DN has been a significant concern and a complication of diabetes mellitus (DM). The number of people with DM has doubled during the past 20 years. [1] By 2045, it is projected that 628 million individuals worldwide will be affected by this disease, while the currently estimated cases of DM stand at approximately 425 million.1 According to statistics, 179 million people can have DM but remain undiagnosed for various reasons. Due to ageing demographics, low levels of physical exercise, and urbanization, the number of people with T2DM has been expanding. [2]

DM is a widespread ailment that tremendously impacts patients by elevating the risks of falls, causing discomfort, and decreasing the quality of life. DM is a nerve injury that starts in the longest nerves, which are supplied throughout the foot and then advance anteriorly. High levels of blood glucose damage the peripheral nerves resulting in disabilities. Symptoms noted in patients with DM are Numbness in limbs, tingling sensation, weakness in the body, and experiencing sharp pain and sensitivity. [3] Retinopathy, nephropathy, and neuropathy are long-term microvascular consequences of DM. DN typically begins affecting the legs and feet first and gradually progresses to the arms and hand region. According to the American Diabetes Association, approximately 50% of the population living with DM is affected by DN; therefore, the primary intervention of screening individuals to prevent DM is crucial. [4]

However, regarding the scientific knowledge that hemoglobin is associated with kidney diseases and adverse diabetic effects, a high probability of renal dysfunction is predicted in DN due to damage to the nerves in the kidney region. Hemoglobin levels are high, around 18.8 g/dl in people with type 1 diabetes (T1DM) and overt nephropathy, compared with the general population suffering from renal disease. [5]

Hematological parameters such as white blood count (WBC), Mean Platelet volume (MPV), plateletcrit (PCT), PLT, NLR, lymphocyte to monocyte ratio (LMR), and others are indicators of endothelial dysfunction and inflammation due to the result of their continued renewal over a lengthy duration of time. Evaluation of inflammatory parameters and potential risk markers can be done using these conventional and straightforward measures. The hematological parameters study aims to find the association between HbA1c and hematology markers and determine whether there is a significant correlation between the microvascular complications of DM and these parameters. [5]

Numerous studies have linked an increased prevalence of neuropathy to the length of DM and HbA1c levels. HbA1c is a form of hemoglobin molecule to which a sugar molecule is chemically attached. The HbA1c test estimates the average blood sugar levels present in the body. When the percentage of glucose in the blood increases, the glucose bond with hemoglobin molecules in a concentration-dependent manner. This mechanism increases the HbA1c levels in the bloodstream, which are then detected in the estimation for DM. Its concentration depends upon the plasma glucose concentration and the length of hyperglycemia. It measures how substantially DM control has progressed over twelve weeks. The HbA1c levels are directly proportional to blood glucose levels. It is the most common test for determining and controlling the blood sugars causing DM. DN often affects the legs and feet. According to Hicks et al5 the mean Red Blood Cell count of a diabetic patient with HbA1c<7 is less than a person who does not have DM. A decrease was noted in mean hemoglobin, red blood cell (RBC), hematocrit, and MCV of diabetic patients with HbA1c>7 as compared to those without DM with HbA1c> as compared to hbA1c<7.5. [6]

These hematological parameters shift in paradigm plays an essential and crucial role in microvascular and microvascular complications of DM. It is, therefore, an utmost important task to evaluate and investigate each hematological parameter, including WBC, RBC, HB, MCH, MCHC, hematocrit, RBC distribution width, and MPV. In this retrospective study, we further discuss the association between glycated hemoglobin and other hematological parameters to assess the onset of DN. [7]

The cross-sectional analytical study was carried out at the Department of Hematology, UNS ASMC, Jaunpur and informed consent, patients were selected by consecutive sampling technique.

Inclusion Criteria: Patients of either gender, aged 40 to 80 years with type 2 Diabetes Mellitus were included in the study.

Exclusion Criteria: Seriously ill patients requiring critical care, patients having active bleeding, pregnancy, evidence of acute renal or liver impairment and the patients who had any recent history of cardiac dysfunctions and any hemoglobinopathy were excluded.

