The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data

Background: Achieving an optimal glycemic control has been described to reduce the incidence of diabetes mellitus (DM) related complications. The association between comorbidities and glycemic control remains unclear. Our aim is to evaluate the effect of comorbidities on glycemic control in people l...

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Autores:
Urina-Jassir, Manuel
Herrera-Parra, Lina Johana
Hernández Vargas, Juliana Alexandra
Valbuena-García, Ana María
Acuña-Merchán, Lizbeth
Urina-Triana, Miguel
Tipo de recurso:
Fecha de publicación:
2021
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/7933
Acceso en línea:
https://hdl.handle.net/20.500.12442/7933
https://doi.org/10.1186/s12902-021-00791-w
https://bmcendocrdisord.biomedcentral.com/articles/10.1186/s12902-021-00791-w
Palabra clave:
Glycated hemoglobin A1c
Diabetes mellitus
Comorbidity
Hypertension
Chronic kidney Disease
Obesity
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openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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dc.title.eng.fl_str_mv The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
title The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
spellingShingle The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
Glycated hemoglobin A1c
Diabetes mellitus
Comorbidity
Hypertension
Chronic kidney Disease
Obesity
title_short The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
title_full The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
title_fullStr The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
title_full_unstemmed The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
title_sort The effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world data
dc.creator.fl_str_mv Urina-Jassir, Manuel
Herrera-Parra, Lina Johana
Hernández Vargas, Juliana Alexandra
Valbuena-García, Ana María
Acuña-Merchán, Lizbeth
Urina-Triana, Miguel
dc.contributor.author.none.fl_str_mv Urina-Jassir, Manuel
Herrera-Parra, Lina Johana
Hernández Vargas, Juliana Alexandra
Valbuena-García, Ana María
Acuña-Merchán, Lizbeth
Urina-Triana, Miguel
dc.subject.eng.fl_str_mv Glycated hemoglobin A1c
Diabetes mellitus
Comorbidity
Hypertension
Chronic kidney Disease
Obesity
topic Glycated hemoglobin A1c
Diabetes mellitus
Comorbidity
Hypertension
Chronic kidney Disease
Obesity
description Background: Achieving an optimal glycemic control has been described to reduce the incidence of diabetes mellitus (DM) related complications. The association between comorbidities and glycemic control remains unclear. Our aim is to evaluate the effect of comorbidities on glycemic control in people living with DM. Methods: A retrospective longitudinal study on data from the National Registry of Chronic Kidney Disease from 2014 to 2019 in Colombia. The outcome was poor glycemic control (PGC = HbA1c ≥7.0%). The association between each comorbidity (hypertension (HTN), chronic kidney disease (CKD) or obesity) and PGC was evaluated through multivariate mixed effects logistic regression models. The measures of effect were odds ratios (OR) and their 95% confidence intervals (CI). We also evaluated the main associations stratified by gender, insurance, and early onset diabetes as well as statistical interaction between each comorbidity and ethnicity. Results: From 969,531 people at baseline, 85% had at least one comorbidity; they were older and mostly female. In people living with DM and CKD, the odds of having a PGC were 78% (OR: 1.78, CI 95%: 1.55-2.05) higher than those without CKD. Same pattern was observed in obese for whom the odds were 52% (OR: 1.52, CI 95%: 1.31-1.75) higher than in non-obese. Non-significant association was found between HTN and PGC. We found statistical interaction between comorbidities and ethnicity (afro descendant) as well as effect modification by health insurance and early onset DM. Conclusions: Prevalence of comorbidities was high in adults living with DM. Patients with concomitant CKD or obesity had significantly higher odds of having a PGC.
