The effect of cardiometabolic control and malnutrition on the prevalence and prognosis of diabetic retinopathy in type 2 diabetes

Year 2024, Volume: 17 Issue: 3, 420 - 429, 05.07.2024

Melek Özdemir , Yaşar Dağ , Mehmet Uzunlulu , Aytekin Oğuz , Aylin Ardagil , Ömer Acar , Bensu Selbest

https://doi.org/10.31362/patd.1419095

Abstract

Purpose: This study aims to investigate the predictive value of cardiometabolic control, gamma glutamyl transferase (GGT) and malnutrition-related inflammation markers for predicting diabetic retinopathy (DR) prevalence and prognosis.
Materials and methods: Type 2 Diabetes Mellitus patients who were consecutively admitted to Internal and Ophthalmology outpatient clinics were included in this study. Clinical, haematological and biochemical data were recorded. Cut-off values of GGT, hemoglobin, albumin, lymphocyte and platelet (HALP) score, nutritional risk index (NRI) and prognostic nutritional index (PNI) scores were determined by receiver operator characteristic curve analysis. Univariate and multivariate analyses were performed to determine the association of all variables with DR. We evaluated which of these tests were predictive and prognostic for the development of DR.
Results: This study included 166 patients. Fasting blood glucose (p<0.001), creatinine (p=0.01), HbA1c (p<0.001) and microalbuminuria (p=0.01) were higher in patients with retinopathy. Mean arterial pressure (p=0.01), fasting blood glucose (p=0.03), triglyceride (p=0.008), body mass index (BMI) (p=0.02) and HbA1c (p=0.04) increased significantly as GGT level increased. Contrary to the literature, HALP, PNI and NRI scores were not associated with DR.
Conclusion: Duration of diabetes, cardiometabolic control and GGT level are variables with predictive value for the prognosis of DR. No significant

Keywords

Diabetic retinopathy, cardiometabolic control, GGT, malnutrition releated inflamation markers

Ethical Statement

Bu çalışmayla ilgili gerekli izin, İstanbul Medeniyet Üniversitesi Göztepe Eğitim ve Araştırma Hastanesi Etik Komisyonu tarafından verildi (Tarih:01.08.2013, Karar No:2013/0036).

Supporting Institution

yok

Project Number

1

Thanks

TEZ danışmanım Mehmet Uzunlulu ve çalışmada emeği geçen hocalarıma çok teşekkür ediyorum

Tip 2 diyabette kardiyometabolik kontrol ve malnütrisyonun diyabetik retinopati prevalansı ve prognozuna etkisi

Abstract

Amaç: Bu çalışmanın amacı kardiyometabolik kontrol, gama glutamil transferaz (GGT) ve malnütrisyonla ilişkili inflamasyon belirteçlerinin diyabetik retinopati (DR) prevalansı ve prognozunu öngörmedeki değerini araştırmaktır.
Gereç ve yöntem: Bu çalışmaya Dahiliye ve Göz Hastalıkları polikliniklerine ardışık olarak başvuran Tip 2 Diabetes Mellitus hastaları dahil edilmiştir. Klinik, hematolojik ve biyokimyasal veriler kaydedildi. Alıcı operatör karakteristik eğri analizi ile GGT, hemoglobin, albümin, lenfosit ve trombosit (HALP) skoru, nutrisyonel risk indeksi (NRI) ve prognostik nutrisyonel indeks (PNI) skorlarının cut-off değerleri belirlendi. Tüm değişkenlerin DR ile ilişkisini belirlemek için tek değişkenli ve çok değişkenli analizler yapıldı. Bu testlerden hangilerinin DR gelişimi için öngörücü ve prognostik olduğu değerlendirilmiştir.
Bulgular: Bu çalışmaya 166 Tip 2 Diyabetes Mellitus hastası dahil edildi. Retinopati olanlarda; açlık kan glukozu (p<0,001), kreatinin (p=0,01), HbA1c (p<0,001) ve mikroalbüminüri (p=0,01) yüksek bulundu. Hastaların GGT düzeyi arttıkça ortalama arteriyel basınç (p=0,01), açlık kan glukoz (p=0,03), trigliserit (p=0,008), vücut kütle indeksi (BMI) (p=0,02) ve HbA1c (p=0,04) değerlerinin anlamlı arttığı bulundu. Literatürün aksine HALP, PNI ve NRI skorun DR ile anlamlı ilişki saptanmadı.
Sonuç: Diyabet süresi, kardiyometabolik kontrol ve GGT düzeyi diyabetik retinopati prognozu için prediktif değeri olan değişkenlerdir. Malnütrisyonla ilişkili inflamasyon belirteçleri ile DR gelişimi ve evresi arasında anlamlı bir ilişki bulunmamıştır.

