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Assessment of red cell distribution width, glycaemic control and diabetes related complications - the ARDENT Study.

Byline: Mohammad Ali Arif, Fibhaa Syed, Rauf Niazi, Saba Ali Arif, Muhammad Usman Javed, Aimen Bashir and Sadia Mansoor

Keywords: RDW, HbA1c, Diabetic complications, Glycaemic control, Type 2 diabetes mellitus.

Introduction

Red blood cell distribution width (RDW) is a quantitative measurement of erythrocyte size variability. Automated haematology analysers provide RDW levels as part of the routine complete blood count (CBC). It is calculated by dividing the standard deviation of erythrocyte volume by the mean cell volume (MCV) and converting it into a percentage.1,2 The results of study data have linked elevated levels of RDW to poorer outcomes in the general population.3,4 There is an established association between raised RDW and cardiovascular disease, particularly coronary artery disease,5-8 stroke,9 heart failure10-18 and the metabolic syndrome.19 The documented associations extend beyond c ardi ovascular dis eas e, with studies highlig hting correlations between elevated RDW and Crohn's disease,20 hypothyroidism and hyperthyroidism,21 and chronic kidney disease.22

Thus it is not surprising that researchers have termed RDW an inflammatory marker with a significant predictive value of mortality in diseased and healthy populations.23,24 The findings of a strong, graded association between RDW and C-Reactive Protein (CRP) and the erythrocyte sedimentation rate (ESR) further establishes the use of RDW as a marker of inflammation.25 Elevated RDW in patients with diabetes has been found to be significantly higher than in non-diabetic controls23 and that longitudinal changes in RDW were significant in patients with diabetes versus non-diabetic counterparts.26 The current study was planned to evaluate RDW in patients with type 2 diabetes mellitus (T2DM) and to assess the relationship between RDW and glycaemic control and the presence of both microvascular and macrovascular complications.

Data collected was analysed using SPSS 20. Descriptive statistics were employed for qualitative variables, expressed as frequencies and percentages, and continuous variables, presented as means +- standard deviations (SD). Variables were compared using independent samples t-test for mean RDW, gender and presence of complications. Analysis of variance (ANOVA) was applied to compare the number of complications, age groups, duration of diabetes and extent of glycaemic control. Pearson correlation coefficient was applied to assess correlations between RDW and clinic-laboratory parameters. Statistical analysis was considered significant at the conventional p<0.05.

Table-1: Demographic and clinical features and mean red cell distribution width (RDW).

###RDW###n###p-value###RDW###n###p-value

###Mean+-SD###Mean+-SD

Sex###Presence of Macrovascular Complications

Male###15.29+-1.83###136###0.366###Yes###16.65+-1.65###60###<0.0001

Female###15.13+-1.49###213###No###14.89+-1.48###289

Age Group (years)###Number of Macrovascular Complications

26 - 35###14.90+-1.49###24###0.051###None###14.89+-1.48###289###<0.0001

36 - 45###15.02+-1.49###71###1###16.361.49###46

46 - 55###15.16+-1.49###115###2###17.37+-1.16###12

56 - 65###15.25+-1.79###93###3###18.90+-2.67###2

66 - 75###15.14+-1.41###31###Neuropathy

76 - 85###16.47+-2.38###15###Yes###15.74+-1.53###231###<0.0001

###No###14.13+-1.27###118

Duration of T2DM

< 5 Years###14.71+-1.48###152###<0.0001###Nephropathy

6 -10 Years###15.47+-1.43###92###Yes###16.21+-1.48###148### 20 Years###15.75+-2.49###25

Medical Treatment for T2DM###Retinopathy

Oral agents alone###14.90+-1.55###217###<0.0001###Yes###16.09+-1.39###162###<0.0001

Insulin alone###15.55+-1.54###47###No###14.42+-1.42###187

Insulin plus oral agents###15.74+-1.73###85

Hypertension###Presence of Microvascular Complications

Yes###15.55+-1.56###159###<0.0001###Yes###15.64+-1.49###266###<0.0001

No###14.89+-1.63###190###No###13.76+-1.18###83

Ischaemic Heart Disease###Number of Microvascular Complications

Yes###16.48+-1.57###32###<0.0001###None###13.75+-1.18###82###<0.0001

No###15.06+-1.58###317###1###14.70+-1.20###91

Peripheral Vascular Disease###2###15.66+-1.04###75

Yes###16.83+-1.43###22###<0.0001###3###16.50+-1.48###101

No###15.08+-1.59###327###Glycaemic Control

Cerebrovascular Disease###Optimal (HbA1c <7%)###13.93+-1.66###38###<0.0001

Yes###16.75+-1.61###21###8.5%)###15.76+-1.55###188

Myocardial Infarction

Yes###17.01+-1.79###33###<0.0001

No###15.01+-1.49###316

Table-2: Correlations between red cell distribution width (RDW) and clinical and laboratory parameters.

