Evolution of predictive models in the diagnosis of patients at risk of diabetes mellitus 2
Keywords:
diabetes mellitus, diagnosis, predictive, riskAbstract
Introduction: The early identification of diabetes mellitus through predictive models has taken a leading role; they constitute an effective way in the management of patients at high risk of this disease.
Objective: Analyze the evolution of predictive models in the identification of risk in type 2 diabetes mellitus.
Opinion: There are several predictive models for identifying patients at risk of developing diabetes mellitus, which are vital for screening. As medical science has evolved, these models have been refined and become key to improving health.
Conclusions: The application and development of predictive models to the daily clinical life of both patients and doctors is key to increasing the effectiveness and efficiency of consultations. This enables us to predict the complications of a person suffering from diabetes, improve their health status and also reduce the economic cost of the disease.
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1. Roca Goderich. Temas de Medicina Interna. Colectivo de autores. 5. ed. Rev María E. Noya Chaveco y Noel Lorenzo Moya González. La Habana: Editorial Ciencias Médicas; 2017. Tomo 3; p. 223.
2. International Diabetes Federation. IDF Diabetes Atlas, 11th edition 2025 [Internet]. Brussels; 2021. [acceso: 07/02/2025]. Disponible en: https://diabetesatlas.org/atlas/tenth-edition/
3. Ministerio de Salud Pública. Anuario Estadístico de Cuba. 2023 [Internet]. La Habana: Dirección Nacional de Registros Médicos y Estadísticas de Salud; 2024. [acceso: 07/12/2023]. Disponible en: https://files.sld.cu/dne/files/2024/09/Anuario-Estad%c3%adstico-de-Salud-2023-EDICION-2024.pdf
4. Jung K, Kashyap S, Avati A, Harman S, Shaw H, Li R, et al. A framework for making predictive models useful in practice [Internet]. Journal of the American Medical Informatics Association. 2021; 28(6):1149-58. DOI: 10.1093/jamia/ocaa318
5. Fajans S, Conn J. Studies on a test for the prediction of diabetes mellitus [Internet]. J Mich State Med Soc. 1954 [acceso: 21/02/2021]; 53(10, Part 1):1126-31. Disponible en: https://pubmed.ncbi.nlm.nih.gov/13222108/
6. Jackson WP, Woolf N. Further studies in prediabetes [Internet]. The Lancet. 1957 [acceso: 12/11/2020]; 269(6969):614-7. Disponible en: https://www.sciencedirect.com/science/article/pii/S01-40673657910735
7. Genuth SM, Houser HB, Carter JR Jr, Merkatz I, Price JW, Schumacher OP, et al. Community screening for diabetes by blood glucose measurement. Results of a five-year experience [Internet]. Diabetes. 1976 [acceso: 21/02/2021]; 25(12):1110-7. Disponible en: https://diabetesjournals.org/diabetes/article/25/12/-1110/4475/Community-Screening-for-Diabetes-by-Blood-Glucose
8. Houser HB, Mackay W, Verma N, Genuth S. A three-year controlled follow-up study of persons identified in a mass screening program for diabetes [Internet]. Diabetes. 1977 [acceso: 21/02/2021]; 26(7):619-27. Disponible en: https://diabetesjournals.org/diabetes/article/26/7/-619/5853/A-Three-year-Controlled-Follow-up-Study-of-Persons
9. Genuth SM, Houser HB, Carter JR Jr, Merkatz IR, Price JW, Schumacher OP, et al. Observations on the value of mass indiscriminate screening for diabetes mellitus based on a five-year follow-up [Internet]. Diabetes. 1978 [acceso: 21/02/2021]; 27(4):377-83. Disponible en: https://diabetesjournals.org/diabetes/article/27/4/3-77/5210/Observations-on-the-Value-of-Mass-Indiscriminate
10. Jarrett RJ, Keen H. Hyperglycaemia and diabetes mellitus [Internet]. Lancet. 1976 [acceso: 21/02/2021]; 2(7993):1009-12. Disponible en: https://www.thelancet.com/journals/lancet/article/PI-IS0140-6736(76)90844-8/fulltext
11. Bennett PH, Rushforth NB, Miller M, LeCompte PM. Epidemiologic studies of diabetes in the Pima Indians [Internet]. Recent Prog Horm Res. 1976 [acceso: 21/02/2021]; 32:333-76. Disponible en: https://www.sciencedirect.com/science/article/pii/B9-78012571132650021X?via%3Dihub
12. Lindström J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk [Internet]. Diabetes Care. 2003 [acceso: 12/11/2020]; 26(3):725-31. Disponible en: https://diabetesjournals.org/care/article/26/3/725/29-197/The-Diabetes-Risk-ScoreA-practical-tool-to-predict
