/diabetes.54.11.3252.Suche in Google Scholar PubMed

19. Czech, MP. Insulin action and resistance in obesity and type 2 diabetes. Nat Med 2017;23:804–14. https://doi.org/10.1038/nm.4350.Suche in Google Scholar PubMed PubMed Central

20. Avena, R, Mitchell, ME, Neville, RF, Sidawy, AN. The additive effects of glucose and insulin on the proliferation of infragenicular vascular smooth muscle cells. J Vasc Surg 1998;28:1033–9. https://doi.org/10.1016/s0741-5214(98)70029-1.Suche in Google Scholar PubMed

21. Sreekumar, R, Halvatsiotis, P, Schimke, JC, Nair, KS. Gene expression profile in skeletal muscle of type 2 diabetes and the effect of insulin treatment. Diabetes 2002;51:1913–20. https://doi.org/10.2337/diabetes.51.6.1913.Suche in Google Scholar PubMed

22. Dietrich, S, Jacobs, S, Zheng, J-S, Meidtner, K, Schwingshackl, L, Schulze, MB. Gene-lifestyle interaction on risk of type 2 diabetes: a systematic review. Obes Rev Off J Int Assoc Study Obes 2019;20:1557–71. https://doi.org/10.1111/obr.12921.Suche in Google Scholar PubMed PubMed Central

23. Chiarelli, F, Marcovecchio, ML. Insulin resistance and obesity in childhood. Eur J Endocrinol 2008;159:S67–74. https://doi.org/10.1530/eje-08-0245.Suche in Google Scholar PubMed

24. Lee, JM, Okumura, MJ, Davis, MM, Herman, WH, Gurney, JG. Prevalence and determinants of insulin resistance among U.S. Adolescents: a population-based study. Diabetes Care 2006;29:2427–32. https://doi.org/10.2337/dc06-0709.Suche in Google Scholar PubMed

25. Valerio, G, Licenziati, MR, Iannuzzi, A, Franzese, A, Siani, P, Riccardi, G, et al.. Insulin resistance and impaired glucose tolerance in obese children and adolescents from Southern Italy. Nutr Metab Cardiovasc Dis NMCD 2006;16:279–84. https://doi.org/10.1016/j.numecd.2005.12.007.Suche in Google Scholar PubMed

26. Wang, T, Huang, T, Zheng, Y, Rood, J, Bray, GA, Sacks, FM, et al.. Genetic variation of fasting glucose and changes in glycemia in response to 2-year weight-loss diet intervention: the POUNDS Lost trial. Int J Obes 2016;40:1164–9. https://doi.org/10.1038/ijo.2016.41.Suche in Google Scholar PubMed PubMed Central

27. Lindström, J, Tuomilehto, J. The Diabetes Risk Score: a practical tool to predict type 2 diabetes risk. Diabetes Care 2003;26:725–31.10.2337/diacare.26.3.725Suche in Google Scholar PubMed

28. Hippisley-Cox, J, Coupland, C. Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study. BMJ 2017;359:j5019. https://doi.org/10.1136/bmj.j5019.Suche in Google Scholar PubMed PubMed Central

29. Chen, L, Magliano, DJ, Balkau, B, Colagiuri, S, Zimmet, PZ, Tonkin, AM, et al.. AUSDRISK: an Australian Type 2 Diabetes Risk Assessment Tool based on demographic, lifestyle and simple anthropometric measures. Med J Aust 2010;192:274. https://doi.org/10.5694/j.1326-5377.2010.tb03507.x.Suche in Google Scholar PubMed

30. Robinson, CA, Agarwal, G, Nerenberg, K. Validating the CANRISK prognostic model for assessing diabetes risk in Canada’s multi-ethnic population. Chronic Dis Inj Can 2011;32:13. https://doi.org/10.24095/hpcdp.32.1.04.Suche in Google Scholar

31. Moreno, LA, De Henauw, S, González-Gross, M, Kersting, M, Molnár, D, Gottrand, F, et al.. Design and implementation of the healthy lifestyle in Europe by nutrition in adolescence cross-sectional study. Int J Obes 2008;32:S4–11. https://doi.org/10.1038/ijo.2008.177.Suche in Google Scholar PubMed

32. Moreno, LA, Gottrand, F, Huybrechts, I, Ruiz, JR, González-Gross, M, DeHenauw, S, et al.. Nutrition and lifestyle in European adolescents: the HELENA (healthy lifestyle in Europe by nutrition in adolescence) study. Adv Nutr 2014;5:615S–23S. https://doi.org/10.3945/an.113.005678.Suche in Google Scholar PubMed PubMed Central