Keywords

Diyabetik retinopati, kardiyometabolik kontrol, GGT, malnutrisyon ilişkili inflamasyon belirteçleri

Project Number

1

References

• 1. GBD 2021 diabetes collaborators. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the global burden of disease study 2021. Lancet 2023;402:203-234. https://doi.org/10.1016/S0140-6736(23)01301-6
• 2. Satman I, Yilmaz T, Sengül A, et al. Population based study of diabetes and risk characteristics in Turkey: results of the Turkish diabetes epidemiology study (TURDEP). Diabetes care 2002;25:1551-1556. https://doi.org/10.2337/diacare.25.9.1551
• 3. Satman I, Omer B, Tutuncu Y, et al. Twelve year trends in the prevalence and risk factors of diabetes and prediabetes in Turkish adults. Eur J Epidemiol 2013;28:169-180. https://doi.org/10.1007/s10654-013-9771-5
• 4. Klein R, Klein BE, Moss SE. Epidemiology of proliferative diabetic retinopathy. Diabetes care 1992;15:1875-1891. https://doi.org/10.2337/diacare.15.12.1875
• 5. Ghamdi AHA. Clinical predictors of diabetic retinopathy progression: a systematic review. Curr Diabetes Rev 2020;16:242-247. https://doi.org/10.2174/1573399815666190215120435
• 6. Henricsson M, Nyström L, Blohmé G, et al. The incidence of retinopathy 10 years after diagnosis in young adult people with diabetes: results from the nationwide population based diabetes incidence study in Sweden (DISS). Diabetes Care 2003;26:349-354. https://doi.org/10.2337/diacare.26.2.349
• 7. Kurtul BE, Koca S, Yilmaz MO. Prognostic nutritional index as a novel marker for diabetic retinopathy in individuals with type 2 diabetes mellitus. Saudi J Ophthalmol 2022;36:322-326. https://doi.org/10.4103/sjopt.sjopt_63_22
• 8. Mohamed Q, Gillies MC, Wong TY. Management of diabetic retinopathy: a systematic review. JAMA 2007;298:902-916. https://doi.org/10.1001/jama.298.8.902
• 9. Sunness JS. The pregnant woman's eye. Surv Ophthalmol 1988;32:219-238. https://doi.org/10.1016/0039-6257(88)90172-5
• 10. Pandit RJ, Taylor R. Mydriasis and glaucoma: exploding the myth. A systematic review. Diabet Med 2000;17:693-699. https://doi.org/10.1046/j.1464-5491.2000.00368.x
• 11. Ozdemir M. Tip 2 diabetes mellitus tanısı olan hastalarda gama glutamil transferaz seviyesinin ve kardiyometabolik risk faktörlerinin diyabetik retinopati evrelemesine etkisi. Yayınlanmamış İç Hastalıkları Uzmanlık Tezi. İstanbul Medeniyet Üniversitesi Göztepe Eğitim ve Araştırma Hastanesi, İç Hastalıkları Anabilim Dalı, İstanbul, 2015.
• 12. Wang W, Lo ACY. Diabetic retinopathy: pathophysiology and treatments. Int J Mol Sci 2018;19:1816. https://doi.org/10.3390/ijms19061816
• 13. Zheng Y, Huang Y, Li H. Hemoglobin albumin lymphocyte and platelet score and all-cause mortality in coronary heart disease: a retrospective cohort study of NHANES database. Front Cardiovasc Med 2023;10:1241217. https://doi.org/10.3389/fcvm.2023.1241217
• 14. Xu M, Chen L, Hu Y, et al. The HALP (hemoglobin, albumin, lymphocyte, and platelet) score is associated with early onset post stroke cognitive impairment. Neurol sci 2023;44:237-245. https://doi.org/10.1007/s10072-022-06414-z
• 15. Xu H, Zheng X, Ai J, Yang L. Hemoglobin, albumin, lymphocyte, and platelet (HALP) score and cancer prognosis: a systematic review and meta-analysis of 13,110 patients. Int Immunopharmacol 2023;114:109496. https://doi.org/10.1016/j.intimp.2022.109496
• 16. Pan H, Lin S. Association of hemoglobin, albumin, lymphocyte, and platelet score with risk of cerebrovascular, cardiovascular, and all cause mortality in the general population: results from the NHANES 1999-2018. Front Endocrinol (Lausanne) 2023;14:1173399. https://doi.org/10.3389/fendo.2023.1173399
• 17. Wei W, Lin R, Li S, et al. Malnutrition ıs associated with diabetic retinopathy in patients with type 2 diabetes. J Diabetes Res 2023;1613727. https://doi.org/10.1155/2023/1613727
