Perfil lipídico como factor predictivo para el desarrollo de diabetes mellitus tipo 2 que acuden a un laboratorio privado, Jipijapa
Resumen
La prediabetes es un estado disglucémico que es actualmente un problema de salud mundial por el riesgo al desarrollo de diabetes. Una de cada dos personas que viven con diabetes desconocen que la tienen y se prevé que alcance 454 millones en el 2030. Los lípidos han sido reconocidos como un potencial marcador de resistencia a la insulina, que es un desencadenante clave para el desarrollo de diabetes. El objetivo fue analizar el perfil lipídico como factor predictivo para el desarrollo de diabetes mellitus tipo 2 en adultos que acuden a un laboratorio privado de Jipijapa. Se realizó un estudio observacional, analítico, transversal y retrospectivo. La muestra correspondió a 200 pacientes atendidos durante los años 2022-2023. Las concentraciones de triglicéridos, colesterol total y de lipoproteínas de baja densidad se observaron incrementadas en el 43,0%, 51,5% y 50,0% de los adultos estudiados, respectivamente; mientras que el 50,0% presentó bajos niveles de colesterol de las lipoproteínas de alta densidad. Todos los componentes del perfil lipídico presentaron alteraciones en sus niveles. Se evidenció hiperglucemia en el 43,0% de los adultos estudiados, con concentraciones de 155±59 mg/dL, que resultó con diferencias muy significativas (p<0,0001), al compararlo con el grupo de adultos con concentraciones normales (89±9,7 mg/dL). Se encontró una relación significativa (p<0,05) entre los niveles alterados de los componentes del perfil lipídico con la hiperglucemia en este grupo de pacientes. En conclusión, se demuestra un potencial valor predictivo del perfil lipídico en la aparición incipiente de prediabetes o diabetes mellitus en esta población.
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Referencias
American Diabetes Association Professional Practice Committee. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2022. Diabetes Care. 2022; 45(Suppl 1): S17-S38. doi: 10.2337/dc22-S002. PMID: 34964875.
Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al; IDF Diabetes Atlas Committee. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2019; 157:107843. doi: 10.1016/j.diabres.2019.107843. PMID: 31518657.
Andes LJ, Cheng YJ, Rolka DB, Gregg EW, Imperatore G. Prevalence of Prediabetes Among Adolescents and Young Adults in the United States, 2005-2016. JAMA Pediatr. 2020; 174(2): e194498. doi: 10.1001/jamapediatrics.2019.4498. PMID: 31790544; PMCID: PMC6902249.
Han C, Song Q, Ren Y, Chen X, Jiang X, Hu D. Global prevalence of prediabetes in children and adolescents: A systematic review and meta-analysis. J Diabetes. 2022; 14(7):434-441. doi: 10.1111/1753-0407.13291. PMID: 35790502; PMCID: PMC9310043.
Anillo Arrieta LA, Flórez Lozano KC, Tuesca Molina R, Acosta Vergara T, Rodríguez Acosta S, Aschner P, et al. Glycemic status and health-related quality of life (HRQOL) in populations at risk of diabetes in two Latin American cities. Qual Life Res. 2023; 32(8):2361-2373. doi: 10.1007/s11136-023-03398-x. PMID: 37010804; PMCID: PMC10328894.
Lucero J, Pacha A. Prevalencia de prediabetes en adultos de 25 a 85 años de una población andina. Revista Sanitaria de Investigación. 2002; https://revistasanitariadeinvestigacion.com/prevalencia-de-prediabetes-en-adultos-de-25-a-85-anos-de-una-poblacion-andina/
Orces CH, Lorenzo C. Prevalence of prediabetes and diabetes among older adults in Ecuador: Analysis of the SABE survey. Diabetes Metab Syndr. 2018; 12(2):147-153. doi: 10.1016/j.dsx.2017.12.002. PMID: 29273428.
Ares J, Valdés S, Botas P, Sánchez-Ragnarsson C, Rodríguez-Rodero S, Morales-Sánchez P, et al. Mortality risk in adults according to categories of impaired glucose metabolism after 18 years of follow-up in the North of Spain: The Asturias Study. PLoS One. 2019;14(1): e0211070. doi: 10.1371/journal.pone.0211070. Erratum in: PLoS One. 2019;14(5): e0216629. PMID: 30703129; PMCID: PMC6354980.
