Abstract
Introduction: Diabetes mellitus is a common metabolic disorder that is sometimes responsible for kidney diseases, especially in the form of diabetic nephropathy. In this study, we tried to investigate the markers associated with kidney diseases within diabetic patients as compared to non-diabetic participants.
Methodology: In this study, among 237 participants, 81 patients were diabetic, whereas 156 were non-diabetic participants. The level and association of serum creatinine, blood urea nitrogen (BUN), and glomerular filtration rate (GFR) were investigated using the enzymatic method and CKD-EPI equation respectively.
Result: We found significantly higher creatinine and BUN levels and lower GFR in the diabetic group compared to the non-diabetic group. Besides, we determined a positive association between creatinine and BUN, and an inverse relationship between GFR and creatinine and BUN respectively which was highly scattered in the case as compared to the non-diabetic group. Further analysis of the participants with high creatinine levels only supported the main outcomes.
Conclusion: Our investigation of kidney markers suggests a significant association between diabetes and kidney complications. Leading a healthy lifestyle and maintaining blood sugar and pressure may help to slow down the progress of diabetic nephropathy for diabetic patients.
Keywords: diabetic, glomeruli, kidney, nephropathy, nitrogenous waste, renal
Introduction
Diabetes mellitus (DM) is a metabolic disorder, especially limiting carbohydrate metabolism, resulting in underusing glucose and producing hyperglycemia or blood sugar [1]. Research says the prevalence of DM will rise from 6.4% (approximately 285 million people) in 2010 to 7.7% by the end of 2030 with approximately 438 million diseased people. This percentage may increase up to 8% in the 21st century [2]. It is responsible for diabetic nephropathy and can cause renal complications which ultimately lead patients to mortality and morbidity [3].
Diabetic nephropathy is a type of kidney disease that usually occurs in diabetic patients suffering from diabetes for long periods or those whose diabetes is not under control [4]. As a result, gradually the filtering organelles inside the kidney get ruptured, and the macro protein molecules start to leak and are lost through urination [5]. To observe the stability of kidney function different tests are done and among them, creatinine, blood urea nitrogen (BUN), and glomerular filtration rate (GFR) are some of the well-recognized [6-8]. Creatinine is recognized as one of the uncharged small molecules (113 Da) and endogenous substances that is produced through the non-enzymatic transformation of phosphate and creatine molecules that remain within the serum until filtered by the glomerulus of the kidney and excreted through urination [9]. BUN, on the other hand, is a nitrogenous protein molecule regarded as metabolic waste. It is mainly produced by the liver after metabolism and filtered by the kidney [10]. Again, the GFR is a method regarded as the exogenous filtration marker [11]. Previously creatinine has been suggested as a crucial indicator of renal failure in kidney complications. However, an enhanced BUN level was regarded as an indicator of interrupted protein metabolism in renal diseases [12]. The GFR level on the other hand was considered as a critical measure for acute and chronic kidney diseases [13]. Although these markers are normally tested and observed in kidney patients, diabetic patients who have developed kidney and renal complications may check their kidney function through these tests.
In this study, we primarily tried to observe the level serum of creatinine, BUN, and GFR among diabetic patients with no diagnosed kidney diseases. Besides, we tried to compare serum creatinine and BUN levels between diabetic and non-diabetic participants, assess the GFR in both groups, and investigate the associations among creatinine, BUN, and GFR specifically in diabetic patients.
Materials and methods
Study approval and participants
The study setting for this observational study was set up in the Muzaffarabad Center, Pakistan. Ethical approval was received from the Abbas Institute of Medical Sciences, Muzaffarabad, AJK, Pakistan with approval number 5493. A total of 237 participants were included in this study including 81 as the diabetic group and 156 as the non-diabetic group. Informed consent was obtained from each participant before collecting the samples with a short questionnaire form.
Inclusion and exclusion criteria
As per the inclusion criteria, patients with diabetes were selected as the diabetic group. In contrast, participants who came for random check-ups with no diabetes or other certain diagnosed diseases or any symptoms were regarded as the non-diabetic group. The participants of the non-diabetic control group were confirmed to have no diabetes based on their oral glucose tolerance test (OGTT) and hemoglobin A1c (HbA1c) tests. Both the male and female participants were considered eligible for this study. No age restriction was maintained. Per the exclusion criteria, participants with other confirmed chronic diseases were excluded from the diabetic and non-diabetic groups. Again, participants with confirmed diabetes were excluded from the non-diabetic group.
