Journal of Biomedical Sciences

Abstract

The study looked into the correlation between glycated haemoglobin A1c (HbA1c) and the risk of developing diabetic nephropathy among diabetic patients attending Ahmadu Bello University Teaching Hospital Zaria, Nigeria, and also determined the level of HbA1c where the risk of nephropathy becomes pronounced.One hundred and one (101) diabetic patients were used for the study comprising of both male and female patients. About 5mL of blood sample was collected from each of the subjects after about 10 hours of overnight fasting. Then 3mL of the sample was centrifuged and the serum analysed for serum creatinine and also fasting blood glucose (FBG). The Glomerular Filtration Rate (GFR) was then calculated from the serum creatinine value using the Cockroft-Gault equation.The remaining 2mL from the blood sample was transferred into EDTA bottles and analysed immediately for glycated haemoglobin (HbA1C).Thirty-seven (37) of the diabetic subjects had mean HbA1C level of 6.96% that correspond to mean FBG level of 91.37mg/dL. Initially no significant correlation was found between HbA1c and the GFR. But there was significant correlation between HbA1c and GFR among patients with HbA1c level ≥ 9% (R= -0.35). Patients with this level of HbA1c (≥ 9%) had equivalent FBG ≥ 136 mg/dL.he risk of developing renal complications among patients was only prominent at the level of 9% HbA1c and above, and monitoring of patients should be done accordingly in order to guard against overtreatment, hypoglycaemia and unnecessary expenses.

Keywords

Glycated haemoglobin (HbA1c); Nephropathy; Diabetes; Serum creatinine; GFR; Blood glucose

Introduction

Diabetes is by all odds a big health problem worldwide. The International Diabetes Federation (IDF) Atlas estimated that about 285 million people around the world had diabetes in the year 2010 [1] and close to ten million people now present with the case in Nigeria alone [2].

As Rahbar made the discovery of a diabetic haemoglobin component in people with diabetes in 1968 [3], before long, it was demonstrated that this component had chromatographic characteristics resembling those of HbA1c (glycated haemoglobin), a minor haemoglobin component [4]. Several clinical studies then showed a close relationship between HbA1c, and the mean plasma glucose few months before doing the HbA1c test [5, 6]. The UK Prospective Diabetes Study (UKPDS) and the Diabetes Control and Complications Trial (DCCT) eventually revealed the link between glycaemic control (as regards HbA1c) and the risk of developing (and aggravating of) chronic diabetic complications [7,8], thereby confirming that HbA1c can be a "gold standard" for assessing medium to long term glycaemic control in diabetic patients. The results from HbA1c testing can therefore be used to determine the course of future treatment for the patient in order to guard against hyperglycaemic-induced complications [9]. However, the level of 6.5% HbA1c (IFCC (International Federation of Clinical Chemistry) 48 mmol/mol) though specific for the diagnosis of diabetes in most studies, lacks sensitivity and may misdiagnose many diabetic cases. The accuracy of the test is complicated further by many factors which modify levels of HbA1c due to genetic factors like red cell life span, race, haemoglobinopathies; or environmental factors like iron deficiency; or interferences e.g. vitamin C; or biological variability [10]. Microvascular complications such as retinopathy, nephropathy and neuropathy occur in diabetes [11]. And largely due to these complications, globally, diabetes is said to be the fifth leading cause of death [12]. Prevention of diabetes and its complications, early detection of disease stages, and therapeutics that would act in the presence of hyperglycaemia to prevent, delay or reverse the complications are the major concerns. Biomarkers such as glycated haemoglobin, serum creatinine and others are studied for understanding the mechanisms of hyperglycaemiainduced metabolic abnormalities [13]. Diabetic nephropathy, a leading cause of kidney failure and one of the key complications in diabetic patients is defined by either microalbuminuria or by an increase in serum creatinine level, which is in turn used in the calculation of estimated GFR (eGFR) in diabetic patients [14]. While microalbuminuria is a very sensitive test in people with Type 1 diabetes, testing for microalbuminuria alone may miss many cases of diabetic kidney disease in those with Type 2 [15]. Therefore, it is very important to test the kidney function by measuring the serum creatinine level [16]. And using the serum concentration of creatinine in an equation that takes into account the person’s weight, age, sex, (and race), one can estimate the GFR to evaluate kidney function. The higher the blood creatinine level, the lower the GFR and the worse shape the kidneys are in [17]. Normal eGFR ranges from 90 to 120 ml/min/1.73m2 [17].

Methods

Study subjects

Volunteers comprised of 101 diabetic male and female subjects. The participants had been receiving treatment in the teaching hospital for at least a year. They were recruited over a time period of 12 months from the month of January 2018 through December 2018. The age range of subjects was 35 years and above.