Cheng C, Liu Y, Sun X, Yin Z, Li H, Zhang M, et al. Dose-response association between the triglycerides: High-density lipoprotein cholesterol ratio and type 2 diabetes mellitus risk: The rural Chinese cohort study and meta-analysis. J Diabetes. 2019;11(3):183-192. doi: 10.1111/1753-0407.12836. PMID: 30091266.
Ghasemi A, Tohidi M, Derakhshan A, Hasheminia M, Azizi F, Hadaegh F. Cut-off points of homeostasis model assessment of insulin resistance, beta-cell function, and fasting serum insulin to identify future type 2 diabetes: Tehran Lipid and Glucose Study. Acta Diabetol. 2015; 52(5):905-15. doi: 10.1007/s00592-015-0730-3. PMID: 25794879.
Tohidi M, Asgari S, Chary A, Safiee S, Azizi F, Hadaegh F. Association of triglycerides to high-density lipoprotein cholesterol ratio to identify future prediabetes and type 2 diabetes mellitus: over one-decade follow-up in the Iranian population. Diabetol Metab Syndr. 2023;15(1):13. doi: 10.1186/s13098-023-00988-0. PMID: 36732786; PMCID: PMC9893691.
Wu L, Xu J. Relationship Between Cardiometabolic Index and Insulin Resistance in Patients with Type 2 Diabetes. Diabetes Metab Syndr Obes. 2024; 17:305-315. doi: 10.2147/DMSO.S449374. PMID: 38283637; PMCID: PMC10821666.
Yuge H, Okada H, Hamaguchi M, Kurogi K, Murata H, Ito M, Fukui M. Triglycerides/HDL cholesterol ratio and type 2 diabetes incidence: Panasonic Cohort Study 10. Cardiovasc Diabetol. 2023;22(1):308. doi: 10.1186/s12933-023-02046-5. PMID: 37940952; PMCID: PMC10634002.
Guo W, Qin P, Lu J, Li X, Zhu W, Xu N, Wang J, Zhang Q. Diagnostic values and appropriate cutoff points of lipid ratios in patients with abnormal glucose tolerance status: a cross-sectional study. Lipids Health Dis. 2019;18(1):130. doi: 10.1186/s12944-019-1070-z. PMID: 31153374; PMCID: PMC6545201.
Ouchi G, Komiya I, Taira S, Wakugami T, Ohya Y. Triglyceride/low-density-lipoprotein cholesterol ratio is the most valuable predictor for increased small, dense LDL in type 2 diabetes patients. Lipids Health Dis. 2022;21(1):4. doi: 10.1186/s12944-021-01612-8. PMID: 34996463; PMCID: PMC8742340.
Zhu L, Lu Z, Zhu L, Ouyang X, Yang Y, He W, Feng Y, Yi F, Song Y. Lipoprotein ratios are better than conventional lipid parameters in predicting coronary heart disease in Chinese Han people. Kardiol Pol. 2015;73(10):931-8. doi: 10.5603/KP.a2015.0086. PMID: 25985729.
Salazar MR, Carbajal HA, Espeche WG, Aizpurúa M, Marillet AG, Leiva Sisnieguez CE, Leiva Sisnieguez BC, Stavile RN, March CE, Reaven GM. Use of the triglyceride/high-density lipoprotein cholesterol ratio to identify cardiometabolic risk: impact of obesity? J Investig Med. 2017; 65(2):323-327. doi: 10.1136/jim-2016-000248. PMID: 27638846.
López-Jaramillo P, Nieto-Martínez RE, Aure-Fariñez G, Mendivil CO, Lahsen RA, Silva-Filho RL, et al. Identification and management of prediabetes: results of the Latin America Strategic Prediabetes Meeting. Rev Panam Salud Publica. 2017; 41: e172. doi: 10.26633/RPSP.2017.172. PMID: 31410086; PMCID: PMC6664235.
Bai Z, Zhang DS, Zhang R, Yin C, Wang RN, Huang WY, et al. A nested case-control study on relationship of traditional and combined lipid metabolism indexes with incidence of diabetes. Zhonghua Liu Xing Bing Xue Za Zhi. 2021; 42(4):656-661. Chinese. doi: 10.3760/cma.j.cn112338-20200401-00490. PMID: 34814446.