Sample collection
The blood sample of the participants was collected using the venipuncture method in the early morning in fasting conditions. The samples were centrifuged after the collection and the serum was separated from the hematocrit. Serum samples were stored at -20°C for further tests.
Measuring diabetic parameters
We initially did the OGTT for all the patients to confirm and distinguish between diabetic and non-diabetic participants. We also measured the HbA1c parameter for each participant to confirm diabetes further.
Biochemical test
Creatinine and BUN were tested using the Abbott architect system using their specific kit. Creatinine was measured following the principle of kinetic test based on alkaline picrate [14]. On the other hand, BUN was measured following the enzymatic testing systems based on urease [15]. The final concentration measurement for the creatinine and BUN for both tests was analyzed through a spectrophotometer. According to the kit, the reference range for serum creatinine was <0.55 mg/dL (low) to >1.02 mg/dL (high) for females, and <0.73 mg/dL (low) to >1.18 mg/dL high for males. For BUN the range was <8 mg/dL (low) to >22 mg/dL (high), and between 8 and 22 mg/dL it was referred to as the normal range.
GFR measurement
The estimated GFR (EGFR) was measured for all the diabetic cases as well as non-diabetic participants. To calculate the value of the EGFR, the CKD-EPI creatinine equation was obtained [16]. The reference range for the GFR was <60 ml/min/1.73m2 as low and >60 ml/min/1.73m2 as normal.
Participants with a higher creatinine level
We further separated the participants of the diabetic and non-diabetic groups with higher creatinine levels. We tried to compare the markers between those groups to observe the differences and significance.
Statistical analysis
Statistical analyses were done to understand the correlation among creatinine, BUN, and GFR. The mean, SD, and one sample t-test to obtain the p-value and investigate the significance were determined using IBM SPSS Statistics for Windows, Version 16 (Released 2007; IBM Corp., Armonk, New York, United States). The mean differences of the levels between the two groups were analyzed with RevMan (version 5.4, Cochrane, London). Scatter dot plots were generated to visualize the relationship among these biomarkers using Microsoft Excel 365 (Microsoft Corporation, Redmond, USA). The associations between biomarkers were further correlated with Pearson’s correlation.
Results
Demographics of participants
The number of total study participants followed by the participant numbers based on gender (i.e. male and female) and percentages, as well as the mean ± standard deviation (SD), and median value of the age, age range, OGTT (fasting and after two hours), HbA1c, ethnicity, and duration of diabetes of participants were determined. The detailed demographics are elaborated in Table 1.
Table 1. Demographics of study participants.
n: number of participants; NA: not applicable; oral glucose tolerance test
| Participant description | Diabetic group | Non-diabetic group |
| Participants (n) | 81 | 156 |
| Female (n) | 43 | 65 |
| Male (n) | 38 | 91 |
| Female (%) | 53.09 | 58.33 |
| Male (%) | 46.91 | 41.67 |
| Age (mean ± SD) (in year) | 58.04 ± 15.69 | 48.86 ± 14.71 |
| Age (median) (in year) | 58.50 | 49 |
| Age range (in year) | 34-82 | 24-72 |
| OGTT (fasting) (mg/dL) | 111.05 ± 13.73 | 87.81 ± 12.96 |
| OGTT (after two hours) (mg/dL) | 185.79 ± 44.76 | 102.13 ± 60.74 |
| HbA1c (%) | 9.29 ± 7.45 | 5.27 ± 0.49 |
| Ethnicity | Asian (Pakistani) | Asian (Pakistani) |
| Duration of diabetes | ≥ 1 year | NA |
Comparison of biomarker levels
Comparing the levels of serum creatinine, we identified that the level was higher in diabetic cases (2.08 ± 2.26 mg/dL) as compared to non-diabetic control (0.95 ± 0.69 mg/dL) (Figure 1a). In the case of BUN, the level was also found higher in the diabetic group (27.05 ± 18.05 mg/dL) as compared to the non-diabetic control (14.98 ± 9.42 mg/dL) (Figure 1b). However, the opposite relationship was observed in the case of GFR where the level was higher in non-diabetic control (96.72 ± 23.77 ml/min/1.72m2) as compared to the diabetic case group (59.59 ± 34.16 ml/min/1.72m2) (Figure 1c). The mean differences of the levels of serum creatinine, BUN, and GFR were found to be 1.12 (95%CI: 0.62-1.62), 12.07 (95%CI: 7.82-16.32), and 37.13 (95%CI: 28.81-45.45) respectively. All the comparisons were determined to be highly significant (p<0.005) respectively (Figure 1).