publishDate 2021
dc.date.accessioned.none.fl_str_mv 2021-06-30T13:34:16Z
dc.date.available.none.fl_str_mv 2021-06-30T13:34:16Z
dc.date.issued.none.fl_str_mv 2021
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dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12442/7933
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1186/s12902-021-00791-w
dc.identifier.url.none.fl_str_mv https://bmcendocrdisord.biomedcentral.com/articles/10.1186/s12902-021-00791-w
identifier_str_mv 14726823
url https://hdl.handle.net/20.500.12442/7933
https://doi.org/10.1186/s12902-021-00791-w
https://bmcendocrdisord.biomedcentral.com/articles/10.1186/s12902-021-00791-w
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv pdf
dc.publisher.eng.fl_str_mv BMC
dc.source.eng.fl_str_mv BMC Endocrine Disorders
dc.source.none.fl_str_mv Vol. 21 N° 128, (2021)
institution Universidad Simón Bolívar
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spelling Urina-Jassir, Manuel60d141eb-2887-4306-9bef-c7eb18b11e7bHerrera-Parra, Lina Johanab319405f-ba6d-4411-b3a0-746a3fee827fHernández Vargas, Juliana Alexandra39fd203c-9585-4839-8caa-c23939e6e65eValbuena-García, Ana Maríab8e01f7f-a74e-4a4c-9da6-3e152f910fd7Acuña-Merchán, Lizbeth2151a46b-080e-47f7-8b8e-011f37bbab42Urina-Triana, Migueld749d19c-0dae-4d0b-8e9a-6d623d682f9e2021-06-30T13:34:16Z2021-06-30T13:34:16Z202114726823https://hdl.handle.net/20.500.12442/7933https://doi.org/10.1186/s12902-021-00791-whttps://bmcendocrdisord.biomedcentral.com/articles/10.1186/s12902-021-00791-wBackground: Achieving an optimal glycemic control has been described to reduce the incidence of diabetes mellitus (DM) related complications. The association between comorbidities and glycemic control remains unclear. Our aim is to evaluate the effect of comorbidities on glycemic control in people living with DM. Methods: A retrospective longitudinal study on data from the National Registry of Chronic Kidney Disease from 2014 to 2019 in Colombia. The outcome was poor glycemic control (PGC = HbA1c ≥7.0%). The association between each comorbidity (hypertension (HTN), chronic kidney disease (CKD) or obesity) and PGC was evaluated through multivariate mixed effects logistic regression models. The measures of effect were odds ratios (OR) and their 95% confidence intervals (CI). We also evaluated the main associations stratified by gender, insurance, and early onset diabetes as well as statistical interaction between each comorbidity and ethnicity. Results: From 969,531 people at baseline, 85% had at least one comorbidity; they were older and mostly female. In people living with DM and CKD, the odds of having a PGC were 78% (OR: 1.78, CI 95%: 1.55-2.05) higher than those without CKD. Same pattern was observed in obese for whom the odds were 52% (OR: 1.52, CI 95%: 1.31-1.75) higher than in non-obese. Non-significant association was found between HTN and PGC. We found statistical interaction between comorbidities and ethnicity (afro descendant) as well as effect modification by health insurance and early onset DM. Conclusions: Prevalence of comorbidities was high in adults living with DM. Patients with concomitant CKD or obesity had significantly higher odds of having a PGC.pdfengBMCAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2BMC Endocrine DisordersVol. 