Liu Y, Feng W, Lou J, Qiu W, Shen J, Zhu Z, Hua Y, Zhang M, Billong LF. Performance of a prediabetes risk prediction model: A systematic review. Heliyon. 2023; 9(5): e15529. doi: 10.1016/j.heliyon.2023.e15529. PMID: 37215820; PMCID: PMC10196520.
Kim J, Shin SJ, Kim YS, Kang HT. Positive association between the ratio of triglycerides to high-density lipoprotein cholesterol and diabetes incidence in Korean adults. Cardiovasc Diabetol. 2021;20(1):183. doi: 10.1186/s12933-021-01377-5. PMID: 34503545; PMCID: PMC8431895.
Ministerio de Salud Pública. Encuesta Nacional de Salud y Nutrición (ENSANUT). Situación actual de las enfermedades crónicas no trasmisibles en Ecuador. Disponible en: https://www.salud.gob.ec/encuesta-nacional-de-salud-y-nutricion-ensanut/
Ministerio de Salud Pública (MSP). Programa Nacional de Atención Integral de la Diabetes. 2023. Disponible en: https://www.salud.gob.ec/msp-presento-el-programa-de-atencion-integral-de-la-diabetes-mellitus/
Instituto Nacional de Estadística y Censos (INEC). Estadísticas Vitales Registro Estadístico de Defunciones. 2022. Disponible en: https://www.ecuadorencifras.gob.ec/documentos/web- inec/Poblacion_y_Demografia/Defunciones_Generales_2021/Principales_resultados_EDG_2021_v2.pdf
Organización de las Naciones Unidas. Objetivos de Desarrollo Sostenible. ODS agenda 2030. 2015. Disponible en: https://www.un.org/sustainabledevelopment/es/objetivos-de-desarrollo-sostenible/
Secretaria Nacional de Planificación. República del Ecuador. 2021. Plan de Creación de Oportunidades 2021-2025. Disponible en: https://www.planificacion.gob.ec/wp-content/uploads/2021/09/Plan-de- Creacio%CC%81n-de-Oportunidades-2021-2025-Aprobado.pdf
Duan D, Kengne AP, Echouffo-Tcheugui JB. Screening for Diabetes and Prediabetes. Endocrinol Metab Clin North Am. 2021;50(3):369-385. doi: 10.1016/j.ecl.2021.05.002. PMID: 34399951; PMCID: PMC8375583.
Gong R, Liu Y, Luo G, Liu W, Jin Z, Xu Z, Li Z, Yang L, Wei X. Associations of TG/HDL Ratio with the Risk of Prediabetes and Diabetes in Chinese Adults: A Chinese Population Cohort Study Based on Open Data. Int J Endocrinol. 2021; :9949579. doi: 10.1155/2021/9949579. PMID: 34306073; PMCID: PMC8282372.
Li X, Xue Y, Dang Y, Liu W, Wang Q, Zhao Y, Zhang Y. Association of Non-Insulin-Based Insulin Resistance Indices with Risk of Incident Prediabetes and Diabetes in a Chinese Rural Population: A 12-Year Prospective Study. Diabetes Metab Syndr Obes. 2022; 15:3809-3819. doi: 10.2147/DMSO.S385906. PMID: 36530590; PMCID: PMC9756794.
Zhou Y, Yang G, Qu C, Chen J, Qian Y, Yuan L, Mao T, Xu Y, Li X, Zhen S, Liu S. Predictive performance of lipid parameters in identifying undiagnosed diabetes and prediabetes: a cross-sectional study in eastern China. BMC Endocr Disord. 2022;22(1):76. doi: 10.1186/s12902-022-00984-x. PMID: 35331213; PMCID: PMC8952267.
Zhang L, Zeng L. Non-linear association of triglyceride-glucose index with prevalence of prediabetes and diabetes: a cross-sectional study. Front Endocrinol (Lausanne). 2023; 14:1295641. doi: 10.3389/fendo.2023.1295641. PMID: 38152130; PMCID: PMC10751584.