Figure 1. Different levels (i.e. mean value) of serum creatinine (A), BUN (B), and GFR (C) in diabetic cases and non-diabetic control.
MD denotes the mean differences between the levels and 95%CI denotes the 95% confidence interval. The asterisk (*) symbol denotes significantly high (p<0.005).
Association of biomarkers
The association of serum creatinine and BUN, serum creatinine and EGFR, and BUN and GFR between diabetic cases and non-diabetic control was investigated using scatter dot plots (Figure 2). In the diabetic group, we observed a positive but scattered correlation between creatinine and BUN and an inverse correlation between creatinine and GFR. However, a negative correlation was also observed between BUN and GFR which was highly scattered (Figures 2A, 2C, 2E). In the non-diabetic control group, the correlation was much homogenized being less scattered and similar with slight variation for creatinine and BUN (Figure 2B), creatinine and GFR (Figure 2D), and BUN and GFR (Figure 2E).
Figure 2. Association between creatinine and BUN.
Plots resemble the association between creatinine and BUN (A), creatinine and GFR (C), and BUN and GFR (E) in the diabetic group and the association between creatinine and BUN (B), creatinine and GFR (D), and BUN and GFR (F) in the non-diabetic group respectively. Here, PC indicates Pearson’s correlation.
Separate analysis of participants with a risk of kidney dysfunction
We further categorized and analyzed the participants for both the diabetic and non-diabetic control groups that have higher creatinine levels as it is regarded as one of the most crucial biomarkers for possible kidney dysfunction. We determined that only 12.17% of the participants in the non-diabetic group had higher (>ref value) creatinine levels whereas approximately 58.02% of patients had higher creatinine levels in the diabetic group with a significantly high variation (p<0.005). Further analysis showed that despite high creatinine levels, the value was much lower in the non-diabetic group than in the diabetic group.
Evaluation of the BUN and GFR of both the groups with higher creatinine levels also demonstrated that the value of BUN was much lower in the non-diabetic group than in the diabetic group. The GFR on the other hand was higher in the non-diabetic group as compared to the diabetic group. All the differences were highly significant (p<0.005) (Table 2).
Table 2. Analysis of markers in participants that had enhanced creatinine levels (>ref value) in both diabetic and non-diabetic groups .
The values are expressed as mean ± standard deviation (SD), and all the comparisons were significantly different (p<0.005).
| Participants and markers | Diabetic group | Non-diabetic group | p-value |
| Participants with enhanced creatinine (n, %) | 47 (58.02%) | 19 (12.17%) | |
| Creatinine level (mg/dL) | 2.97 ± 2.62 | 1.98 ± 1.56 | <0.005 |
| BUN level (mg/dL) | 35.32 ± 19.51 | 27.78 ± 19.80 | <0.005 |
| GFR (ml/min/1.73m2) | 36.25 ± 20.94 | 56.58 ± 29.30 | <0.005 |
Discussion
Diabetic nephropathy commonly occurs in diabetic patients and more frequently in end-stage renal disease. According to statistics, approximately 30% of diabetic patients worldwide have diabetic nephropathy [17]. Besides, diabetic nephropathy has been a major portion with about one-third of the disability-adjusted life-years among all types of kidney diseases worldwide from 1997-2017. This has also been increasing yearly [18,19]. To prevent these complications, regular check-up is important for diabetes patients.
