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Table of Contents
Year : 2022  |  Volume : 15  |  Issue : 2  |  Page : 71-77

Role of microalbuminuria, creatinine, glomerular filtration rate and body mass index in predicting early nephropathy in patients with sickle cell disease

1 Department of Clinical Chemistry, Faculty of Medical Laboratory Sciences, University of Gezira; Department of Clinical Chemistry, Faculty of Medical Laboratory Sciences, University of El Imam El Mahdi, Kosti, Sudan
2 Department of Medical Parasitology, Faculty of Medical Laboratory Sciences, University of Gezira, Kosti; Department of Parasitology, Blue Nile National Institute for Communicable Diseases, University of Gezira, Wad Madani, Sudan
3 Department of Pathology, College of Medicine, Karary University, Khartoum, Sudan
4 Department of Microbiology, Faculty of Medical Laboratory Sciences, University of El Imam El Mahdi, Kosti, Sudan

Date of Submission16-Sep-2021
Date of Decision07-Nov-2021
Date of Acceptance21-Nov-2021
Date of Web Publication04-Jul-2022

Correspondence Address:
Mubarak Elsaeed Mustafa Elkarsany
Department of Pathology, College of Medicine, Karary University, Khartoum
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/hmj.hmj_60_21

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Background: Notably, sickle cell disease (SCD) is a major risk for renal problems. Proteinuria is a feature of sickle cell nephropathy that can develop into end-stage renal disease. Objective: The main goal of this study was to assess the link between microalbuminuria, creatinine, glomerular filtration rate (GFR) and body mass index (BMI) with the predicting early nephropathy in sickle cell disease patients who were admitted to Kosti Teaching Hospital during the period from June to August 2018. Materials and Methods: A total of 156 SCD participants were enrolled in this study. Venous blood and fresh urine samples were collected from each participant using sterile containers. Serum creatinine and urine microalbuminuria were measured. Results: Out of 156 patients, 61.5% were underweight. Interestingly, a decline in creatinine level and GFR was observed in 21.1% and 64.7% of the SCD cases, respectively. Likewise, microalbuminuria was detected in 55.8% of participants. Notably, the duration of SCD (P < 0.05), creatinine level (P < 0.05), age (P < 0.05) and microalbuminuria (P < 0.05) was significantly positively correlated with BMI. SCD duration, GFR, microalbuminuria, weight and highest exhibited a significant positive correlation with creatinine. Furthermore, GFR has presented a positive correlation with weight and highest, P < 0.05. In addition, weight displayed a positive correlation (P < 0.000) with disease duration. Conclusion: Altogether, the study findings highlighted the link of BMI, creatinine, microalbuminuria and GFR with SCD, which is significant in the prediction and assessment of early nephropathy in SCD patients.

Keywords: Body mass index, creatinine, glomerular filtration rate, microalbuminuria, sickle cell disease

How to cite this article:
Ismail AM, Abakar AD, Elkarsany ME, Almugadam BS. Role of microalbuminuria, creatinine, glomerular filtration rate and body mass index in predicting early nephropathy in patients with sickle cell disease. Hamdan Med J 2022;15:71-7

How to cite this URL:
Ismail AM, Abakar AD, Elkarsany ME, Almugadam BS. Role of microalbuminuria, creatinine, glomerular filtration rate and body mass index in predicting early nephropathy in patients with sickle cell disease. Hamdan Med J [serial online] 2022 [cited 2022 Aug 8];15:71-7. Available from: http://www.hamdanjournal.org/text.asp?2022/15/2/71/349781

  Introduction Top

Sickle cell disease (SCD) is a non-infectious autosomal recessive illness. It is characterised by the existence of haemoglobin S which is abnormal haemoglobin.[1],[2] Typically, sickle cell disease begins at the 5th–6th months of age.[3] The lack of red blood cell (RBC) elasticity is significant in sickle cell disease development. Normal RBCs are quite elastic. This elasticity allows the cells to pass through capillaries. Low-O2 tension in sickle cell disease encourages RBCs sickling, and the recurrent episodes of sickling decrease the cell's elasticity and damage the cell membrane. This sickle cell fails to return to normal when O2 tension is restored. As a result, it is unable to deform when they move through narrow capillaries, which lead to ischaemia and vessel occlusion.[4] Existence of Hbs results in many consequences including the vaso-occlusive, haemolytic crises and organ damage.[1],[2] The acidotic, hypertonic and hypoxic state of the renal medulla improves destruction and vaso-occlusion of the vaso-recta. Sickle cell disease (SCD) infants may show hyposthenuria that manifests as enuresis or nocturia by the 1st year of his life.[5] In sickle cell disease, cholecystitis and cholelithiasis may also develop due to a high level of bilirubin and its precipitation through haemolytic crises.[6]

