Evaluation of Serum Urea and Creatinine as Predictive Biomarkers of Renal Dysfunction in Diabetes Mellitus

Authors

  • Zeeshan Abbas DMLT, Faculty of Allied Health Sciences, Superior University Lahore, Pakistan
  • Hifsa Mobeen DMLT-FAHS, Superior University Lahore, Pakistan / Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore, Pakistan
  • Muhammad Dawood Khan DMLT, Faculty of Allied Health Sciences, Superior University Lahore, Pakistan
  • Loviza DMLT, Faculty of Allied Health Sciences, Superior University Lahore, Pakistan
  • Muhammad Sufyan DMLT, Faculty of Allied Health Sciences, Superior University Lahore, Pakistan
  • Muhammad Ansar DMLT, Faculty of Allied Health Sciences, Superior University Lahore, Pakistan
  • Asma Fatima Institute of Molecular Biology and Biotechnology (IMBB), The University of Lahore, Pakistan

DOI:

https://doi.org/10.70749/ijbr.v4iS1.3121

Keywords:

Serum urea, Serum creatinine, Renal function, eGFR, kidney disease.

Abstract

Diabetes mellitus is a persistent metabolism disease, which may have severe complications, especially the damaged functioning of the kidney. It is critical to keep renal biomarkers monitored to timely identify kidney impairment. The study was conducted to examine the value of serum urea and creatinine as early biochemicals markers of diabetes linked to renal stress. The cross-sectional study was a comparative study that involved a sample of 139 participants, who were carefully selected using non-probability convenience sampling. Blood tests, serum urea and creatinine were done for both groups. A t-test was used to estimate statistical significance by the use of an independent sample. The serum urea and creatinine were significantly higher among diabetic patients, and eGFR levels were reduced relative to non-diabetic patients, which implied the poor renal functioning (p < 0.001. Kidney functionality is greatly affected in diabetes. Early prevention and detection of renal complications may be performed with the help of regular observation of serum urea and creatinine.

Downloads

Download data is not yet available.

References

1. Jardine MJ, Ninomiya T, Perkovic V, et al. Aspirin is beneficial in hypertensive patients with chronic kidney disease: a post-hoc subgroup analysis of a randomized controlled trial. J Am Coll Cardiol. 2010; 56:956–965.

https://doi.org/10.1016/j.jacc.2010.02.068

2. Levine GN, Bates ER, Bittl JA, et al. 2016 ACC/AHA guideline focused update on duration of dual antiplatelet therapy in patients with coronary artery disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2016; 68:1082–1115.

https://doi.org/10.1161/cir.0000000000000453

3. Bielka W, Przezak A, Molęda P, Pius-Sadowska E, Machaliński B. Double diabetes—when type 1 diabetes meets type 2 diabetes: definition, pathogenesis and recognition. Cardiovascular diabetology. 2024 Feb 10;23(1):62.

https://doi.org/10.1186/s12933-024-02145-x

4. Tong LL, Adler SG. Diabetic kidney disease treatment: new perspectives. Kidney research and clinical practice. 2022 Sep 30;41(Suppl 2): S63.

https://doi.org/10.23876/j.krcp.21.288

5. Ramachandran A. Know the signs and symptoms of diabetes. Indian Journal of Medical Research. 2014 Nov 1;140(5):579-81.

6. Ke C, Narayan KMV, Chan JCN, Jha P, Shah BR. Pathophysiology, phenotypes and management of type 2 diabetes mellitus in Indian and Chinese populations. Nat Rev Endocrinol. 2022; 18:413–32

https://doi.org/10.1038/s41574-022-00669-4

7. Pierre D, Jonas B, Emmanuelle V-P, et al. Diabetic status and the performances of creatinine- and cystatin C-based eGFR equations. Nephrol Dial Transplant. 2024.

https://doi.org/10.1093/ndt/gfae161

8. Guanghong J, Guido L, Brian PB, et al. The mineralocorticoid receptors in diabetic kidney disease. Am J Physiol Renal Physiol. 2024.

https://doi.org/10.1152/ajprenal.00135.2024

9. Chukwuka E, Minichimso JO, Kemeasoudei DJF, et al. Comprehensive advancements in the prevention and treatment of diabetic nephropathy: a narrative review. Medicine. 2023;102(40).

https://doi.org/10.1097/md.0000000000035397

10. Raja DS, Kumarganesh S, Sagayam KM, Dang H. Diabetic retinopathy detection and grading system using deep learning approach. Digital Health. 2026 Jan; 12:20552076251410982.

https://doi.org/10.1177/20552076251410982

11. Chowdhury E. Risk Prediction of Cardiovascular Disease for Diabetic Patients with Machine Learning and Deep Learning Techniques. arXiv preprint arXiv:2511.04971. 2025 Nov 7.

12. Khalid S, Bashir S, Mehboob R, Waseem H, Shahid I, Alzahrani AR, Malik U, Shalabi H, Bima AI, Maidin SS, Arif RH. Comparison of Diabetic Nephropathy Markers in Diabetic Patients with Insomnia Before and After Potassium and Magnesium Supplementation: A Randomized Controlled Trial. Health Science Reports. 2026 Jan;9(1): e71738.

https://doi.org/10.1002/hsr2.71738

13. Ali S, Muqadas K, Ramzan I, Junaid M, Khan V, Arshad H, Nazar MS. Gender and Family Medical History as Determinants of Type-2 Diabetes Mellitus Complications: A Cross-Sectional Assessment from Haripur, Pakistan: Gender and Family Medical History as Determinants of Type-2 Diabetes Mellitus Complications. Pakistan BioMedical Journal. 2026 Feb 28:27-33.

https://doi.org/10.54393/pbmj.v9i2.1348

14. Moeez S, Riaz SK, Qaiser TA, Sarfraz J, Naseer A, Haque S. Metformin-mediated modulation of epigenetic regulators in type 2 diabetes: A study on differential expression of DNMT1, TET1, OGG1, and AID genes. Naunyn-Schmiedeberg's Archives of Pharmacology. 2026 Feb;399(3):4099-115.

https://doi.org/10.1007/s00210-025-04700-z

Downloads

Published

2026-05-08

How to Cite

Abbas, Z., Mobeen, H., Khan, M. D., Loviza, Muhammad Sufyan, Muhammad Ansar, & Fatima, A. (2026). Evaluation of Serum Urea and Creatinine as Predictive Biomarkers of Renal Dysfunction in Diabetes Mellitus. Indus Journal of Bioscience Research, 4(S1), 21-24. https://doi.org/10.70749/ijbr.v4iS1.3121