In this study, we determined the creatinine, BUN, and GFR levels in both diabetic cases and non-diabetic control. No participants in this study were previously diagnosed or confirmed to be kidney patients. However, we saw a significant variation in the level of all these markers between diabetic and non-diabetic participants, and the level was much higher than the reference range in diabetic cases (Figure 1). Previous studies also found higher creatinine levels in diabetic patients which supports our findings. Navale et al. claimed the creatinine value to be around 1.90 mg/dL which is close to our determined value (2.08 ± 2.26 mg/dL) [20]. Another study also found higher creatinine levels in patients with type 2 DM [21]. BUN was also found to be higher in diabetic patients with different values for ages <45 years (22.43 ± 5.00 mg/dL) and >45 years (26.73 ± 6.21 mg/dL) [22]. Another study also determined higher levels of BUN in both Type 1 (27.23 ± 7.39 mg/dL) and Type 2 (28.4 ± 3.78 mg/dL) DM [23]. This data regarding BUN further supports our findings.
According to a previous study, the GFR was also investigated to be <60, mL/min/1.73m2 in seven diabetes patients out of 45 patients which is low compared to the regular GFR value [24]. Another study found that more than 20% of their study participants with DM had lower GFR values (<60 mL/min/1.73m2) and more than 32% had low to moderate range of GFR (60-75 mL/min/1.73m2) [25]. This also supports our observations regarding the lower GFR in diabetic patients as compared to the non-diabetic control group.
All these findings imply that diabetes patients have a higher risk of deteriorated function of the kidney which may ultimately result in kidney damage. Besides, the positive scattered (i.e. positive Pearson’s correlation) and heterogeneous association between serum creatinine and BUN also implies the plausible combined effect of kidney deterioration in diabetic patients (Figure 2). However, the opposite (i.e. negative Pearson’s correlation) and scattered correlation between GFR and creatinine as well as BUN indicates the possible destruction of kidney function that may lead the patients towards diabetic nephropathy and chronic kidney diseases (Figure 2). However, normal levels and the non-scattered association for all these markers in non-diabetic patients indicate the normal function of the kidney. Usually, creatinine is a nitrogenous waste that is excreted through the help of the kidney. BUN is another potential nitrogenous end product similar to creatinine that is produced by amino acid and protein catabolism and excreted by kidney. However, when kidney function is disrupted the level of both creatinine and BUN is enhanced in the blood [26]. Besides, the GFR is usually the conversion rate of impure blood transporting nitrogenous waste materials to ultrafiltrate blood which is performed by the kidney. Therefore, when the kidney function is disrupted, the GFR gets lower [27]. These biological phenomena further support our investigations and associations to be accurate.
Although 12% of the participants in the non-diabetic group showed slightly higher creatinine levels, the level was still much lower than that of the diabetic group. Besides, further comparison of the BUN and GFR in these diabetic and non-diabetic groups with higher creatinine levels demonstrated better kidney function in the non-diabetic group than in the diabetic group (Table 2). The possible reason for the participants having slightly higher creatinine levels might be some kidney or renal complications other than diabetic nephropathy. Further studies need to be done to focus on these issues.
Strength of the study
This study appropriately investigated the association and variation among the creatinine, BUN, and GFR in both diabetic and non-diabetic groups. These findings would help physicians make better decisions for diabetic patients who are suffering for a long period and are at risk of developing diabetic nephropathy. This study also would enlighten physicians and clinical researchers regarding the early diagnosis, prognosis, and prevention of diabetic nephropathy and would be a food for thought for further research.
Limitations of the study
We could not confirm whether non-diabetic participants had any other diseases or were fully healthy. We could only confirm that they did not have diabetes. Again, we did not have any confirmed diabetic nephropathy group to compare our obtained data with them. Additionally, the sample was relatively small, and the number of participants, age, and sex did not match accurately between the two groups. Besides, the study participants were of a specific location, and therefore, this study lacks generalization of the outcome. Further study regarding age-sex-matched prospective case-control research can overcome these limitations.
Conclusions
This study found a negative association of kidney markers in diabetic patients as compared to non-diabetic controls. From this observation, it can be said that diabetic patients have a higher risk of kidney damage through diabetic nephropathy. Maintaining a balanced life with controlled blood sugar and hypertension can minimize the chances of diabetic nephropathy. Taking no or very small amount of sugar occasionally, walking and exercising daily, and eating fiber, drinking enough water, and regular check-ups as per the advice of a physician can help to control the blood sugar and diabetes and prevent the risk of diabetic nephropathy. However, further research is required to observe the level of other associated markers to predict the possibilities of diabetic nephropathy in diabetic patients.