Kidney diseases in sickle cell anaemia (SCA) patients result from several conditions include glomerular and tubular disorders.[7] Notably, renal involvement is a common factor of early death in SCA and around 16%–18% of early mortality in SCA patients is linked to renal disorder.[1] It is believed that around 80% of patients with sickle cell disease are occurring in sub-Saharan Africa, which makes them at high risk for sickle cell nephropathy (SCN).[8]

A little is known about kidney disease in SCD. Identifying the early kidney involvement allows the early management and improving quality of life which will help us in the long-term management of sickle cell patients and avoid renal complications. Therefore, the current study aimed to assess the link of microalbuminuria, creatinine, glomerular filtration rate (GFR) and body mass index (BMI) levels with kidney involvement in sickle cell patients who were attended Kosti Teaching Hospital.

  Materials and Methods Top

Study design, area and duration

This a cross-sectional study conducted at Kosti Teaching Hospital that locates in Kosti city, White Nile State, Sudan. The study was carried out from January 2018 to December 2020.

Study population and data collection

All patients with sickle cell disease who were attended to Kosti Teaching Hospital during the study duration were included in this study.

Inclusion criteria

The targeted participants were patients with SCD (children, adolescents and adults) as diagnosed based on the clinical features, past medical history and laboratory examination.

Exclusion criteria

The main exclusion criteria include pregnancy, breastfeeding, alcohol addiction, acute febrile illnesses, and past history of chronic diseases (kidney disease, hypertension, cancer, diabetes, autoimmune or immunodeficiency disease). Those with history of renal surgery or transplantation were excluded. Participants with a documented disease that can cause proteinuria dependently or urinary tract infection as based on the presence of nitrites and/or leucocyte esterase were excluded. Additionally, those unable to provide urine or blood sample were also excluded.

Data were collected by direct interview and questionnaire. For each participant, BMI was calculated by the following formula:

BMI = weight/high2.

Sample size

Out of the study duration, 156 SCD patients were enrolled.

Sample collection and laboratory analysis

The early morning urine specimen was collected from every contributor. Next, screening for macroalbuminuria was performed using urinalysis reagent strips (ACON, USA). Each urine sample was examined for urinary albumin excretion level using the immunoturbidimetric method (Biosystems, Barcelona, Spain). Briefly, 10 ul of urine sample was added to 1ml of working reagent in a test tube and incubated for 5 min. Then, the concentration of microalbuminuria was measured at 540-nm wavelength using Mindray BA88A semi-automated biochemistry analyser.

A venous blood sample was also collected from every individual in a lithium heparin container and immediately centrifuged at 3000 rpm for 5 min to obtain plasma, which tested for creatinine level using Biosystems kit (Biosystems, Barcelona, Spain) and Mindray BA88A semi-automated biochemistry analyser. The test was done by endpoint method, and the absorbance of both test and standard was eared at 500-nm wavelength. First, the absorbance was measured after 30 s from addition of sample then after 90 s. The absorbance of either test or standard equals the value of the absorbance after 90 s minus that after 30 s. The detection and linearity limits of the kit were 0.03 mg/dl and 20 mg/dl, respectively.

Creatinine level was calculated as follows:

Creatinine level = absorbance of test/absorbance of standard × concentration of standard (2 mg/dl).

Statistical analysis

The study data were analysed using the GraphPad Prism version 7 software. Pearson and Spearman correlations were used to evaluate the link between the study variables. R < 0.0 and R > 0.0 were considered negative and positive correlations, respectively. All P < 0.05 were reported as significant.