21 N° 128, (2021)Glycated hemoglobin A1cDiabetes mellitusComorbidityHypertensionChronic kidney DiseaseObesityThe effect of comorbidities on glycemic control among Colombian adults with diabetes mellitus: a longitudinal approach with real-world datainfo:eu-repo/semantics/articleArtículo científicohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_2df8fbb1Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. 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.Vargas-Uricoechea H, Casas-Figueroa LÁ. An epidemiologic analysis of diabetes in Colombia. Ann Glob Health. 2015;81:742–53.Harding JL, Pavkov ME, Magliano DJ, Shaw JE, Gregg EW. Global trends in diabetes complications: a review of current evidence. Diabetologia. 2019;62: 3–16.Herman WH, Braffett BH, Kuo S, Lee JM, Brandle M, Jacobson AM, et al. What are the clinical, quality-of-life, and cost consequences of 30 years of excellent vs. poor glycemic control in type 1 diabetes? J Diabetes Complicat. 2018;32:911–5.Zoungas S, Arima H, Gerstein HC, Holman RR, Woodward M, Reaven P, et al. Effects of intensive glucose control on microvascular outcomes in patients with type 2 diabetes: a meta-analysis of individual participant data from randomised controlled trials. Lancet Diabetes Endocrinol. 2017;5:431–7.Ray KK, Seshasai SRK, Wijesuriya S, Sivakumaran R, Nethercott S, Preiss D, et al. Effect of intensive control of glucose on cardiovascular outcomes and death in patients with diabetes mellitus: a meta-analysis of randomised controlled trials. Lancet. 2009;373:1765–72.Hayward RA, Reaven PD, Wiitala WL, Bahn GD, Reda DJ, Ge L, et al. Followup of glycemic control and cardiovascular outcomes in type 2 diabetes. N Engl J Med. 2015;372:2197–206.Mannucci E, Monami M, Dicembrini I, Piselli A, Porta M. Achieving HbA1c targets in clinical trials and in the real world: a systematic review and metaanalysis. J Endocrinol Investig. 2014;37:477–95.De Pablos-Velasco P, Parhofer KG, Bradley C, Eschwège E, Gönder-Frederick L, Maheux P, et al. Current level of glycaemic control and its associated factors in patients with type 2 diabetes across Europe: Data from the PANORAMA study. Clin Endocrinol (Oxf). 2014;80:47–56.Smalls BL, Ritchwood TD, Bishu KG, Egede LE. Racial/ethnic differences in glycemic control in older adults with type 2 diabetes: United States 2003– 2014. Int J Environ Res Public Health. 2020;17:950.Suh DC, Choi IS, Plauschinat C, Kwon J, Baron M. Impact of comorbid conditions and race/ethnicity on glycemic control among the US population with type 2 diabetes, 1988-1994 to 1999-2004. J Diabetes Complicat. 2010;24:382–91.Chetoui A, Kaoutar K, Elmoussaoui S, Boutahar K, El Kardoudi A, Chigr F, et al. Prevalence and determinants of poor glycaemic control: a crosssectional study among Moroccan type 2 diabetes patients. Int Health. 2020; 00:1–8.Iglay K, Hannachi H, Howie PJ, Xu J, Li X, Engel SS, et al. Prevalence and coprevalence of comorbidities among patients with type 2 diabetes mellitus. Curr Med Res Opin. 2016;32:1243–52.Luijks H, Biermans M, Bor H, van Weel C, Lagro-Janssen T, de Grauw W, et al. The effect of comorbidity on glycemic control and systolic blood pressure in type 2 diabetes: a cohort study with 5 year follow-up in primary care. PLoS One. 2015;10:e0138662.Bralić Lang V, Bergman MB. Prevalence of comorbidity in primary care patients with type 2 diabetes and its association with elevated HbA1c: a cross-sectional study in Croatia. Scand J Prim Health Care. 2016;34:66–72.Hudon C. Comorbidity and glycemia control among patients with type 2 diabetes in primary care. Diabetes Metab Syndr Obes Targets Ther. 2008;1: 33–7.Almetwazi M, Alwhaibi