Disclosures
Human subjects: Consent was obtained or waived by all participants in this study. Abbas Institute of Medical Sciences issued approval 5493.
Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.
Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following:
Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work.
Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work.
Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.
Author Contributions
Concept and design: Amna Akbar, Batool Butt, Shoukat Hussain, Mumtaz Ahmad Khan, Sarosh Khan Jadoon
Acquisition, analysis, or interpretation of data: Amna Akbar, Batool Butt, Zahira Bashir, Bushra Ghulam, Mumtaz Ahmad Khan, Sajid Rafique Abbasi
Critical review of the manuscript for important intellectual content: Amna Akbar, Batool Butt, Zahira Bashir, Bushra Ghulam, Mumtaz Ahmad Khan, Sarosh Khan Jadoon, Sajid Rafique Abbasi
Drafting of the manuscript: Batool Butt, Shoukat Hussain, Mumtaz Ahmad Khan
Supervision: Batool Butt, Shoukat Hussain, Mumtaz Ahmad Khan, Sajid Rafique Abbasi
References
- 1.Diabetes: a 21st century challenge. Zimmet PZ, Magliano DJ, Herman WH, Shaw JE. Lancet Diabetes Endocrinol. 2014;2:56–64. doi: 10.1016/S2213-8587(13)70112-8. [DOI] [PubMed] [Google Scholar]
- 2.Global estimates of the prevalence of diabetes for 2010 and 2030. Shaw JE, Sicree RA, Zimmet PZ. Diabetes Res Clin Pract. 2010;87:4–14. doi: 10.1016/j.diabres.2009.10.007. [DOI] [PubMed] [Google Scholar]
- 3.Chronic renal disease and risk of cardiovascular morbidity-mortality. Santoro A, Mandreoli M. Kidney Blood Press Res. 2014;39:142–146. doi: 10.1159/000355789. [DOI] [PubMed] [Google Scholar]
- 4.Prevalence of nephropathy among diabetic patients in North American region: a systematic review and meta-analysis. Zahra S, Saleem MK, Ejaz KF, et al. Medicine (Baltimore) 2024;103:0. doi: 10.1097/MD.0000000000039759. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Diabetic nephropathy: an overview. Sagoo MK, Gnudi L. Methods Mol Biol. 2020;2067:3–7. doi: 10.1007/978-1-4939-9841-8_1. [DOI] [PubMed] [Google Scholar]
- 6.Electrochemical creatinine (bio)sensors for point-of-care diagnosis of renal malfunction and chronic kidney disorders. Saddique Z, Faheem M, Habib A, UlHasan I, Mujahid A, Afzal A. Diagnostics (Basel) 2023;13:1737. doi: 10.3390/diagnostics13101737. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Effects of Shenkang decoction on creatinine and blood urea nitrogen in chronic renal failure hemodialysis patients: a randomized controlled trial. Cao W, Liu L, Peng J, Li Y, Tian J, Gong D. J Integr Complement Med. 2023;29:253–260. doi: 10.1089/jicm.2022.0587. [DOI] [PubMed] [Google Scholar]
- 8.A meta-analysis of GFR slope as a surrogate endpoint for kidney failure. Inker LA, Collier W, Greene T, et al. Nat Med. 2023;29:1867–1876. doi: 10.1038/s41591-023-02418-0. [DOI] [PubMed] [Google Scholar]
- 9.The good, the bad, and the serum creatinine: exploring the effect of muscle mass and nutrition. De Rosa S, Greco M, Rauseo M, Annetta MG. Blood Purif. 2023;52:775–785. doi: 10.1159/000533173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Association of blood urea nitrogen with cardiovascular diseases and all-cause mortality in USA adults: results from NHANES 1999-2006. Hong C, Zhu H, Zhou X, et al. Nutrients. 2023;15:461. doi: 10.3390/nu15020461. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Performance and pitfalls of the tools for measuring glomerular filtration rate to guide chronic kidney disease diagnosis and assessment. Gama RM, Griffiths K, Vincent RP, Peters AM, Bramham K. J Clin Pathol. 2023;76:442–449. doi: 10.1136/jcp-2023-208887. [DOI] [PubMed] [Google Scholar]