In the study out of which 30 were non diabetic healthy subjects which were taken as group1 and 60 were known diabetic patients which were divided into two groups with HbA1c <7(30 subjects) as group 2 and HbA1c >7(30 subjects) as group 3.

Upon admission, all patients were assessed for diabetes related complications. People with diabetes were defined according to the World Health Organization (WHO) classification of Diabetes and Glycosylated haemoglobin (HBA1c) as ˃7 %.11 Diabetic retinopathy was defined with the presence of at least two micro-aneurysms and/or retinal haemorrhages. Diabetic nephropathy was defined with microalbuminuria (30-300mg/24hrs), urinary excretion or macroalbuminuria. Diabetic neuropathy was defined as clinical symptoms of hyperesthesia/paraesthesia/motor weakness or polyradiculopathy.12,13 Cardiovascular complications were considered present if the patient had an ischemic history or electrocardiographic signal ischemia, such as T waves spiking before ST elevation perturbations. CVD was diagnosed based on the presence of either transient ischemic attack or stroke. The peripheral arterial disease was diagnosed with a plaque on the carotid or lower limb arteries wall using ultrasonography. Diabetic Retinopathy, Diabetic Neuropathy and Diabetic peripheral Neuropathy were considered diabetic microvascular complications. In contrast, cardiovascular heart disease related to diabetes, Cerebrovascular Disease and Peripheral Artery diseases were considered diabetic macrovascular complications.

The demographic details were collected. Height, weight and Body Mass Index (BMI); weight(kg)/height(m2) were measured. Detailed clinical history was obtained. A history of comorbid conditions was documented. Duration of diabetes and history of diabetes-related complications were taken. Patients were asked for dietary preferences, gastrointestinal disorders (i.e., acid peptic disease, gastrooesophagal reflux disease, altered bowel habits) and history of blood loss. Treatment history and list of medications used by patients were recorded. Patients were also asked about using Non-Steroidal AntiInflammatory Drugs (NSAIDs), corti-costeroids, antiplatelets, anticoagulants, proton pump inhibitors and antacids. Patients were then investigated for the presence of anaemia. Complete blood counts (CBC) were obtained, including red cell indices, white cell indices, platelet, Total lymphocyte count (TLC), HbA1c, and Plasma Glucose Fasting were recorded. Anaemia was diagnosed based on WHO criteria. Those with iron deficiency were further investigated for the source of blood loss. Urea and creatinine levels were obtained, and a urine routine examination was performed for albuminuria. ECG was done for all patients. Anaemia was defined as Hemoglobin ˂13 g/dl in males and <12g/dL in females, as recommended by the WHO. The cut-off values for TLC were 4-11x103/mm, platelets were 1.5-4.5 lakhs and Mean Platelet Volume as 7-11.5 femtoliters.

Statistical Analysis

Data were analyzed using version 21 of the Statistical Package for Social Sciences (SPSS). Means were estimated and presented as Mean±SD. Analysis of variance technique was applied to see the significance level (α=0.05). Means were compared through the Least Significance Difference Test. Logistic regression analysis was applied to examine the association of complications with variables.

In this study, a total of 90 subjects were included out of which 31 were non-diabetic healthy subjects (group 1) with their age ranging from 40-80 years and 59 were type-2 diabetic subjects with their age ranging from 40-80 years. The mean age of non-diabetics was 48.4 years and mean age of diabetics was 54.1 years. The diabetic subjects were divided into 2 groups, one with HbA1c<7(group 2) and other with HbA1c>7(group 3). The majority of the subjects among all the groups were females. In this study it was observed that the mean RBC count of diabetics with HbA1c<7 was less when compared to non-diabetic healthy individuals. There was a significant decrease in mean RBC count, Hb, HCT of diabetics with HbA1c>7 when compared to non-diabetic individuals. There was significant decrease in mean MCV and MCH of diabetics with HbA1c >7 when compared to diabetics with HbA1c <7.

Overall, in diabetics the mean RBC, HB, PCV, MCV and MCH values were lower when compared to non-diabetic individuals.

Table 1: Patient Demographics.

Tables 2: Comparison of RBC indices in Group 1 (Non Diabetics) with Group 2 (Diabetics with HbA1c<7).