33. Béghin, L, Castera, M, Manios, Y, Gilbert, CC, Kersting, M, De Henauw, S, et al.. Quality assurance of ethical issues and regulatory aspects relating to good clinical practices in the HELENA Cross-Sectional Study. Int J Obes 2008;32:S12–8. https://doi.org/10.1038/ijo.2008.179.Suche in Google Scholar PubMed

34. Nagy, E, Vicente-Rodriguez, G, Manios, Y, Béghin, L, Iliescu, C, Censi, L, et al.. Harmonization process and reliability assessment of anthropometric measurements in a multicenter study in adolescents. Int J Obes 2008;32:S58–65. https://doi.org/10.1038/ijo.2008.184.Suche in Google Scholar PubMed

35. Cole, TJ, Bellizzi, MC, Flegal, KM, Dietz, WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ 2000;320:1240–3. https://doi.org/10.1136/bmj.320.7244.1240.Suche in Google Scholar PubMed PubMed Central

36. World Obesity Federation. Extended International (IOTF) body mass index cut-offs for thinness, overweight and obesity in children n.d. https://www.worldobesity.org/about/about-obesity/obesity-classification [Accessed 4 Apr 2022].Suche in Google Scholar

37. Tanner, JM, Whitehouse, RH. Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty. Arch Dis Child 1976;51:170–9. https://doi.org/10.1136/adc.51.3.170.Suche in Google Scholar PubMed PubMed Central

38. Gätjens, I, Schmidt, SCE, Plachta-Danielzik, S, Bosy-Westphal, A, Müller, MJ. Body composition characteristics of a load-capacity model: age-dependent and sex-specific percentiles in 5- to 17-year-old children. Obes Facts 2021;14:593–603. https://doi.org/10.1159/000518638.Suche in Google Scholar PubMed PubMed Central

39. Hagströmer, M, Bergman, P, De Bourdeaudhuij, I, Ortega, FB, Ruiz, JR, Manios, Y, et al.. Concurrent validity of a modified version of the international physical activity questionnaire (IPAQ-A) in European adolescents: the HELENA study. Int J Obes 2008;32(5 Suppl):S42–8. https://doi.org/10.1038/ijo.2008.182.Suche in Google Scholar PubMed

40. Ortega, FB, Artero, EG, Ruiz, JR, Vicente-Rodriguez, G, Bergman, P, Hagströmer, M, et al.. Reliability of health-related physical fitness tests in European adolescents. The HELENA Study. Int J Obes 2008;32:S49–57. https://doi.org/10.1038/ijo.2008.183.Suche in Google Scholar PubMed

41. Léger, LA, Mercier, D, Gadoury, C, Lambert, J. The multistage 20 metre shuttle run test for aerobic fitness. J Sports Sci 1988;6:93–101. https://doi.org/10.1080/02640418808729800.Suche in Google Scholar PubMed

42. Tomkinson, GR, Lang, JJ, Tremblay, MS, Dale, M, LeBlanc, AG, Belanger, K, et al.. International normative 20 m shuttle run values from 1 142 026 children and youth representing 50 countries. Br J Sports Med 2017;51:1545–54. https://doi.org/10.1136/bjsports-2016-095987.Suche in Google Scholar PubMed

43. Welk, GJ, Laurson, KR, Eisenmann, JC, Cureton, KJ. Development of youth aerobic-capacity standards using receiver operating characteristic curves. Am J Prev Med 2011;41:S111–6. https://doi.org/10.1016/j.amepre.2011.07.007.Suche in Google Scholar PubMed

44. Matthews, DR, Hosker, JP, Rudenski, AS, Naylor, BA, Treacher, DF, Turner, RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985;28:412–9. https://doi.org/10.1007/bf00280883.Suche in Google Scholar

45. González-Gross, M, Breidenassel, C, Gómez-Martínez, S, Ferrari, M, Béghin, L, Spinneker, A, et al.. Sampling and processing of fresh blood samples within a European multicenter nutritional study: evaluation of biomarker stability during transport and storage. Int J Obes 2008;32(5 Suppl):S66–75. https://doi.org/10.1038/ijo.2008.185.Suche in Google Scholar PubMed

46. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2021.Suche in Google Scholar

