Low reproducibility of fasting blood glucose makes it difficult to identify patients with prediabetes
Keywords:
Reproducibility of results, blood glucose, prediabetic state, Diabetes mellitus, mass screening, glycated hemoglobin, early diagnosis, diagnostic techniques and proceduresAbstract
Introduction: Tests for screening and diagnosis of prediabetes based on plasma glycaemia have low reproducibility, which affects their precision, reliability and increases costs for the health system.
Objective: To identify clinical or humoral factors associated with the reproducibility of fasting blood glucose in the prediabetes range, in the context of preventive medical examinations.
Material and Methods: Cross-sectional study in 69 patients without a history of diabetes and with fasting blood glucose between 5.6 - 6.9 mmol/L. Medical history, demographic and anthropometric variables, HbA1c and glucose tolerance test (GTT) were recorded. The correlation between fasting blood glucose, GTT and HbA1c was analyzed using Pearson's correlation coefficient, and the OR for hyperglycemia reproduced according to risk factors was calculated. Biochemical parameters were compared between patients with and without reproduced hyperglycemia.
Results: The correlations of fasting blood glucose with HbA1c, 0h-GTT blood glucose and 2h-GTT blood glucose were weak and positive. The best correlation was obtained between the two GTT blood glucose values (p 0.549; sig 0.000). No diabetes risk variable behaved as a risk factor for reproduced hyperglycemia. Patients with reproduced hyperglycemia had significantly higher fasting blood glucose than those without it (6.23 ± 0.31 vs. 5.99 ± 0.35 mmol/L).
Conclusions: Fasting blood glucose showed low reproducibility in the context of preventive examinations. Only the highest blood glucose values were associated with reproduced hyperglycemia. No clinical variable was identified as a risk factor for reproduced hyperglycemia.
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1. American Diabetes Association Professional Practice Committee. 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2024. Diabetes Care [Internet]. 2023 [Citado 13/12/2024]; 47(Supplement_1):pS20-S42. Disponible en: https://doi.org/10.2337/dc24-S002
2. Zieleniewska NA, Jamiołkowski J, Chlabicz M, Łukasiewicz A, Dubatówka M, Kondraciuk M, et al. The impact of prediabetes on preclinical atherosclerosis in general apparently healthy population: A cross-sectional study. PloS one [Internet]. 2024 [Citado 13/12/2024]; 19(10): e0309896. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC11521245/pdf/pone.0309896.pdf
3. Magliano JD, Boyko JE, Balkau B, Barengo N, Barr E, Basit A, et al. IDF Diabetes Atlas.10 Edition. EE. UU: Berkeley Communications; 2021. Disponible en: www.diabetesatlas.org