  Results Top

[Figure 1]a, [Figure 1]b, [Figure 1]c shows the rate of abnormal study findings. Out of 156 patients, 96 (61.5%) were underweight and only 2 (1.3%) cases were obese [Figure 1]a. Interestingly, a reduction in creatinine level and GFR was observed in 33 (21.1%) and 101 (64.7%) of the SCD cases, respectively [Figure 1]b. In addition, 69 (44.2%), 107 (68.6%) and 50 (32.1%) of SCD patients displayed no microalbuminuria, normal creatinine level and normal GFR level, respectively [Figure 1]b and [Figure 1]c. Microalbuminuria was detected in 87 (55.8%) of participants [Figure 1]c. The higher creatinine and GFR levels [Figure 1]b were observed only in 16 (10.3%) and 5 (3.2%) of patients, respectively.
Figure 1: (a c) Rate of abnormal study findings. (a) Body Mass Index, (b) Creatinine + Glomerular Filtration Rate, (c) Microalbuminuria

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To evaluate the relationship between the study variables, Pearson and Spearman correlation analyses were performed. [Figure 2]a, [Figure 2]b, [Figure 2]c, [Figure 2]d, [Figure 3]a, [Figure 3]b, [Figure 3]c, [Figure 3]d, [Figure 3]f, [Figure 4]a, [Figure 4]b, [Figure 4]c, [Figure 4]d, [Figure 4]e, [Figure 4]f, [Figure 4]g, [Figure 4]h, [Figure 4]i and [Figure 5]a, [Figure 5]b, [Figure 5]c show the findings of correlation analysis. Notably, all of the duration of SCD [Figure 2]d, microalbuminuria [Figure 3]a, creatinine level [Figure 3]b and age [Figure 4]b were significantly positively correlated with BMI.
Figure 2: Correlation of sickle cell disease duration with body mass index (a), Microalbuminuria (b), Creatinine (c) and Glomerular filtration rate (d)

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Figure 3: Correlation analysis. (a) Body mass index versus microalbuminuria, (b) Body mass index versus creatinine, (c) Body mass index versus glomerular filtration rate, (d) Glomerular filtration rate versus microalbuminuria, (e) Glomerular filtration rate versus creatinine and (f) Microalbuminuria versus creatinine.

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Figure 4: Correlation of age and weight with study variables. Link of patients age and weight with disease duration (a), Body mass index (b), Microalbuminuria (c), Creatinine (d) and glomerular filtration rate (e). Link of patients weight with disease duration (f), Microalbuminuria (g), Creatinine (h) and Glomerular filtration rate (i)

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Figure 5: Link of highest with microalbuminuria (a), creatinine (b) and GFR (c). GFR: glomerular filtration rate

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Furthermore, all of SCD duration [Figure 2]c, microalbuminuria [Figure 3]f, age [Figure 4]d, weight [Figure 4]h and highest [Figure 5]b exhibited a positive correlation with creatinine. In addition, GFR has presented a positive correlation with weight [Figure 4]i and highest [Figure 5]c. On the other hand, weight was revealed a positive correlation (P < 0.000) with disease duration [Figure 4f].