Li M, Zhang W, Zhang M, Li L, Wang D, Yan G, et al. Nonlinear relationship between untraditional lipid parameters and the risk of prediabetes: a large retrospective study based on Chinese adults. Cardiovasc Diabetol. 2024 ;23(1):12. doi: 10.1186/s12933-023-02103-z. PMID: 38184606; PMCID: PMC10771669.
Mohammadi F, Yadegar A, Rabizadeh S, Ayati A, Seyedi SA, Nabipoorashrafi SA, et al. Correlates of normal and decreased HDL cholesterol levels in type 2 diabetes: a cohort-based cross-sectional study. Lipids Health Dis. 2024; 23(1):18. doi: 10.1186/s12944-024-02010-6. PMID: 38243302; PMCID: PMC10797913.
Seifi N, Nosrati M, Koochackpoor G, Aghasizadeh M, Bahari H, Namdar HB, et al. The association between hyperuricemia and insulin resistance surrogates, dietary- and lifestyle insulin resistance indices in an Iranian population: MASHAD cohort study. Nutr J. 2024;23(1):5. doi: 10.1186/s12937-023-00904-2. PMID: 38172828; PMCID: PMC10765631.
Zhang Z, Rodriguez M, Zheng Z. Clot or Not? Reviewing the Reciprocal Regulation Between Lipids and Blood Clotting. Arterioscler Thromb Vasc Biol. 2024;44(3):533-544. doi: 10.1161/ATVBAHA.123.318286. PMID: 38235555; PMCID: PMC10922732.
Waksman R, Merdler I, Case BC, Waksman O, Porto I. Targeting inflammation in atherosclerosis: overview, strategy and directions. EuroIntervention. 2024;20(1):32-44. doi: 10.4244/EIJ-D-23-00606. PMID: 38165117; PMCID: PMC10756224.
Nordestgaard BG, Langlois MR, Langsted A, Chapman MJ, Aakre KM, Baum H, et al; European Atherosclerosis Society (EAS) and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Joint Consensus Initiative. Quantifying atherogenic lipoproteins for lipid-lowering strategies: Consensus-based recommendations from EAS and EFLM. Atherosclerosis. 2020; 294:46-61. doi: 10.1016/j.atherosclerosis.2019.12.005. PMID: 31928713.
Hegele RA, Borén J, Ginsberg HN, Arca M, Averna M, Binder CJ, et al. Rare dyslipidaemias, from phenotype to genotype to management: a European Atherosclerosis Society task force consensus statement. Lancet Diabetes Endocrinol. 2020; 8(1):50-67. doi: 10.1016/S2213-8587(19)30264-5. PMID: 31582260.
Pavlatos N, Kalra DK. The Role of Lipoprotein(a) in Peripheral Artery Disease. Biomedicines. 2024;12(6):1229. doi: 10.3390/biomedicines12061229. PMID: 38927436; PMCID: PMC11200468.
Castillo-Núñez Y, Morales-Villegas E, Aguilar-Salinas CA. Triglyceride-Rich Lipoproteins: Their Role in Atherosclerosis. Rev Invest Clin. 2022;74(2):061-070. doi: 10.24875/RIC.21000416. PMID: 34759386.
Xu D, Xie L, Cheng C, Xue F, Sun C. Triglyceride-rich lipoproteins and cardiovascular diseases. Front Endocrinol (Lausanne). 2024; 15:1409653. doi: 10.3389/fendo.2024.1409653. PMID: 38883601; PMCID: PMC11176465.
Kosmas CE, Rodriguez Polanco S, Bousvarou MD, Papakonstantinou EJ, Peña Genao E, Guzman E, Kostara CE. The Triglyceride/High-Density Lipoprotein Cholesterol (TG/HDL-C) Ratio as a Risk Marker for Metabolic Syndrome and Cardiovascular Disease. Diagnostics (Basel). 2023;13(5):929. doi: 10.3390/diagnostics13050929. PMID: 36900073; PMCID: PMC10001260.
ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer Det al. On behalf of the American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care. 2023; 46(Suppl 1): S19-S40. doi: 10.2337/dc23-S002.
Choi W, Park M, Park S, Park JY, Hong AR, Yoon JH, et al. Combined impact of prediabetes and hepatic steatosis on cardiometabolic outcomes in young adults. Cardiovasc Diabetol. 2024; 23(1):422. doi: 10.1186/s12933-024-02516-4. PMID: 39574105; PMCID: PMC11583572.