- 12.Blood Urea Nitrogen (BUN) levels in renal failure: Unraveling the complex interplay of protein metabolism and kidney health. Mahmood R, Batool M, Majeed N, Shoukat Z, Qureshi AM, Shoaib M. Professional Med J. 2024;31:364–370. [Google Scholar]
- 13.Uses of GFR and albuminuria level in acute and chronic kidney disease. Levey AS, Grams ME, Inker LA. N Engl J Med. 2022;386:2120–2128. doi: 10.1056/NEJMra2201153. [DOI] [PubMed] [Google Scholar]
- 14.Measurement of serum creatinine--current status and future goals. Peake M, Whiting M. https://pubmed.ncbi.nlm.nih.gov/17581641/ Clin Biochem Rev. 2006;27:173–184. [PMC free article] [PubMed] [Google Scholar]
- 15.The determination of urea, ammonia, and urease. Kaplan A. Methods Biochem Anal. 1969;17:311–324. doi: 10.1002/9780470110355.ch7. [DOI] [PubMed] [Google Scholar]
- 16.Estimating GFR using the CKD Epidemiology Collaboration (CKD-EPI) creatinine equation: more accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Levey AS, Stevens LA. http://10.1053/j.ajkd.2010.02.337. Am J Kidney Dis. 2010;55:622–627. doi: 10.1053/j.ajkd.2010.02.337. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Diabetic nephropathy: challenges in pathogenesis, diagnosis, and treatment. Samsu N. Biomed Res Int. 2021;2021:1497449. doi: 10.1155/2021/1497449. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2020;395:709–733. doi: 10.1016/S0140-6736(20)30045-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Diabetic nephropathy: an update on pathogenesis and drug development. A/L B Vasanth Rao VR, Tan SH, Candasamy M, Bhattamisra SK. Diabetes Metab Syndr. 2019;13:754–762. doi: 10.1016/j.dsx.2018.11.054. [DOI] [PubMed] [Google Scholar]
- 20.Effects of pre-existing metformin therapy on platelet count, serum creatinine, and hospitalization in COVID-19 patients with diabetes mellitus. Navale AM, Devangan V, Goswami A, Sahu V, Lavanya S, Patel D. AIMS Mol Sci. 2023;10:311–321. [Google Scholar]
- 21.Impact of albumin-to-creatinine ratio point-of-care testing on the diagnosis and management of diabetic kidney disease. Schultes B, Emmerich S, Kistler AD, Mecheri B, Schnell O, Rudofsky G. J Diabetes Sci Technol. 2023;17:428–438. doi: 10.1177/19322968211054520. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Study of blood urea nitrogen (BUN), serum creatinine in diabetic and non-diabetic patients in a tertiary care hospital. Bhatia K, Misra P, Singh A, Mukherjee B, Ambade VK. Int J Med Biomed Stud. 2019;3:180–186. [Google Scholar]
- 23.Correlation of blood urea and creatinine levels with thiamin levels in type 1 and type 2 diabetic patients. Anwar A, Faisal F, Elahi W, et al. Cureus. 2024;16:0. doi: 10.7759/cureus.57022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.The effects of empagliflozin on measured glomerular filtration rate and estimated extracellular and plasma volumes in patients with type 2 diabetes. Jürgens M, Schou M, Hasbak P, et al. https://doi.org/10.1111/dom.15183. Diabetes Obes Metab. 2023;25:2888–2896. doi: 10.1111/dom.15183. [DOI] [PubMed] [Google Scholar]
- 25.Association of estimated glomerular filtration rate with progression of albuminuria in individuals with type 2 diabetes. Hanai K, Mori T, Yamamoto Y, Yoshida N, Murata H, Babazono T. Diabetes Care. 2023;46:183–189. doi: 10.2337/dc22-1582. [DOI] [PubMed] [Google Scholar]
- 26.Assessment of blood urea nitrogen (BUN) and creatinine as biochemical markers in chronic kidney disease and end stage renal disease patients undergoing hemodialysis. Al Jameil N. https://saudijournals.com/media/articles/SJM_42_97-102_c.pdf Saudi J Med. 2019;4:97–102. [Google Scholar]
- 27.Association between glomerular filtration rate and β-thalassemia major: a systematic review and meta-analysis. Khandker SS, Jannat N, Sarkar D, et al. Thalassemia Reports. 2023;13:195–205. [Google Scholar]