  Discussion Top

SCD is a worldwide health problem.[9] Over 4 million people were affected by sickle cell disease, and about 43 million suffered from sickle cell trait in 2015.[10],[11] Around 90% of patients survive up to age 20 and 50% live beyond age 50.[9] According to a previous study that was performed in Jamaica, the mean survival age was 53 years old for men with SCA and 58 years old for women with homozygous SCA.[12] However, the specific life expectancy varies in African countries.[13] Notably, SCN begins with glomerular illness, with significant proteinuria, then progresses gradually into chronic kidney failure.[14],[15],[16] The mechanism of SCN pathogenesis includes ischaemia, chronic hypoxia, oxidative stress and low pH of the renal medulla. APOL1 had also been stated as a factor affecting the progress of proteinuria.[14],[17],[18],[19],[20] Multiple mechanisms underlie kidney injury in chronic sickling: first, a low O2 tension in the arterial side of renal microvasculature and second, the low pH and hypertonicity of the renal medulla encourage the creation of the haemoglobin polymers in RBCs along with the deformation of the cells, which led to an upsurge in functional venous engorgement, blood viscosity and interstitial oedema. It also predisposes renal microcirculation to infarction and ischaemia. On the other hand, the obliteration of the medullary vasculature leads to interstitial fibrosis and segmental scarring. In sickle disease, haematuria can be developing due to the dilated vessels as a result of scarring or rupture of the vessels from early venous engorgement. Renal cortical blood flow and GFR are raised possibly due to the secretion of prostaglandins.[21] In the medulla, the collateral vessels and their abnormal orientation affect the mechanism of countercurrent exchange and lead to a permanent lack of medullary tonicity with time. Prior studies had been stated that renal problems happen in 5%–18% of sickle cell children and adolescents. They also found that over 90% of deaths in young adults occur as a result of kidney disease-related complications.[14],[15],[22] The current study attempts to assess the role of microalbuminuria, creatinine, GFR and BMI in predicting early nephropathy in sickle cell disease patients who attended Kosti Teaching Hospital. Sociodemographic analysis of studied participants revealed that 61.5% of the study cases were underweight, which is in line with the Odetunde OI et al. study.[23] Notably, the duration of SCD, creatinine, microalbuminuria and age of patients were significantly positively correlated with BMI. In line with this study, Imuetinyan BAI et al.'s study found that microalbuminuria is significantly associated with weight.[24] Based on univariate analysis, Aloni et al. study[25] also found a non-significantly association between BMI and microalbuminuria. In normal conditions, albumin excretion ranged from 5 to 10 mg per day, and urine albumin-to-creatinine ratio ranged from 0 to 29 mg. Microalbuminuria is defined as an abnormal increase in albumin excretion rate within the specific range of 30–299 mg of albumin/g of creatinine.[26],[27] Interestingly, 64.7% of the study participants were shown a decline in GFR, which is in the same line with many studies' findings.[1],[25] Dissimilar to our study, Brewin et al. study found that the prevalence of hyperfiltration was 98%.[28] In this study, microalbuminuria was detected in 55.8% of cases. Microalbuminuria is an early feature of SCN and it is a pre-clinical sign of kidney damage.[29] Previously, several studies[19],[24],[25],[29],[30],[31],[32],[33],[34],[35],[36] were documented microalbuminuria in sickle cell disease. Analogs to many studies,[1],[24],[25],[33],[36] microalbuminuria was positively correlated with age as based on Spearman correlation. Comparable to our study, Asnani et al.[35] and Brewin et al.'s[28] studies also showed an increase in ACR with age. In this study, microalbuminuria was positively correlated with GFR, which is analogous to Ocheke et al.[29] and Aloni et al.'s[25] studies. Antagonistic to our findings, Eke et al. study[33] reported a negative correlation between microalbuminuria and GFR, but in the same line with our findings, they found a positive correlation between microalbuminuria and serum creatinine. Formerly, Asnani and Reid study[35] found a significant negative between GFR and ACR, which is different from our findings. Altogether, these findings underlined the link of microalbuminuria, serum creatinine and GFR with sickle cell disease and showed the requirement for more deep studies. The dissimilarity between the studies may result from divergence in the study population, sample size, duration of illness, age of participants and variation in many other factors between studies. As indicated previously, GFR is fundamental in the investigation of early kidney disease, which may appear as hyperfiltration or rapid GFR decline.[36] In our study, the positive correlation of creatinine and microalbuminuria with the duration of SCD indicates the progress of early kidney disease with time. Thus, the evaluation of these parameters is critical in the management of SCD patients. The limitations of the present research include the small sample size due to short duration period of the study. The shortage of highly sensitive diagnostic techniques is also a major limitation of the study, which is significant to get more accurate data. The lack of tests about cysteine C and myoglobin level may also affect the outcome of the study.

  Conclusion Top

Altogether, the study findings highlighted the link of BMI, creatinine, microalbuminuria and GFR with SCD, which is significant in the prediction and assessment of early nephropathy in SCD patients. Thus, regular measurement of these parameters should be done in the management of SCD patients.

Ethical clearance

This article was part of the PhD thesis whose ethical approval was provided by the ethics committee of the Graduate College_Gezira University Sudan.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patients have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

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Conflicts of interest

There are no conflicts of interest.

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