Zhou M, Zhu L, Cui X, Feng L, Zhao X, He S, Ping F, Li W, Li Y. The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio as a predictor of insulin resistance but not of β cell function in a Chinese population with different glucose tolerance status. Lipids Health Dis. 2016; 15:104. doi: 10.1186/s12944-016-0270-z. PMID: 27267043; PMCID: PMC4895977.
Elkanawati RY, Sumiwi SA, Levita J. Impact of Lipids on Insulin Resistance: Insights from Human and Animal Studies. Drug Des Devel Ther. 2024; 18:3337-3360. doi: 10.2147/DDDT.S468147. PMID: 39100221; PMCID: PMC11298177.
Zhou Y, Yang G, Qu C, Chen J, Qian Y, Yuan L, Mao T, Xu Y, Li X, Zhen S, Liu S. Predictive performance of lipid parameters in identifying undiagnosed diabetes and prediabetes: a cross-sectional study in eastern China. BMC Endocr Disord. 2022; 22(1):76. doi: 10.1186/s12902-022-00984-x. PMID: 35331213; PMCID: PMC8952267.
Surrati AMQ, Mohammedsaeed W, Alfadhli EM. Anthropometrics and Plasma Atherogenic Index in Saudi Women Madinah KSA. Pak J Med Sci. 2024;40 (3Part-II):364-370. doi: 10.12669/pjms.40.3.8318. PMID: 38356847; PMCID: PMC10862441.
Lelis DF, Calzavara JVS, Santos RD, Sposito AC, Griep RH, Barreto SM, et al. Reference values for the triglyceride to high-density lipoprotein ratio and its association with cardiometabolic diseases in a mixed adult population: The ELSA-Brasil study. J Clin Lipidol. 2021;15(5):699-711. doi: 10.1016/j.jacl.2021.07.005. PMID: 34389285.
Cui H, Liu Q, Wu Y, Cao L. Cumulative triglyceride-glucose index is a risk for CVD: a prospective cohort study. Cardiovasc Diabetol. 2022; 21(1):22. doi: 10.1186/s12933-022-01456-1. PMID: 35144621; PMCID: PMC8830002.
Wu S, Xu L, Wu M, Chen S, Wang Y, Tian Y. Association between triglyceride-glucose index and risk of arterial stiffness: a cohort study. Cardiovasc Diabetol. 2021; 20(1):146. doi: 10.1186/s12933-021-01342-2. PMID: 34271940; PMCID: PMC8285795.
Dimova R, Chakarova N, Serdarova M, Tankova T. Lipid profile is similar in both subjects with high 1-hour postload glucose and 2-hour postload glucose and is related to cardio-metabolic profile in prediabetes. J Diabetes Complications. 2024;38(11):108869. doi: 10.1016/j.jdiacomp.2024.108869. PMID: 39306875.
De Sanctis V, Soliman A, Tzoulis P, Daar S, Pozzobon GC, Kattamis C. A study of isolated hyperglycemia (blood glucose ≥155 mg/dL) at 1-hour of oral glucose tolerance test (OGTT) in patients with β-transfusion dependent thalassemia (β-TDT) followed for 12 years. Acta Biomed. 2021;92(4): e2021322. doi: 10.23750/abm.v92i4.11105. PMID: 34487089; PMCID: PMC8477110.
Jagannathan R, Stefanovski D, Smiley DD, Oladejo O, Cotten LF, Umpierrez G, et al. 1-h Glucose during oral glucose tolerance test predicts hyperglycemia relapse-free survival in obese black patients with hyperglycemic crises. Front Endocrinol (Lausanne). 2022; 13:871965. doi: 10.3389/fendo.2022.871965. PMID: 35721763; PMCID: PMC9202609.
Mulla IG, Anjankar A, Shinde A, Pratinidhi S, Agrawal SV, Gundpatil DB, et al. Comparison of Lipid Profiles Between Prediabetic and Non-prediabetic Young Adults. Cureus. 2024; 16(7): e65251. doi: 10.7759/cureus.65251. PMID: 39184606; PMCID: PMC11343337.