47. Panagiotopoulos, C, Hadjiyannakis, S, Henderson, M. Type 2 diabetes in children and adolescents. Can J Diabetes 2018;42:S247–54. https://doi.org/10.1016/j.jcjd.2017.10.037.Suche in Google Scholar PubMed

48. World Health Organization; International Diabetes Federation. Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia: report of a WHO/IDF consultation. Geneva, Switzerland: World Health Organization; 2006.Suche in Google Scholar

49. Fonseca, VA. Early identification and treatment of insulin resistance: impact on subsequent prediabetes and type 2 diabetes. Clin Cornerstone 2007;8:S7–18. https://doi.org/10.1016/s1098-3597(07)80017-2.Suche in Google Scholar PubMed

50. Hanley, AJG, Williams, K, Stern, MP, Haffner, SM. Homeostasis model assessment of insulin resistance in relation to the incidence of cardiovascular disease: the San Antonio heart study. Diabetes Care 2002;25:1177–84. https://doi.org/10.2337/diacare.25.7.1177.Suche in Google Scholar PubMed

51. Herman, WH, Hoerger, TJ, Brandle, M, Hicks, K, Sorensen, S, Zhang, P, et al.. The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance. Ann Intern Med 2005;142:323–32. https://doi.org/10.7326/0003-4819-142-5-200503010-00007.Suche in Google Scholar PubMed PubMed Central

52. Costa, B, Barrio, F, Piñol, JL, Cabré, JJ, Mundet, X, Sagarra, R, et al.. Shifting from glucose diagnosis to the new HbA1c diagnosis reduces the capability of the Finnish Diabetes Risk Score (FINDRISC) to screen for glucose abnormalities within a real-life primary healthcare preventive strategy. BMC Med 2013;11:45. https://doi.org/10.1186/1741-7015-11-45.Suche in Google Scholar PubMed PubMed Central

53. Franciosi, M, Berardis, GD, Rossi, MCE, Sacco, M, Belfiglio, M, Pellegrini, F, et al.. Use of the diabetes risk score for opportunistic screening of undiagnosed diabetes and impaired glucose tolerance: the IGLOO (impaired glucose tolerance and long-term outcomes observational) study. Diabetes Care 2005;28:1187–94. https://doi.org/10.2337/diacare.28.5.1187.Suche in Google Scholar PubMed

54. Makrilakis, K, Liatis, S, Grammatikou, S, Perrea, D, Stathi, C, Tsiligros, P, et al.. Validation of the Finnish diabetes risk score (FINDRISC) questionnaire for screening for undiagnosed type 2 diabetes, dysglycaemia and the metabolic syndrome in Greece. Diabetes Metab 2011;37:144–51. https://doi.org/10.1016/j.diabet.2010.09.006.Suche in Google Scholar PubMed

55. Tankova, T, Chakarova, N, Atanassova, I, Dakovska, L. Evaluation of the Finnish Diabetes Risk Score as a screening tool for impaired fasting glucose, impaired glucose tolerance and undetected diabetes. Diabetes Res Clin Pract 2011;92:46–52. https://doi.org/10.1016/j.diabres.2010.12.020.Suche in Google Scholar PubMed

56. Mavrogianni, C, Lambrinou, C-P, Androutsos, O, Lindström, J, Kivelä, J, Cardon, G, et al.. Evaluation of the Finnish Diabetes Risk Score as a screening tool for undiagnosed type 2 diabetes and dysglycaemia among early middle-aged adults in a large-scale European cohort. The Feel4Diabetes-study. Diabetes Res Clin Pract 2019;150:99–110. https://doi.org/10.1016/j.diabres.2019.02.017.Suche in Google Scholar PubMed

57. Gomez-Arbelaez, D, Alvarado-Jurado, L, Ayala-Castillo, M, Forero-Naranjo, L, Camacho, PA, Lopez-Jaramillo, P. Evaluation of the Finnish Diabetes Risk Score to predict type 2 diabetes mellitus in a Colombian population: a longitudinal observational study. World J Diabetes 2015;6:1337–44. https://doi.org/10.4239/wjd.v6.i17.1337.Suche in Google Scholar PubMed PubMed Central

58. Gray, LJ, Taub, NA, Khunti, K, Gardiner, E, Hiles, S, Webb, DR, et al.. The Leicester Risk Assessment score for detecting undiagnosed Type 2 diabetes and impaired glucose regulation for use in a multiethnic UK setting. Diabet Med 2010;27:887–95. https://doi.org/10.1111/j.1464-5491.2010.03037.x.Suche in Google Scholar PubMed

Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/jpem-2022-0265).