###Pearson Correlation###p-value

Age###0.123###0.022

Weight###-0.009###0.862

BMI###-0.036###0.505

Duration of T2DM###0.263###<0.0001

HbA1c###0.438###<0.0001

Random Blood Glucose###0.366###<0.0001

Fasting Blood Glucose###0.357###<0.0001

TLC###-0.027###0.616

Hb###0.026###0.626

MCV###-0.038###0.481

MCH###0.045###0.406

Haematocrit###0.041###0.443

Platelets###0.071###0.184

Urea###0.198###<0.0001

Creatinine###0.282###<0.0001

ALT###0.093###0.082

Total Cholesterol###0.134###0.012

LDL-C###0.079###0.141

HDL-C###-0.060###0.260

Triglycerides###0.098###0.067

Table-3: Correlations between red cell distribution width (RDW) and clinical and laboratory parameters.

###Optimal###Borderline###Poor###p-value

###(HbA1c 8.5%)

RDW###13.94+-1.66###14.72+-.38###15.76+-1.55###<0.0001

TLC###7676+-1614###7842+-1846###8580+-6097###0.239

Hb###13.5+-1.2###13.7+-1.0###13.4+-1.1###0.071

MCV###86.4+-3.7###85.3+-3.5###84.0+-3.5###<0.0001

MCH###29.2+-1.6###29.1+-2.2###28.9 +- 1.8###0.571

Platelets###261276+-82050###270974 +- 91421###281321 +- 89833###0.357

Urea###33+-13###41+-29###37+-21###0.192

Creatinine###0.98+-0.57###1.00+-0.59###1.10+-0.55###0.245

ALT###35+-22###33+-18###36+-22###0.308

Total Cholesterol###168+-45###171+-49###184+-54###0.043

LDL-C###92+-28###98+-39###106+-57###0.154

HDL-C###35+-7###35+-10###35+-8###0.798

Triglycerides###163+-66###179+-86###225+-174###0.004

Results

Of the 349 patients, 213(61%) were females. The overall mean age was 53.14+-11.77 years (range: 26-85 years. Mean T2DM duration was 8.36+-6.64 years and mean HbA1c was 9.05+-1.93. Macrovascular and complications as well as other conditions of the sample was noted (Table 1) Mean RDW was 15.194+-11.77% and it was be significantly associated with T2DM duration, hypertension, macrovascular and microvascular complications of diabetes and the extent of glycaemic control (p0.05 each). A statistically significant linear relationship was observed between RDW and number of macrovascular complications (p<0.0001), number of microvascular complications (p<0.0001) and HbA1c (p<0.0001). Weaker but statistically significant correlations were also observed for RDW and fasting blood glucose, random blood glucose, serum total cholesterol and serum creatinine (p<0.0001).

No significant correlations were seen between RDW and ALT, high-density lipoprotein (HDL), low-density lipoprotein (LDL) and triglycerides (TG). RDW value was also not significantly associated with any of the other CBC parameters (Table-2). Comparisons were analysed between different levels of glycaemic control and RDW. The mean value for RDW was 13.94+-1.66, 14.72+-1.38, 15.76+-1.55 for optimal control (HbA1c 8.5%) respectively. This linear incremental pattern was statistically significant (p<0.0001). Poor glycaemic control was associated with smaller values for MCV than optimal control (p<0.0001). Both total cholesterol and TG levels were found to increase as glycaemic control worsened (p<0.0001) (Table-3).