Kojta I, Chacińska M, Błachnio-Zabielska A. Obesity, Bioactive Lipids, and Adipose Tissue Inflammation in Insulin Resistance. Nutrients. 2020; 12(5):1305. doi: 10.3390/nu12051305. PMID: 32375231; PMCID: PMC7284998.
Manterola C, Quiroz G, Salazar P, García N. Metodología de los tipos y diseños de estudio más frecuentemente utilizados en investigación clínica. Revista Médica Clínica Las Condes. 2019; 30(1): 36-49. https://doi.org/10.1016/j.rmclc.2018.11.005.
Asamblea Nacional del Ecuador. Ley Orgánica de Protección de Datos Personales. 2021. Disponible en: https://www.telecomunicaciones.gob.ec/wp-content/uploads/2021/06/Ley-Organica-de-Datos-Personales.pdf
Asociación Médica Mundial. Declaración de Helsinki. Principios Éticos para las Investigaciones Médicas en seres humanos. 2020. Disponible en https://www.wma.net/es/policies-post/declaracion-de-helsinki-de-la-amm-principios-eticos-para-las-investigaciones-medicas-en-seres-humanos/
Ministerio de Salud Pública del Ecuador. Manual: Gestión interna de los residuos y desechos generados en los establecimientos de salud. Quito. 2019. Disponible en: https://aplicaciones.msp.gob.ec/salud/archivosdigitales/documentosDirecciones/dnn/archivos/AC00036-2019.pdf.
Mulla IG, Anjankar A, Pratinidhi S, Agrawal SV, Gundpatil D, Lambe SD. Prediabetes: A Benign Intermediate Stage or a Risk Factor in Itself? Cureus. 2024; 16(6):e63186. doi: 10.7759/cureus.63186. PMID: 39070421; PMCID: PMC11273947.
Valdivieso J, Alvarado D, Cango A, Gaona J, Jiménez A, Mejía J. Confiabilidad del Test de Riesgo de Diabetes Tipo 2 de la Asociación Americana de Diabetes como Cribado para Prediabetes en los Visitantes de SOLCA Núcleo de Loja. Ciencia Latina. 2024; 8(2). https://doi.org/10.37811/cl_rcm.v8i2.10541
Rivadeneira J, Fuenmayor-González L, Jácome-García M, Flores-Lastra N, Delgado H, Otzen T. Impact of COVID-19 on the prevalence of dyslipidemia in Ecuador: A cross-sectional study between 2017 and 2022. Aten Primaria. 2024;57(4):103007. doi: 10.1016/j.aprim.2024.103007. PMID: 39426052; PMCID: PMC11533009.
Encalada L, Arias A, Yupa M, Paute P, Wong S. Dislipidemia y estado nutricional en adultos mayores urbanos de la sierra ecuatoriana. Rev Med Ateneo. 2019; 21 (1): 13-30. Disponible en: https://www.colegiomedicosazuay.ec/ojs/index.php/ateneo/article/view/89
Zhang Z, Wang C, Lin C, Wu Y, Wei J, Lu J, et al. Association of long-term exposure to ozone with cardiovascular mortality and its metabolic mediators: evidence from a nationwide, population-based, prospective cohort study. Lancet Reg Health West Pac. 2024; 52:101222. doi: 10.1016/j.lanwpc.2024.101222. PMID: 39444716; PMCID: PMC11497431.
Pirillo A, Casula M, Olmastroni E, Norata GD, Catapano AL. Global epidemiology of dyslipidaemias. Nat Rev Cardiol. 2021;18(10):689-700. doi: 10.1038/s41569-021-00541-4. PMID: 33833450.
Jose JS, Madhu Latha K, Bhongir AV, Sampath S, Pyati AK. Evaluating Dyslipidemia and Atherogenic Indices as Predictors of Coronary Artery Disease Risk: A Retrospective Cross-Sectional Study. Cureus. 2024;16(10):e71187. doi: 10.7759/cureus.71187. PMID: 39525120; PMCID: PMC11550104.
Spohn O, Morkem R, Singer AG, Barber D. Prevalence and management of dyslipidemia in primary care practices in Canada. Can Fam Physician. 2024; 70(3):187-196. doi: 10.46747/cfp.7003187. PMID: 38499368; PMCID: PMC11280621.