Received: 2022-05-18
Accepted: 2022-09-26
Published Online: 2022-11-22
Published in Print: 2022-12-16

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Review Article
  3. The efficacy and safety of dipeptidyl peptidase-4 inhibitors and glucagon-like peptide-1 agonists in pediatric patients with type 2 diabetes: a systematic review
  4. Original Articles
  5. Triple burden of malnutrition and role of anaemia in the development of complications associated with type 1 diabetes in Indian children and youth
  6. Effect of obesity and excessive body fat on glycaemic control in paediatric type 1 diabetes
  7. Role of pan immune inflammatory value in the evaluation of hepatosteatosis in children and adolescents with obesity
  8. Secular trends of birth weight and its associations with obesity and hypertension among Southern Chinese children and adolescents
  9. Insights into the implication of obesity in hypogonadism among adolescent boys
  10. The association between plasma carnitines and duration of diabetic ketoacidosis treatment in children with type 1 diabetes
  11. Cathelicidin as a marker for subclinical cardiac changes and microvascular complications in children and adolescents with type 1 diabetes
  12. Developing a risk assessment tool for identifying individuals at high risk for developing insulin resistance in European adolescents: the HELENA-IR score
  13. Hemoglobin A1C can differentiate subjects with GCK mutations among patients suspected to have MODY
  14. Perceptions and use of complementary and alternative medicine in patients with precocious puberty
  15. Case Reports
  16. Infection with SARS-CoV-2 may alter the half-life of desmopressin (DDAVP) in patients with central diabetes insipidus
  17. Heterozygous CDC73 mutation causing hyperparathyroidism in children and adolescents: a report of 2 cases
  18. Wolfram syndrome in a young woman with associated hypergonadotropic hypogonadism – A case report
  19. Continuous glucose monitoring in an infant with panhypopituitarism having hypoglycemia on growth hormone therapy
  20. Severe consumptive hypothyroidism in hepatic hemangioendothelioma
  21. Efficacy of aromatase inhibitor therapy in a case with large cell calcifying Sertoli cell tumour-associated prepubertal gynaecomastia
https://doi.org/10.1515/jpem-2022-0265
Schlagwörter für diesen Artikel
adolescents; body fatness; insulin resistance; screening tool; type 2 diabetes; VO2max

Artikel in diesem Heft

  1. Frontmatter
  2. Review Article
  3. The efficacy and safety of dipeptidyl peptidase-4 inhibitors and glucagon-like peptide-1 agonists in pediatric patients with type 2 diabetes: a systematic review
  4. Original Articles
  5. Triple burden of malnutrition and role of anaemia in the development of complications associated with type 1 diabetes in Indian children and youth
  6. Effect of obesity and excessive body fat on glycaemic control in paediatric type 1 diabetes
  7. Role of pan immune inflammatory value in the evaluation of hepatosteatosis in children and adolescents with obesity
  8. Secular trends of birth weight and its associations with obesity and hypertension among Southern Chinese children and adolescents
  9. Insights into the implication of obesity in hypogonadism among adolescent boys
  10. The association between plasma carnitines and duration of diabetic ketoacidosis treatment in children with type 1 diabetes
  11. Cathelicidin as a marker for subclinical cardiac changes and microvascular complications in children and adolescents with type 1 diabetes
  12. Developing a risk assessment tool for identifying individuals at high risk for developing insulin resistance in European adolescents: the HELENA-IR score
  13. Hemoglobin A1C can differentiate subjects with GCK mutations among patients suspected to have MODY
  14. Perceptions and use of complementary and alternative medicine in patients with precocious puberty
  15. Case Reports
  16. Infection with SARS-CoV-2 may alter the half-life of desmopressin (DDAVP) in patients with central diabetes insipidus
  17. Heterozygous CDC73 mutation causing hyperparathyroidism in children and adolescents: a report of 2 cases
  18. Wolfram syndrome in a young woman with associated hypergonadotropic hypogonadism – A case report
  19. Continuous glucose monitoring in an infant with panhypopituitarism having hypoglycemia on growth hormone therapy
  20. Severe consumptive hypothyroidism in hepatic hemangioendothelioma
  21. Efficacy of aromatase inhibitor therapy in a case with large cell calcifying Sertoli cell tumour-associated prepubertal gynaecomastia
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