Table 3: Comparison of RBC indices in Group 1( Non Diabetics) with Group 3( Diabetics with HbA1c>7).

Table 4: Comparison of RBC indices in Group 2(Diabetics with HbA1c<7) with Group 3  (Diabetics with HbA1c>7).

Diabetes Mellitus is a complex metabolic multisystemic disorder with steadily increasing prevalence. Persistent hyperglycemia results in non-enzymatic glycation of various proteins in blood such as hemoglobin, prothrombin and fibrinogen, which in turn changes viscosity, flow, red cell deformability, surface charge, erythrocyte aggregation and other physiochemical properties of blood. Also, the pro inflammatory milieu associated with diabetes brings about various changes in hematological parameters. The resultant RBC, WBC and platelet dysfunction is reflected in the hemogram.

In our study 90 subjects were included in each of the two groups. Mean age of diabetics was 48.7 years and of non-diabetics 46.9 years, which was lower as compared to studies by Ravi Patel and Harish Kumar.

Hemoglobin along with RBC parameters like RBC count, PCV and MCHC were significantly lower in diabetic group, whereas MCV and RDW CV showed significant increase. Diabetes with its associated hyperglycemia induced changes in the body’s metabolic and physiochemical composition has been shown to be independent risk factor for Anaemia in previous studies. [11] The etiopathogenesis of anaemia is complex and multifactorial in diabetes. The association of renal failure and development of secondary anaemia through erythropoietin pathway is well known, however, it has been observed that diabetics develop anaemia much earlier in the course of disease and also the severity of anemia when linked to stage of renal impairment was much more compared to non-diabetic patients with renal impairment due to various other causes. These findings point towards the complex multifactorial etiopathogenesis of anaemia in diabetes.

Other pathways contributing to development of anaemia in these patients are inflammatory meliu with associated increase in cytokines like IL 6 having detrimental effect on erythropoiesis, decreased responsiveness to erythropoietin, direct toxic effect on hematopoiesis, defect in feedback loop of peripheral blood cells and bone marrow and accelerated ageing and destruction of RBCs due to membrane protein glycation, rigidity and increased viscosity. [12] Drugs like metformin and ACE inhibitors also contribute to anaemia in diabetic population. Decreased hemoglobin concentration along with accelerated ageing of RBCs interfere with HbA1C estimation, thus creating conflict in effective pharmacotherapeutic control of hyperglycemia.

Anaemia in turn hastens the development and progress of micro- and macrovascular complications of diabetes, adding to the morbidity caused by these. Hence, correction of anaemia in diabetic patients can act as a preventive measure, avoiding much of morbidity and in turn improving quality of life. [13]

RDW showed significant increase in diabetic patients reflecting impaired erythropoiesis and inflammatory mileu. RDW is being considered as an independent inflammatory marker by some. Magri C et al found RDW to be elevated in patients with macro and microvascular complications in diabetes. [14]

Although normal in value, total count along with absolute lymphocyte count showed positive correlation with diabetes. Absolute neutrophil, eosinophil and monocyte count were higher in diabetic patients but they did not show any significant correlation. [15] Proinflammatory mileu along with oxidative stress present in diabetes is linked to the higher WBC count along with lymphocytosis in these patients, which in turn is linked to development and progress of various angiopathic complications associated with diabetes. [16] Epidemiological workers have suggested role of inflammation in inducing diabetes. Leucocyte function is derranged in diabetics, making them prone to recurrent infection. Even though absolute eosinophil count did not show any significant correlation, the number of diabetic subjects with eosinophilia was higher than non-diabetics. This could be due to asymptomatic/subclinical fungal infections they are prone to. [17]

Platelet count along with MPV was higher in diabetic subjects compared to control group. Due to microhemorrhages in the atheromatous plaques, the bone marrow is signaled to release reserve and immature giant platelets. Swelling of platelets due to hyperosmalirity of plasma and degranulation of platelets contribute to increase MPV and increased variation in size of platelets reflected in PDW. Platelet function is also affected in diabetes contributing to thrombotic complications. [18] Reduced effectiveness of antiplatelet drugs in diabetes has been studied by Agrawal R et al. [19] Development and progression of atherosclerosis is reflected in platelet parameters, particularly raised MPV. Malandrino N et al suggested a possible relation between MPV and pathophysiology of cardiovascular disease. Further platelet parameters are shown to be associated with HbA1C levels and cholesterol levels, which in turn is a major determinant of cardiovascular morbidity. [20]

To conclude periodic monitoring and careful assessment of haematological parameters can prove to be of utmost help in foreseeing, preventing and delaying many diabetes associated complications.