Study site

Zaria, a major city in Kaduna State (North-western region of Nigeria) has a population of about 700,000 people [18]. The denizens of Zaria are of various Nigerian ethnicity and livelihood. The city houses Nigeria’s largest University, Ahmadu Bello University. Ahmadu Bello University Teaching Hospital (ABUTH) is a modern hospital and serves patients with myriad forms of ailments including diabetes.

Informed consent and ethics committee approval

The study was approved by the Committee on Ethics for Human Research of Ahmadu Bello University, Zaria with the Approval No: ABUCUHSR/2017/002. Informed consent was gotten from each of the participants.

Inclusion and exclusion criteria

Diabetic patients that have presented with the ailment for at least a year were selected for the study. Their type of diabetes was Type II and the age range of patients was 35 years and above. Subjects that had any condition that affect erythrocyte turn over; or had evidence of chronic medical conditions like hypertension, renal failure, liver disease and urinary tract infection were all excluded from this study. Also, patients with diabetes for less than a year were excluded. Inclusion and exclusion was done based on the information about subject's personal and health-history data filled in a questionnaire and by scrutinizing the patients’ medical record

Sample size

Where: n = Sample size, Z = Z statistic for a level of confidence (for the level of confidence of 95%, Z’s value is 1.96), P = Expected prevalence or proportion (expressed in proportion of 1 instead of percentage), d = Precision (expressed in proportion of 1 instead of percentage).

Choosing a prevalence of 6.7% [20] at 95% confidence interval, the expected prevalence P = 6.7% (or 0.067) and Precision = 5% (or 0.05), [21].

Substituting the values in the equation:

This indicates that the sample size should at least be 96 but 101 subjects were used for the study, with the attrition rate at 5%.

Sample collection and analysis

Information about personal data, lifestyle and medical history for each subject was obtained using questionnaire and matching hospital records. Their blood pressure was checked at the point of blood collection to ascertain absence of hypertension. Blood samples were collected from subjects after about 10 hours of fasting. Then 5mL of blood sample (each) was collected via venepuncture. About 3mL of the blood was transferred from syringe into plain bottles, and centrifuged at 4000 rpm for 10 minutes. The serum was kept in the freezer (at -180C) until analysis. The remaining 2ml was transferred into EDTA bottles to prevent clotting and analysed immediately for glycated haemoglobin (HbA1c).

The glycated haemoglobin (HbA1c) level in the blood samples was measured using the FinecareTM fluorescence immunoassay (FIA) meter and cartridges.

The levels of creatinine and glucose present in the serum samples were measured using the automated Erba® Mannheim XL-200 Full-Auto Chemistry Analyzer by Erba Diagnostics Mannheim, Germany. The creatinine clearance was calculated for each sample from its serum concentration of creatinine using the Cockroft-Gault equation [22] where creatinine clearance (C_CR) = GFR:

Statistical analysis

Results were presented as mean ± SD and data was analysed using the Descriptive Statistics while relationships between variables was determined using the Pearson’s correlation test. A linear regression analysis was also conducted to generate a regression equation. A p-value of < 0.05 was considered statistically significant. All analysis was done using SPSS version 24.

Results

Table 1 simply shows the mean levels of each of the parameters that were measured or determined.

Table 1. Mean values of measured parameters of the patients.

On comparing the interrelationship between the measured parameters, FBG and HbA1c showed a strong positive correlation with an R value of 0.84 (Table 2). The relationship was also significant at a P level of 0.01. Also the GFR and SCr showed a significant correlation (P<0.01) with an inverse correlation coefficient R of -0.49. However, the FBG and HbA1c though showed negative correlations with the GFR, it was not to a significant level.

Table 2. Exploring the relationship (correlation) between the parameters (HbA1c, FBG, GFR and SCr) for the diabetic subjects.

Although patients with HbA1c ≥ 9% had a strong negative correlation between their HbA1c and GFR, significant at a level of P< 0.05 (Table 3).

Table 3. Exploring the correlation between HbA1c and GFR of patients with HbA1c ≥ 9%.

The patients that had HbA1c ≥ 9% were selected and the mean level of each of the measured parameters was calculated (Table 4). Their mean HbA1c and FBG levels are expectedly higher than the collective mean HbA1c and FBG levels whereas for the mean GFR and SCr levels, they are about the same as the collective. Figure 1 is a graph depicting the inverse relationship between the HbA1c and GFR of patients with HbA1c greater than or equal to 9%. In (Figure 2), a graph of the relationship between HbA1C and FBG was plot and a line equation generated. Picking a point of 135 mg/dL FBG on the graph, the equivalent HbA1c is about 8.5%.

Table 4. Mean values of measured parameters of the patients with HbA1c ≥ 9%.

This is intriguingly about the same HbA1c level where correlation (negative) between HbA1c and GFR is observed. Table 5 shows varied hypothetical FBG values and their (expected) respective equivalent HbA1c values.

