Diagnostic performance of urinary biomarkers and self-monitoring blood glucose in estimating microvascular complications in elderly patients with diabetes mellitus

Öz

Aim: In elderly patients, detection of diabetes mellitus (DM)-associated complications is crucial to improve quality of life and prevent serious pathologies. This study aimed to evaluate the diagnostic performance of urine microalbumin-creatinine ratio (uMCR), urine protein-creatinine ratio (uPCR), and self-monitoring blood glucose (SMBG) in estimating microvascular complications, neuropathy, retinopathy, and nephropathy in older adults with DM. Methods: In this diagnostic methodological study, DM patients (n=99) older than 64 years were followed in the endocrinology clinic parameters; serum hemoglobin A1c (HbA1c), serum triglyceride-glucose index (TyG index), the difference between self-measured peak glucose level and nadir level (SMBGdiff), and the ratio of the SMBGdiff to the highest SMBG level (SMNGratio), uMCR and uPCR were evaluated by ROC analysis and their cut-off values and specificity were determined to evaluate the diagnostic power for microvascular complications. Results: Our findings showed that 70% of the patients were male, 48.5% had neuropathy, 25.3% had retinopathy and 25.3% had nephropathy. Although lipid metabolism and liver-related indicators were within the normal range, patients were vitamin D deficient. ROC analysis revealed that uMCR and uPCR levels were independently associated with nephropathy (p<0.001), with strong specificity and moderate sensitivity. SMBGdiff was associated with both retinopathy and neuropathy (p=0.049 and p=0.040), and both specificity and sensitivity were poor. Conclusion: In elderly patients with DM uMCR and uPCR are strong indicators of nephropathy. However, other diabetes-associated biomarkers showed poor correlations emphasizing the age-related complexities in diabetic patients and an urgent need for further research.

Anahtar Kelimeler

• Type 2 diabetes
• retinopathy
• neuropathy
• nephropathy
• urine microalbumin-creatinine ratio
• protein-creatinine ratio

Yaşlı diyabetli hastalarda mikrovasküler komplikasyonları tahmin etmede idrar biyobelirteçlerinin ve kendi kendine kan glikozu izlemenin tanısal performansı

Öz

Amaç: Yaşlı hastalarda yaşam kalitesini artırmak ve ciddi patolojileri önlemek için diabetes mellitus (DM) ile ilişkili komplikasyonların saptanması çok önemlidir. Bu çalışmanın amacı, DM'li yaşlı erişkinlerde üriner mikroalbümin-kreatinin oranı (uMCR), üriner protein-kreatinin oranı (uPCR) ve kendi kendine kan şekeri takibinin (SMBG) nöropati, retinopati ve nefropatiyi gibi mikrovasküler komplikasyonları tahmin etmedeki tanısal performansını değerlendirmektir. Yöntem: Bu tanısal metodolojik çalışmada, endokrinoloji kliniğinde takip edilen 64 yaş üstü DM hastalarının (n=99) serum hemoglobin A1c (HbA1c), serum trigliserid-glukoz indeksi (TyG indeksi), SMBG ile ölçülen en yüksek ve en düşük kan şekeri düzeyleri farkı (SMBGfarkı) ve SMBGfarkı ile en yüksek SMBG düzeyinin oranı (SMBGoranı), uMCR ve uPCR değerleri, mikrovasküler komplikasyonları tahmin etmedeki tanısal güçleri ROC analiziyle değerlendirildi. Tanısal performansa sahip olanların kesim değerleri ve sensitivite ve spesifiteleri hesaplanmıştır. Bulgular: DM hastalarının %70'inin erkek olduğunu, %48,5'inde nöropati, %25,3'ünde retinopati ve %25,3'ünde nefropati olduğunu göstermiştir. Lipid metabolizması ve karaciğerle ilgili göstergeler normal aralıkta olmasına rağmen, hastalarda D vitamini eksikliği görülmüştür. ROC analizi, uMCR ve uPCR düzeylerinin bağımsız olarak nefropati ile ilişkili olduğunu (p<0.001), güçlü spesifisite ve orta düzeyde duyarlılık gösterdiğini ortaya koymuştur. SMBGfarkı hem retinopati hem de nöropati açısından istatistiksel olarak anlamlı tanısal performansa sahip (p=0.049, p=0.040), ancak hem spesifite hem de sensitivite düzeyleri düşüktür. Sonuçlar: DM'lu yaşlı hastalarda uMCR ve uPCR nefropatinin güçlü göstergeleridir. Bununla birlikte, diyabetle ilişkili diğer biyobelirteçler zayıf korelasyon göstermiştir; bu da diyabetik hastalarda yaşa bağlı sorunları ve araştırmaya duyulan ihtiyacı vurgulamaktadır.