Wei X, Ouyang F, Liu Y, Du Q. Prevalence of dyslipidemia among teachers in China: a systematic review and meta-analysis. Front Public Health. 2024; 12:1425387. doi: 10.3389/fpubh.2024.1425387. PMID: 39319293; PMCID: PMC11421384.
Shafiee A, Kazemian S, Jalali A, Alaeddini F, Saadat S, Masoudkabir F, et al. Epidemiology and Prevalence of Dyslipidemia Among Adult Population of Tehran: The Tehran Cohort Study. Arch Iran Med. 2024;27(2):51-61. doi: 10.34172/aim.2024.10. PMID: 38619028; PMCID: PMC11017263.
Virgen-Carrillo LR, Díaz-Sandoval L, Rossi M, Pedernera GO, Duarte ER, Pascua JA, et al. Rationale and Design of the Latin-American Registry of Peripheral Interventions: Insights From SOLACI Peripheral. J Soc Cardiovasc Angiogr Interv. 2024;3(7):101931. doi: 10.1016/j.jscai.2024.101931. PMID: 39132002; PMCID: PMC11307582.
Formagini T, Brooks JV, Roberts A, Bullard KM, Zhang Y, Saelee R, O'Brien MJ. Prediabetes prevalence and awareness by race, ethnicity, and educational attainment among U.S. adults. Front Public Health. 2023; 11:1277657. doi: 10.3389/fpubh.2023.1277657. PMID: 38164446; PMCID: PMC10758124.
Jin C, Lai Y, Li Y, Teng D, Yang W, et al. China National Diabetes and Metabolic Disorders Study Group and the Thyroid Disorders, Iodine Status and Diabetes Epidemiological Survey Group. Changes in the prevalence of diabetes and control of risk factors for diabetes among Chinese adults from 2007 to 2017: An analysis of repeated national cross-sectional surveys. J Diabetes. 2024; 16(2): e13492. doi: 10.1111/1753-0407.13492. PMID: 37927176; PMCID: PMC10859318.
do Vale Moreira NC, Hussain A, Bhowmik B, Mdala I, Siddiquee T, Fernandes VO, et al. Prevalence of Metabolic Syndrome by different definitions, and its association with type 2 diabetes, pre-diabetes, and cardiovascular disease risk in Brazil. Diabetes Metab Syndr. 2020; 14(5):1217-1224. doi: 10.1016/j.dsx.2020.05.043. PMID: 32682310.
Martorell M, Opazo M, Ramírez-Alarcón K, Labraña AM, Nazar G, Villagrán M, et al. Prevalencia de prediabesidad y diabesidad en Chile: Resultados de la Encuesta Nacional de Salud 2016-2017. Rev Med Chil. 2024; 152(2):178-186. doi: 10.4067/s0034-98872024000200178. PMID: 39450795.
Peralta HM, Costa Gil JE, Saleme AE. Evaluación del puntaje FINDRISC para detección de prediabetes y diabetes tipo 2 sin diagnóstico [FINDRISC as screening for detection of prediabetes and unknown type 2 diabetes]. Medicina (B Aires). 2024;84(1):1-10. Spanish. PMID: 38271927.
Wu J, Huang J, Hong M, Xia L, Lin Y, Chen Y, et al. Association of triglyceride-glucose index with diabetes or prediabetes in Chinese hypertensive patients: A retrospective cohort study. Medicine (Baltimore). 2024;103(41): e40006. doi: 10.1097/MD.0000000000040006. PMID: 39465859; PMCID: PMC11479436.
Jiang J, Chen M, Li R, Zhu J, Qin F, Peng Q. Association of remnant cholesterol with progression and regression of prediabetes in middle-aged and older adults: a nationwide cohort study. Acta Diabetol. 2024. doi: 10.1007/s00592-024-02416-9. PMID: 39565373.
Xu Z, Liu D, Zhai Y, Tang Y, Jiang L, Li L, Wu Q. Association between the oxidative balance score and all-cause and cardiovascular mortality in patients with diabetes and prediabetes. Redox Biol. 2024; 76:103327. doi: 10.1016/j.redox.2024.103327. PMID: 39186882; PMCID: PMC11389538.
DOI: https://doi.org/10.23857/pc.v10i1.8759
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