M, Balkhi B, Almohaini H, Alturki H, Alhawassi T, et al. Factors associated with glycemic control in type 2 diabetic patients in Saudi Arabia. Saudi Pharm J. 2019;27:384–8.Alzaheb R, Altemani A. The prevalence and determinants of poor glycemic control among adults with type 2 diabetes mellitus in Saudi Arabia. Diabetes Metab Syndr Obes Targets Ther. 2018;11:15–21.Ministerio de Salud y Proteccion Social - Republica de Colombia. Resolucion 2643 del 2014; 2014. p. 1–13. https://cuentadealtocosto.org/site/wpcontent/ uploads/2019/10/Resolucion-02463-de-2014-ERC.pdf. Accessed 9 Oct 2020Ministerio de Salud y Proteccion Social - Republica de Colombia. Cifras de aseguramiento en salud con corte diciembre 2020. 2020. https://www. minsalud.gov.co/proteccionsocial/Paginas/cifras-aseguramiento-salud.aspx. Accessed 19 Jan 2021.Ministerio de Salud y Protección Social de Colombia. Guía de práctica clínica Hipertensión arterial primaria (HTA). 2013. https://www.minsalud.gov. co/sites/rid/Lists/BibliotecaDigital/RIDE/INEC/IETS/GPC_Completa_HTA.pdf. Accessed 22 Apr 2021.WHO Consultation on Obesity (1999:Geneva Switzerland) & World Health Organization. Obesity: Preventing and managing the global epidemic: Report of a WHO Consultation (WHO Technical Report Series 894). 2000:1- 252. https://apps.who.int/iris/handle/10665/42330. Accessed 9 Oct 2020.American Diabetes Association. 6. Glycemic Targets: Standards of Medical Care in Diabetes-2020. Diabetes Care. 2020;43(Suppl. 1):S66–76.Levey AS, Stevens LA, Schmid CH, Zhang Y (Lucy), Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150:604–12.Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl. 2013;3:1–150.Yang D, Dalton JE. A unified approach to measuring the effect size between two groups using SAS®. SAS Glob Forum Stat Data Anal. 2012;335:1–6.Wilmot E, Idris I. Early onset type 2 diabetes: risk factors, clinical impact and management. Ther Adv Chronic Dis. 2014;5:234–44.Kidney Disease: Improving Global Outcomes (KDIGO) Diabetes Work Group. KDIGO 2020 clinical practice guideline for diabetes management in chronic kidney disease. Kidney Int. 2020;98:S1–115.Sosa-Rubí SG, Galárraga O, López-Ridaura R. Diabetes treatment and control: the effect of public health insurance for the poor in Mexico. Bull World Health Organ. 2009;87:512–9.Zhang X, McKeever Bullard K, Gregg EW, Beckles GL, Williams DE, Barker LE, et al. Access to health care and control of ABCS of diabetes. Diabetes Care. 2012;35:1566–71.Copur S, Onal EM, Afsar B, Ortiz A, van Raalte DH, Cherney DZ, et al. Diabetes mellitus in chronic kidney disease: biomarkers beyond HbA1c to estimate glycemic control and diabetes-dependent morbidity and mortality. J Diabetes Complicat. 2020;34:107707.De Cosmo S, Viazzi F, Pacilli A, Giorda C, Ceriello A, Gentile S, et al. Achievement of therapeutic targets in patients with diabetes and chronic kidney disease: insights from the Associazione Medici Diabetologi annals initiative. Nephrol Dial Transplant. 2015;30:1526–33.Bae JP, Lage MJ, Mo D, Nelson DR, Hoogwerf BJ. Obesity and glycemic control in patients with diabetes mellitus: analysis of physician electronic health records in the US from 2009-2011. J Diabetes Complicat. 2016;30: 212–20.Speeckaert M, Van Biesen W, Delanghe J, Slingerland R, Wiecek A, Heaf J, et al. Are there better alternatives than haemoglobin A1c to estimate glycaemic control in the chronic kidney disease population? Nephrol Dial Transplant. 