Anahtar Kelimeler

• Tip 2 diyabet
• retinopati
• nöropati
• nefropati
• idrar mikroalbümin-kreatinin oranı
• protein-kreatinin oranı

Kaynakça

1. Wu Y, Xiong T, Tan X, and Chen L. Frailty and risk of microvascular complications in patients with type 2 diabetes: a population-based cohort study. BMC Med. 2022;20(1):473. DOI: 10.1186/s12916-022-02675-9.
2. Kaya UP and Caydam OD. Association between Social Support and Diabetes Burden among Elderly Patients with Diabetes: A Cross-Sectional Study from Turkey. Saudi J Med Med Sci. 2019;7(2):86-92. DOI: 10.4103/sjmms.sjmms_44_18.
3. Prabhu D, Rao A, Rajanna A, Kannan S, and Kumar S. Urinary Albumin to Creatinine Ratio to Predict Diabetic Retinopathy: The Eyes Have It! Cureus. 2022;14(3):e22902. DOI: 10.7759/cureus.22902.
4. Fagot-Campagna A, Bourdel-Marchasson I, and Simon D. Burden of diabetes in an aging population: prevalence, incidence, mortality, characteristics and quality of care. Diabetes Metab. 2005;31 Spec No 2:5S35-5S52. DOI: 10.1016/s1262-3636(05)73650-8.
5. Jiang S, Yu T, Di D, Wang Y, and Li W. Worldwide burden and trends of diabetes among people aged 70 years and older, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019. Diabetes Metab Res Rev. 2024;40(3):e3745. DOI: 10.1002/dmrr.3745.
6. American Diabetes A. 11. Microvascular Complications and Foot Care: Standards of Medical Care in Diabetes-2020. Diabetes Care. 2020;43(Suppl 1):S135-S51. DOI: 10.2337/dc20-S011.
7. Zhang H, Yang S, Wang H, et al. Assessing the diagnostic utility of urinary albumin-to-creatinine ratio as a potential biomarker for diabetic peripheral neuropathy in type 2 diabetes mellitus patients. Sci Rep. 2024;14(1):27198. DOI: 10.1038/s41598-024-78828-y.
8. Benitez-Aguirre PZ, Marcovecchio ML, Chiesa ST, et al. Urinary albumin/creatinine ratio tertiles predict risk of diabetic retinopathy progression: a natural history study from the Adolescent Cardio-Renal Intervention Trial (AdDIT) observational cohort. Diabetologia. 2022;65(5):872-78. DOI: 10.1007/s00125-022-05661-1.