1. Farooqui R, Afsar N. Role and Significance of Hematological Parameters in Diabetes Mellitus. Annals of Pathology and Laboratory Medicine 2019; 6(3): 158-162.
2. Shukla D, Chandra K. Study of hematological parameters in patients with diabetes mellitus and hypertensive diabetes mellitus. International Journal of Medicine Research 2016;1(4): 28-31
3. Kumar HS et al. International Journal of Advances in Medicine.2017 Oct;4(5):1271-1275
4. Phadnis P, Kamble M et al. Prevalence and risk factors – Hemoglobin A1c, serum magnesium, lipids, and microalbuminuria for diabetic retinopathy: A rural Hospital-based study. J Datta Meghe Inst Med Sci Univ [serial online] 2017 [cited 2020 Apr 21]; 12:121-32
5. BeleteBiadgo, Mulugeta Melku. Hematological parameters and their correlation with fasting blood glucose level and anthropometric measurements in type 2 diabetes mellitus patients in Gondar, Northwest Ethiopia.Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2016:9 91– 992016:9 91–99
6. El-achkar T et al. Higher prevalence of anaemia with diabetes mellitus in moderate kidney insufficiency: The Kidney Early Evaluation Program. Kidney Int. 2005; 67(4):1483-8.
7. Bosman D et al. Anaemia with erythropoietin deficiency occurs early in diabetic nephropathy. Diabetes Care. 2001; 24(3):495-9.
8. Magri C, Fava S. Red blood cell distribution width and diabetes-associatedcomplications. Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2014; 8(1):13-17.
9. LeventDemirtas, HusnuDegirmenci. Association of hematologicalindicies with diabetes,impaired glucose regulation and microvascular complications of diabetes.Int J ClinExp Med 2015;8(7):114201142
10. Dragana Milosevic, VioletaLukicPanin. Relationship Between Hematological Parameters and Glycemic Control in Type 2 Diabetes Mellitus Patients.J Med Biochem 2019; 38: 164–171
11. SelvinE, Michael W. Glycatedhaemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med.2010; 362:800-811
12. Ravi Patel, Richa Patel. Hematological profile in uncomplicated type 2 diabetes mellitus patients. International Journal of Scientific Research.2019; 8(11):61-63.
13. Evans TC, Jehle D. The red blood cell distribution width. The Journal of emergency medicine 1991;9Suppl 1:71–74
14. Magri C, Fava S. Red blood cell distribution width and diabetes-associated complications. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2014;8(1):13-17.
15. White B. Hormonal regulation of energy metabolism. In: Koeppen B, Stanton B, editors. In: Berne and Levy Physiology 6th edition. Mosby Elsevier; 2010:676-689.
16. Virtue MA, Furne JK, Nuttall FQ, Levitt MD. Relationship between GHb concentration and erythrocyte survival determined from breath carbonmonoxide concentration. J Diabetes Care. 2004; 27:931-5.
17. Schmid-Schonbein H, Volger E. Red-cell aggregation and red-cell deformability in diabetes. J Diabetes. 1976; 25:897902.
18. McMillan DE, Utterback NG, La PJ. Reduced erythrocyte deformability in diabetes.J Diabetes. 1978; 27:895-901.
19. Agrawal R, Thomas S, João N, Christopher R, Rhythm B, Adnan T, et al. Assessment of red blood cell deformability in type 2 diabetes mellitus and diabetic retinopathy by dual optical tweezers stretching technique. Sci Reports 2016; 6:15873.
20. Malandrino N, Wu WC, Taveira TH, Whitlatch HB, Smith RJ. Association between red blood cell distribution width and macrovascular and microvascular complications in diabetes. Diabetologia. 2012 Jan;55(1):226-35.