13. Navarro-González D, Sánchez-Íñigo L, Pastrana-Delgado J, Fernández-Montero A, Martínez JA. Triglyceride-glucose index (TyG index) in comparison with fasting plasma glucose improved diabetes prediction in patients with normal fasting glucose: The Vascular-Metabolic CUN cohort [Internet]. Prev Med. 2016 [acceso: 21/02/2021]; 86:99-105. Disponible en: https://www.sciencedirect.com/science/article/abs/pii-/S0091743516000360?via%3Dihub
14. Lee DY, Lee ES, Kim JH, Park SE, Park CY, Oh KW, et al. Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study [Internet]. PLoS One. 2016 [acceso: 21/02/2021]; 11(9):e0163465. Disponible en: https://journals.plos.org/plosone/article?id=10.1371-/journal.pone.0163465
15. Janghorbani M, Almasi SZ, Amini M. The product of triglycerides and glucose in comparison with fasting plasma glucose did not improve diabetes prediction [Internet]. Acta Diabetol. 2015 [acceso: 21/02/2021]; 52(4):781-8. Disponible en: https://link.springer.com/article/10.1007/s00592-014-0709-5
16. Er LK, Wu S, Chou HH, Hsu LA, Teng MS, Sun YC, et al. Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals [Internet]. PLoS One. 2016 [acceso: 21/02/2021]; 11(3):e0149731. Disponible en: https://journals.plos.org/plosone/article?id=10.137-1/journal.pone.0149731
17. Zhang M, Wang B, Liu Y, Sun X, Luo X, Wang C, et al. Cumulative increased risk of incident type 2 diabetes mellitus with increasing triglyceride glucose index in normal-weight people: The Rural Chinese Cohort Study [Internet]. Cardiovasc Diabetol. 2017 [acceso: 21/02/2021]; 16(1):30. Disponible en: https://cardiab.biomedcentral.com/articles/10.1186-/s12933-017-0514-x
18. Saadeldin MK, Elshaer SS, Emara IA, Maged M, Abdel-Aziz AK. Serum sclerostin and irisin as predictive markers for atherosclerosis in Egyptian type II diabetic female patients: a case control study [Internet]. PLoS One. 2018 [acceso: 16/03/2021]; 13(11):e0206761. Disponible en: https://journals.plos.org/plosone/article?id=10.137-1/journal.pone.0206761
19. Lee HS, Park TJ, Kim JM, Yun JH, Yu HY, Kim YJ, et al. Identification of metabolic markers predictive of prediabetes in a Korean population [Internet]. Sci Rep. 2020 [acceso: 16/03/2021]; 10(1):22009. Disponible en: https://www.nature.com/articles/s41598-020-78961-4
20. Atlantis E, Lange K, Martin S, Haren MT, Taylor A, O'Loughlin PD, et al. Testosterone and modifiable risk factors associated with diabetes in men [Internet]. Maturitas. 2011 [acceso: 16/03/2021]; 68(3):279-85. Disponible en: https://www.maturitas.org/article/S0378-5122(10)00455-X/fulltext
21. Ding EL, Song Y, Malik VS, Liu S. Sex differences of endogenous sex hormones and risk of type 2 diabetes: a systematic review and meta-analysis [Internet]. JAMA. 2006 [acceso: 16/03/2021]; 295(11):1288-99. Disponible en: https://jamanetwork.com/journals/jama/article-abstract/202548
22. Atlantis E, Fahey P, Martin S, O'Loughlin P, Taylor AW, Adams RJ, et al. Predictive value of serum testosterone for type 2 diabetes risk assessment in men [Internet]. BMC Endocr Disord. 2016 [acceso: 16/03/2021]; 16(1):26. Disponible en: https://bmcendocrdisord.biomedcentral.com/articles/-10.1186/s12902-016-0109-7
23. Abbasi A, Peelen LM, Corpeleijn E, van der Schouw YT, Stolk RP, Spijkerman AM, et al. Prediction models for risk of developing type 2 diabetes: systematic literature search and independent external validation study [Internet]. BMJ. 2012 [acceso: 16/03/2021]; 345:e5900. Disponible en: https://www.bmj.com/content/345/bmj.e5900
24. Barzilay JI, Abraham L, Heckbert SR, Cushman M, Kuller LH, Resnick HE, et al. The relation of markers of inflammation to the development of glucose disorders in the elderly: the Cardiovascular Health Study [Internet]. Diabetes. 2001 [acceso: 16/03/2021]; 50(10):2384-9. Disponible en: https://diabetesjournals.org/diabetes/article/50/10/23-84/19414/The-Relation-of-Markers-of-Inflammation-to-the
25. Cabrera RE, Rodríguez CV, Rodríguez J, et al. Evaluación de tres metodologías para la predicción del riesgo de alteraciones del metabolismo de la glucosa en sujetos con sobrepeso y obesidad. [Internet]. Rev Cuba Endoc. 2017 [acceso: 16/03/2021]; 28(2):1-19. Disponible en: https://www.medigraphic.com/pdfs/revcubend/rce-2017/rce172c.pdf
26. Rubén González Tabares, Frank Abel Acosta González. Utilidad de una escala de riesgo para identificar pacientes con disglucemia. [Internet]. Rev Cubana Med Milit. 2017 [acceso: 21/02/2021]; 46(2):135-47. Disponible en: https://revmedmilitar.sld.cu/index.php/mil/article/view/26
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