2014;29:2167–77.Hill CJ, Maxwell AP, Cardwell CR, Freedman BI, Tonelli M, Emoto M, et al. Glycated hemoglobin and risk of death in diabetic patients treated with hemodialysis: a meta-analysis. Am J Kidney Dis. 2014;63:84–94.Kuo I-C, Lin HY-H, Niu S-W, Hwang D-Y, Lee J-J, Tsai J-C, et al. Glycated hemoglobin and outcomes in patients with advanced diabetic chronic kidney Disease. Sci Rep. 2016;6:20028.Esteghamati A, Ismail-Beigi F, Khaloo P, Moosaie F, Alemi H, Mansournia MA, et al. Determinants of glycemic control: phase 2 analysis from nationwide diabetes report of National Program for prevention and control of diabetes (NPPCD-2018). Prim Care Diabetes. 2020;14:222–31.Gummesson A, Nyman E, Knutsson M, Karpefors M. Effect of weight reduction on glycated haemoglobin in weight loss trials in patients with type 2 diabetes. Diabetes Obes Metab. 2017;19:1295–305.Bo A, Thomsen RW, Nielsen JS, Nicolaisen SK, Beck-Nielsen H, Rungby J, et al. Early-onset type 2 diabetes: age gradient in clinical and behavioural risk factors in 5115 persons with newly diagnosed type 2 diabetes-results from the DD2 study. Diabetes Metab Res Rev. 2018;34:e2968.Gopalan A, Mishra P, Alexeeff SE, Blatchins MA, Kim E, Man A, et al. Initial glycemic control and care among younger adults diagnosed with type 2 diabetes. Diabetes Care. 2020;43:975–81.Badedi M, Solan Y, Darraj H, Sabai A, Mahfouz M, Alamodi S, et al. Factors associated with long-term control of type 2 diabetes mellitus. J Diabetes Res. 2016;2016:2109542.Menzin J, Korn JR, Cohen J, Lobo F, Zhang B, Friedman M, et al. Relationship between glycemic control and diabetes-related hospital costs in patients with type 1 or type 2 diabetes mellitus. J Manag Care Pharm. 2010;16:264–75.Gil J, Sicras-Mainar A, Zucchelli E. Uncontrolled diabetes and health care utilisation: panel data evidence from Spain. Eur J Health Econ. 2018;19:785–95.Mata-Cases M, Rodríguez-Sánchez B, Mauricio D, Real J, Vlacho B, Franch- Nadal J, et al. The association between poor glycemic control and health care costs in people with diabetes: a population-based study. Diabetes Care. 2020;43:751–8.Ministerio de Salud y Protección Social de Colombia. Guía de Práctica Clínica para el manejo de la hipertensión arterial primaria (HTA). 2017; 2da edición. Guía No.18. http://gpc.minsalud.gov.co/gpc_sites/Repositorio/ Conv_500/GPC_hta/gpc_hta_profesionales.aspx. Accessed 22 Apr 2021.Ministerio de Salud y Protección Social de Colombia. Guía de Práctica Clínica para el diagnóstico y tratamiento de la Enfermedad Renal Crónica (adopción). 2016. http://gpc.minsalud.gov.co/gpc_sites/Repositorio/Otros_ conv/GPC_e_renal/gpc_e_renal_completa.aspx. Accessed 22 Apr 2021.Departamento Administrativo Nacional de Estadistica (DANE). Cuentas departamentales, Producto Interno Bruto por departamento 2019 preliminar; 2020. p. 7–8. https://www.dane.gov.co/files/investigaciones/pib/ departamentales/B_2015/Bol_dptal_2019preliminar.pdf. Accessed 10 Nov 2020.Ministerio de Salud y Protección Social de Colombia. Todo lo que usted debe saber sobre el plan de beneficios POS. 2014. https://www.minsalud. gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/VP/RBC/todo-lo-que-usted-debesaber- sobre-el-plan-de-beneficios.pdf. Accessed 7 May 2021.Lerman-Garber I, Aguilar-Salinas C, Tusié-Luna T, Velásquez D, Lobato- Valverde M, Osornio-Flores M, et al. Diabetes tipo 2 de inicio temprano. Experiencia en una institución de tercer nivel de atención médica. 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