Table 5. Glucose values and equivalent glycated haemoglobin levels based on the regression equation: y = 0.031x + 4.29 gotten from the study.

Figure 1: Relationship (with line of best fit) between HbA1c and GFR in patients with HbA1c level ≥ 9%. The correlation was significant at a level of P < 0.05.

In Table 6, subjects that had HbA1C at 5.7% – the purported point of onset of pre-diabetes – or greater were selected and their FBG compared with their HbA1c. Those whose FBG is correspondingly high (at the prediabetic or diabetic level) are classified as “conforming” while those whose FBG is within the normal range are classified as “deviating”.

Table 6. Proportion of Diabetic Subjects with Deviating HbA1c Levels (5.7% and above) Not Conforming to their Corresponding FBG Levels.

Discussion

Diabetic nephropathy is said to affect up to 20 or 30 percent of patients with diabetes and it is a common cause of kidney failure [23]. In Nigeria, it is reported to be the third most common cause of chronic renal failure. Though diabetic nephropathy is said to present at its earliest stage with microalbuminuria, it is important to test for the estimated GFR especially in patients with type 2 diabetes. For instance, patients with type 2 diabetes in NHANES III (Third National Health and Nutrition Examination Survey), low GFR was present in 30% of patients in the absence of micro- or macro albuminuria and retinopathy [23]. Gross et al, 2005, [25] therefore recommended that GFR should be routinely estimated for a proper screening of diabetic nephropathy, as it is regarded as the best parameter for overall kidney function [26,27]. In this study, the GFR was first observed not to drop significantly with increasing HbA1c. Whereas the GFR, an index for determining kidney function is known to drop with increasing level of HbA1c, a glycaemic marker which increases progressively with increase in FBG and used to monitor glycaemic control among diabetic patients [28-30]. But as from 9% glycation of haemoglobin (9% HbA1c) onward, the GFR dropped proportionally and significantly as the HbA1c increased. This occurred because below the level of 9% haemoglobin glycation, there isn’t the expected correspondingly high FBG level among the patients which would actually compromise the renal function and cause the GFR to drop – HbA1c being just a marker of glycaemic level. Thus, it is only in the patients with HbA1c above 9% that depreciating kidney function with increasing HbA1c is seen. The mean FBG at this level is also seen to be correspondingly very high.

The cut-point (point of onset of diabetes and risk of complications) of HbA1c from the diagnostic point of view is still controversial [31,32] and there is need to investigate local equivalent levels for a given blood glucose range [9]. As seen from figure 2, the equivalent level of HbA1c for FBG of about 136 mg/dL is 8.5% suggesting the cut-point for the diagnosis of diabetes [33]. It is worthy of note that it is around the same level (⁓9%) that significant correlation between the rising HbA1c and the dropping GFR was observed among the patients. This conjointly points at that HbA1c level (of ⁓9%) as an important point where diagnosis of diabetes and prognosis of complications – especially nephropathy – can be made.

Figure 2: Relationship (with line of best fit) between HbA1c and FBG in the patients. The correlation was significant at a level of P < 0.01.

Though a significant downward trend of GFR against rising HbA1c was observed among patients with HbA1c ≥ 9%, their mean GFR seemed not to be lower than the collective mean GFR level. This is likely due to the effectiveness of treatment among this group of patients moving more of them towards the relatively higher GFR (as observed in the mean value) and thus, an improving kidney function. There is however the necessity of further studies to investigate the relationship and interdependence between local HbA1c levels and accompanying renal function status among diabetic patients using microalbuminuria and/or albumincreatinine ratio as an index or indices for determining kidney function.

The study shows that about 37% of diabetic subjects used had HbA1c levels that do not match their glucose level – they had higher HbA1c (at the supposed diabetic or prediabetic level) for their (normal) blood glucose range. This indicates that 37 of the patients were capable of being over-treated and indulge in unnecessary or inimical expenses.

Finally, this study has provided a gateway for the underlying physiologic factors responsible for such a relatively wide range in normal HbA1c level to be investigated in the nearest future.

Conclusion

Glycated haemoglobin level of 8.5% should be taken as the threshold for the diagnosis of diabetes and the point of likelihood for the development diabetic complications particularly nephropathy. Also, the treatment of diabetic patients should be targeted at points well below this level with effort to provide adequate care for them. In addition, taking 8.5% as the “point of worry” could help guard against overtreatment, treatmentinduced hypoglycaemia and unnecessary expenses.

Other Information

Data are available on request.

Funding

The study was privately funded.

Conflict of Interest

No conflict of interest declared.

Citation: Oladayo MI, Tanko V, Yusuf R, et al. (2022) Glycated Haemoglobin (Hba1 c) and the Assessment of Risk of Nephropathy in Diabetic Patients in Ahmadu Bello University Teaching Hospital Zaria, Nigeria. J Biomed Sci, Vol. 11 No. 9: 78