Discussion

The current study demonstrated a significant association between raised RDW and T2DM duration, the presence of hypertension, macrovascular and microvascular complications of diabetes and the extent of glycaemic control. A statistically significant linear relationship was found between RDW and number of macrovascular complications, number of microvascular complications and HbA1c. Increasing levels of HbA1c were associated with a rising trend in RDW. Weaker but statistically significant correlations were also observed for RDW and FBG, RBG, serum total cholesterol and serum creatinine. Our findings corroborate the study28 which found that RDW was significantly and positively associated with HbA1c, corresponding to an increase in HbA1c of 0.10% per 1 SD increase in RDW.

The relationship between RDW and complications of diabetes (microvascular and macrovascular) was investigated by a study27 which found that higher values of RDW were associated with anincreased probability of developing vascular complications, heart failure, myocardial infarction, stroke and nephropathy. T2DM is considered a pro-inflammatory state29 and it has been suggested30 that RDW can be used as a marker of inflammation in T2DM.

Red blood cells (RBCs) are impacted by hyperglycaemia in ways other than the formation of HbA1c. The presence of hyperglycaemia leads to reduced cellular deformability, altered mechanical properties of RBCs, an increase in adhesion and increased osmotic fragility. High glucose levels lead to rearrangement of erythrocyte membranes, defects in oxygen binding activity of Hb and alterations in the mechanical features of the cell membrane and general aspects of the cell wall.31,32 These changes lead to an altered erythrocyte structure and changes in the haemodynamic characteristics of RBCs.33,34 The effect of hyperglycaemia goes beyond structural changes, with a marked effect on RBC lifespan. This leads to high variability in erythrocyte volumes.35 Tight glycaemic control was found to result in a modest but consistent increase in RBC half-life compared to poor control.36

It can thus be inferred that the interplay between inflammation and the undesirable effects of hyperglycaemia on the mechanical features of the erythrocytes could impact RDW values. The question arises whether RDW is simply a marker of inflammation or is also actively involved in the pathogenesis of a variety of disorders. This has been aptly summarised in a review article.37 Citing a study38 which showed that a strong and direct relationship exists between the degree of anisocytosis (i.e. the RDW value) and the cholesterol content of erythrocytes membranes (p<0.001), and that the cholesterol content of erythrocytes membranes is positively and independently associated with clinical instability in patients with cardiovascular disorders. It also found that the total amount of free cholesterol contained within the necrotic core of advanced atherosclerotic plaques appears to be much greater than that expected from apoptotic death of inflammatory cells.

It thus postulated that it is conceivable that the free cholesterol in excess within the primary atherosclerotic lesion may originate from other cellular sources, including RBCs, and that anisocytosis may directly participate in the pathogenesis of cardiovascular disease (CVD) through a variety of mechanisms. Another postulated mechanism supporting the pathogenetic role of an elevated RDW in CVD relates to the physical properties of RBCs in patients with high degree of anisocytosis. A study39 showed that an increased RDW is significantly and positively associated with decreased erythrocyte deformability (p<0.003). Therefore, it is plausible that a greater variation of erythrocyte volumes would impair blood flow throught he microcirculation by increasing blood viscosity, thus triggering or amplifying the adverse consequences of a pre-existing vascular occlusion in both CVD and venous thrombosis.40

Deregulation of RBC homeostasis involving a combination of impaired erythropoiesis and abnormal erythrocyte metabolism and survival is mirrored by an increased RDW. This may potentially be caused by a variety of factors that include oxidative stress, inflammation fragmentation of RBCs, shortening of telomere length, hypertension, dyslipidaemia and abnormal erythropoietin function. All of the mentioned factors have an independent standing as important prognostic factors for severe morbidity and death.37 In terms of limitations, the cross-sectional design of the current study can measure only correlation but cannot establish causality. The study was a single-centre effort and was not prospective in nature. Also, the results represent the population of the study who were T2DM patients being managed at a government tertiary healthcare centre.

In order for our results to be generalised, a multi-centre replication should be performed to diversify patient groups. Other inflammatory markers such as ESR, CRP and serum ferr itin we re al so not measured.

Conclusion

RDW is a routinely per formed, low-cost and widely available marker that correlates well with glycaemic control. Its association with the presence of hypertension and both macrovascular and microvascular complications may reflect the inflammatory burden that exists with T2DM complications. The linear association with HbA1c may enable its use as a measure of the extent of hyperglycaemia and may provide a rationale for use in future prospec tive studies to fur ther explore this association.

Disclaimer: None.

Conflict of Interest: None.

Source of Funding: None.

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