• 18. Kohner EM, Patel V, Rassam SM. Role of blood flow and impaired autoregulation in the pathogenesis of diabetic retinopathy. Diabetes 1995;44:603-607. https://doi.org/10.2337/diab.44.6.603
• 19. Ruberte J, Ayuso E, Navarro M, et al. Increased ocular levels of IGF-1 in transgenic mice lead to diabetes like eye disease. J Clin Invest 2004;113:1149-1157. https://doi.org/10.1172/JCI19478
• 20. ElSayed NA, Aleppo G, Aroda VR, et al. Glycemic targets: standards of care in diabetes 2023. Diabetes Care 2023;46:97-110. https://doi.org/10.2337/dc23-S006
• 21. Davies MJ, Aroda VR, Collins BS, et al. Management of hyperglycaemia in type 2 diabetes, 2022. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 2022;65:1925-1966. https://doi.org/10.1007/s00125-022-05787-2
• 22. Rodriguez Gutierrez R, Gonzalez Gonzalez JG, Zuñiga Hernandez JA, McCoy RG. Benefits and harms of intensive glycemic control in patients with type 2 diabetes. BMJ 2019;367:i5887. https://doi.org/10.1136/bmj.l5887
• 23. International clinical classification system for diabetic retinopathy and diabetic macular edema, Global diabetic retinopathy project task force and ınvitational workshop, AAO Hoskins Center for Quality Eye Care 2012. Available at: https://www.aao.org/education/clinical-statement/international-clinical-classification-system-diabe#disqus_thread. Accessed August 01, 2013
• 24. Fawwad A, Butt AM, Siddiqui IA, Khalid M, Sabir R, Basit A. Neutrophil to lymphocyte ratio and microvascular complications in subjects with type 2 diabetes: Pakistan's perspective. Turk J Med Sci 2018;48:157-161. https://doi.org/10.3906/sag-1706-141
• 25. Willis JR, Doan QV, Gleeson M, et al. Vision related functional burden of diabetic retinopathy across severity levels in the United States. JAMA Ophthalmol 2017;135:926-932. https://doi.org/10.1001/jamaophthalmol.2017.2553
• 26. Mazhar K, Varma R, Choudhury F, et al. Severity of diabetic retinopathy and health related quality of life: the Los Angeles latino eye study. Ophthalmology 2011;118:649-655. https://doi.org/10.1016/j.ophtha.2010.08.003
• 27. Leasher JL, Bourne RR, Flaxman SR, et al. Global estimates on the number of people blind or visually ımpaired by diabetic retinopathy: a meta-analysis from 1990 to 2010 Diabetes Care 2016;39:1643-1649. https://doi.org/10.2337/dc15-2171
• 28. Ren J, Zhang S, Pan Y, et al. Diabetic retinopathy: involved cells, biomarkers, and treatments. Front Pharmacol 2022;13:953691. https://doi.org/10.3389/fphar.2022.953691
• 29. Nilssen O, Forde OH, Brenn T. The tromso study. Distribution and population determinants of gamma-glutamyltransferase. Am J Epidemiol 1990;132:318-326. https://doi.org/10.1093/oxfordjournals.aje.a115661
• 30. Perry IJ, Wannamethee SG, Shaper AG. Prospective study of serum gamma-glutamyltransferase and risk of NIDDM. Diabetes Care 1998;21:732-737. https://doi.org/10.2337/diacare.21.5.732
• 31. Lee DH, Blomhoff R, Jacobs DR Jr. Is serum gamma glutamyltransferase a marker of oxidative stress?. Free Radic Res 2004;38:535-539. https://doi.org/10.1080/10715760410001694026
• 32. El Boghdady NA, Badr GA. Evaluation of oxidative stress markers and vascular risk factors in patients with diabetic peripheral neuropathy. Cell Biochem Funct 2012;30:328-334. https://doi.org/10.1002/cbf.2808
• 33. Mohamed Q, Gillies MC, Wong TY. Management of diabetic retinopathy: a systematic review. JAMA 2007;298:902-916. https://doi.org/10.1001/jama.298.8.902
• 34. Perais J, Agarwal R, Evans JR, et al. Prognostic factors for the development and progression of proliferative diabetic retinopathy in people with diabetic retinopathy. Cochrane Database Syst Rev 2023;2:013775. https://doi.org/10.1002/14651858.CD013775.pub2
• 35. Saini DC, Kochar A, Poonia R. Clinical correlation of diabetic retinopathy with nephropathy and neuropathy. Indian J Ophthalmol 2021;69:3364-3368. https://doi.org/10.4103/ijo.IJO_1237_21