4. Organization WH. HEARTS D: diagnosis and management of type 2 diabetes. Geneva: World Health Organization; 2020.
5. Tjaden AH, Edelstein SL, Arslanian S, Barengolts E, Caprio S, Cree-Green M, et al. Reproducibility of Glycemic Measures Among Dysglycemic Youth and Adults in the RISE Study. The Journal of Clinical Endocrinology and Metabolism [Internet]. 2023 [Citado 13/12/2024]; 108(10):1125-33. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC10505524/
6. Selvin E, Crainiceanu CM, Brancati FL, Coresh J. Short-term Variability in Measures of Glycemia and Implications for the Classification of Diabetes. Archives of Internal Medicine [Internet]. 2007 [Citado 13/12/2024]; 167(14):1545-51. Disponible en: https://doi.org/10.1001/archinte.167.14.1545
7. Inker LA, Eneanya ND, Coresh J, Tighiouart H, Wang D, Sang, et al. New Creatinine- and Cystatin C-Based Equations to Estimate GFR without Race. The New England Journal of Medicine [Internet]. 2021 [Citado 13/12/2024]; 385(19):1737-49. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC8822996/pdf/nihms-1763303.pdf
8. Abdul-Ghani MA, Tripathy D, DeFronzo RA. Contributions of β-Cell Dysfunction and Insulin Resistance to the Pathogenesis of Impaired Glucose Tolerance and Impaired Fasting Glucose. Diabetes Care [Internet]. 2006 [Citado 13/12/2024]; 29(5):1130-9. Disponible en: https://doi.org/10.2337/dc05-2179
9. Saban M, Rovira G, Curriá MI. Risk factors associated with the need for insulin in patients with gestational diabetes in a reference hospital in Buenos Aires, Argentina: retrospective cohort study. Revista Colombiana de Obstetricia y Ginecologia [Internet]. 2023 [Citado 13/12/2024]; 74(2):136-42. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC10419874/pdf/2463-0225-rcog-74-02-3883.pdf
10. Mata-Cases M, Artola S, Escalada J, Ezkurra-Loyola P, Ferrer-García JC, Fornos JA, et al. Consensus on the detection and management of prediabetes. Consensus and Clinical Guidelines Working Group of the Spanish Diabetes Society. Atencion primaria [Internet]. 2015 [Citado 13/12/2024]; 47(7):456-68. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC6983698/pdf/main.pdf
11. Chakkalakal RJ, Galaviz KI, Thirunavukkarasu S, Shah MK, Narayan KMV. Test and Treat for Prediabetes: A Review of the Health Effects of Prediabetes and the Role of Screening and Prevention. Annual Review of Public Health [Internet]. 2024 [Citado 13/12/2024]; 45(1):151-67. Disponible en: https://www.annualreviews.org/docserver/fulltext/publhealth/45/1/annurev-publhealth-060222-023417.pdf
12. Cobey KD, Ebrahimzadeh S, Page MJ, Thibault RT, Nguyen PY, Abu-Dalfa F, et al. Biomedical researchers' perspectives on the reproducibility of research. PLoS Biology [Internet]. 2024 [Citado 13/12/2024]; 22(11):e3002870. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC11537370/pdf/pbio.3002870.pdf
13. Liao HW, Saver J, Yeh HC, Chen CS, Wu YL, Lee L, et al. Low fasting glucose and future risks of major adverse outcomes in people without baseline diabetes or cardiovascular disease: a systematic review and meta-analysis. BMJ open [Internet]. 2019 [Citado 13/12/2024]; 9(7): e026010. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC6609056/pdf/bmjopen-2018-026010.pdf
14. Matabuena M, Pazos-Couselo M, Alonso-Sampedro M, Fernández-Merino C, González-Quintela A, Gude F. Reproducibility of continuous glucose monitoring results under real-life conditions in an adult population: a functional data analysis. Scientific Reports [Internet]. 2023 [Citado 13/12/2024]; 13(1):e13987. Disponible en: https://doi.org/10.1038/s41598-023-40949-1
15. Nathan DM, Davidson MB, DeFronzo RA, Heine RJ, Henry RR, Pratley R, et al. Impaired Fasting Glucose and Impaired Glucose Tolerance: Implications for care. Diabetes Care [Internet]. 2007 [Citado 13/12/2024]; 30(3):753-9. Disponible en: https://doi.org/10.2337/dc07-9920
16. Chen Y, Lundeen EA, Koyama AK, Kompaniyets L, Andes LJ, Benoit SR, et al. Prevalence of Testing for Diabetes Among US Adults With Overweight or Obesity, 2016–2019. Preventing Chronic Disease [Internet]. 2023 [Citado 13/12/2024]; 20. Disponible en: https://www.cdc.gov/pcd/issues/2023/23_0173.htm
17. Galicia-Garcia U, Benito-Vicente A, Jebari S, Larrea-Sebal A, Siddiqi H, Uribe KB, et al. Pathophysiology of Type 2 Diabetes Mellitus. International Journal of Molecular Sciences [Internet]. 2020 [Citado 13/12/2024]; 21(17) e6275. Disponible en: https://pmc.ncbi.nlm.nih.gov/articles/PMC7503727/pdf/ijms-21-06275.pdf
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