9. Mujeeb S, Rodrigues GR, Nayak RR, Kamath AR, Kamath SJ, and Kamath G. Urine protein: Urine creatinine ratio correlation with diabetic retinopathy. Indian J Ophthalmol. 2021;69(11):3359-63. DOI: 10.4103/ijo.IJO_1269_21.
10. Stratton IM, Adler AI, Neil HA, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321(7258):405-12. DOI: 10.1136/bmj.321.7258.405.
11. Pozzilli P, Strollo R, and Bonora E. One size does not fit all glycemic targets for type 2 diabetes. J Diabetes Investig. 2014;5(2):134-41. DOI: 10.1111/jdi.12206.
12. Kim KS. Self-Monitoring of Blood Glucose in Patients with Insulin-Treated Type 2 Diabetes Mellitus. Diabetes Metab J. 2018;42(1):26-27. DOI: 10.4093/dmj.2018.42.1.26.
13. American Diabetes A. 12. Older Adults: Standards of Medical Care in Diabetes-2021. Diabetes Care. 2021;44(Suppl 1):S168-S79. DOI: 10.2337/dc21-S012.
14. World Health Organisation (WHO). Waist Circumference and Waist–Hip Ratio. Report of a WHO Expert Consultation. Access address: https://www.who.int/publications/i/item/9789241501491, Access date: 15.02.2025
15. DeLong ER, DeLong DM, and Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44(3):837-45.
16. Corriere M, Rooparinesingh N, and Kalyani RR. Epidemiology of diabetes and diabetes complications in the elderly: an emerging public health burden. Curr Diab Rep. 2013;13(6):805-13. DOI: 10.1007/s11892-013-0425-5.
17. Bansal D, Gudala K, Muthyala H, Esam HP, Nayakallu R, and Bhansali A. Prevalence and risk factors of development of peripheral diabetic neuropathy in type 2 diabetes mellitus in a tertiary care setting. J Diabetes Investig. 2014;5(6):714-21. DOI: 10.1111/jdi.12223.
18. Lind M, Pivodic A, Svensson AM, Olafsdottir AF, Wedel H, and Ludvigsson J. HbA(1c) level as a risk factor for retinopathy and nephropathy in children and adults with type 1 diabetes: Swedish population based cohort study. BMJ. 2019;366:l4894. DOI: 10.1136/bmj.l4894.
19. Arnold F, Kappes J, Rottmann FA, Westermann L, and Welte T. HbA1c-dependent projection of long-term renal outcomes. J Intern Med. 2024;295(2):206-15. DOI: 10.1111/joim.13736.
20. Fakı S, Tam AA, İnce N, et al. Relationship Between Triglyceride-Glucose Index and Microvascular Complications in Hospitalized Patients with Type 2 Diabetes Mellitus. Türkiye Diyabet ve Obezite Dergisi. 2024;8(1):13-18.
21. Tu Z, Du J, Ge X, et al. Triglyceride Glucose Index for the Detection of Diabetic Kidney Disease and Diabetic Peripheral Neuropathy in Hospitalized Patients with Type 2 Diabetes. Diabetes Ther. 2024;15(8):1799-810. DOI: 10.1007/s13300-024-01609-3.
22. Liu L, Xia R, Song X, et al. Association between the triglyceride-glucose index and diabetic nephropathy in patients with type 2 diabetes: A cross-sectional study. J Diabetes Investig. 2021;12(4):557-65. DOI: 10.1111/jdi.13371.
23. Srinivasan S, Singh P, Kulothungan V, Sharma T, and Raman R. Relationship between triglyceride glucose index, retinopathy and nephropathy in Type 2 diabetes. Endocrinol Diabetes Metab. 2021;4(1):e00151. DOI: 10.1002/edm2.151.
24. Shamshirgaran SM, Mamaghanian A, Aliasgarzadeh A, Aiminisani N, Iranparvar-Alamdari M, and Ataie J. Age differences in diabetes-related complications and glycemic control. BMC Endocr Disord. 2017;17(1):25. DOI: 10.1186/s12902-017-0175-5.
25. Yu S, Am Song S, Jun KR, and Lee JN. Performance evaluation of MEDITAPE UC-11A strip test in estimating the urine albumin-to-creatinine ratio and urine protein-to-creatinine ratio. Laboratory Medicine Online. 2020;10(1):52-57.
26. Fabre L and Rangel EB. Age-related markers and predictors of diabetic kidney disease progression in type 2 diabetes patients: a retrospective cohort study. Ther Adv Endocrinol Metab. 2024;15:20420188241242947. DOI: 10.1177/20420188241242947.
27. Hwang S, Lee K, Park J, et al. Prognostic significance of albuminuria in elderly of various ages with diabetes. Sci Rep. 2023;13(1):7079. DOI: 10.1038/s41598-023-32305-0.
28. Yang P and Yang B. Development and validation of predictive models for diabetic retinopathy using machine learning. PLoS One. 2025;20(2):e0318226. DOI: 10.1371/journal.pone.0318226.
29. Davis WA, Bruce DG, and Davis TM. Does self-monitoring of blood glucose improve outcome in type 2 diabetes? The Fremantle Diabetes Study. Diabetologia. 2007;50(3):510-5. DOI: 10.1007/s00125-006-0581-0.
30. Ang L, Jaiswal M, Martin C, and Pop-Busui R. Glucose control and diabetic neuropathy: lessons from recent large clinical trials. Curr Diab Rep. 2014;14(9):528. DOI: 10.1007/s11892-014-0528-7.
31. Gouveri E and Papanas N. The Emerging Role of Continuous Glucose Monitoring in the Management of Diabetic Peripheral Neuropathy: A Narrative Review. Diabetes Ther. 2022;13(5):931-52. DOI: 10.1007/s13300-022-01257-5.
32. Cosson E, Baz B, Gary F, et al. Poor Reliability and Poor Adherence to Self-Monitoring of Blood Glucose Are Common in Women With Gestational Diabetes Mellitus and May Be Associated With Poor Pregnancy Outcomes. Diabetes Care. 2017;40(9):1181-86. DOI: 10.2337/dc17-0369.