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ORIGINAL ARTICLE
Year : 2018  |  Volume : 31  |  Issue : 2  |  Page : 449-454

Red blood cell distribution width to estimate lupus activity


Department of Internal Medicine, Faculty of Medicine, Menoufiya University, Shebeen El-Kom, Egypt

Date of Submission10-Nov-2016
Date of Acceptance11-Dec-2016
Date of Web Publication27-Aug-2018

Correspondence Address:
Heba G Sherief
Kafe Shanawan, Shebeen El-Kom, Menoufia
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1110-2098.239752

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  Abstract 


Objective
The aim of the study was to study red blood cell distribution width (RDW) in systemic lupus erythematous (SLE) patients as a lupus activity marker.
Background
SLE is a multifactorial systemic autoimmune disease that can affect multiple organs. The general pathogenesis of this disease still needs a better understanding. RDW is a measure of the red blood cell size variation.
Patient and methods
This prospective study was carried in the Internal Medicine Department, Menoufia University Hospital, from March 2016 to August 2016. Our study included 58 patients with SLE activity, which was measured using the Systemic Lupus Erythematous Disease Activity Index. RDW was measured as one of the parameters of complete blood count. RDW was reported on the Sysmex XT. In this study we excluded any other causes of anemia and other connective tissue diseases.
Results
The study included 58 SLE patients: 20 systemic lupus patients with high activity and 38 systemic lupus patients with very high activity. RDW was higher in systemic lupus patients with very high activity than in systemic lupus patients with high activity. There was a highly significant correlation between RDW and Systemic Lupus Erythematous Disease Activity Index. There was a highly significant correlation between RDW and erythrocyte sedimentation rate.
Conclusion
There was statistically higher RDW in lupus patients with very high activity than in those with high activity; therefore, RDW can be used as a lupus activity marker. RDW was associated with the inflammatory process of SLE.

Keywords: lupus activity, red blood cells distribution width, red blood cell indices, systemic lupus erythematous


How to cite this article:
Shoeib SA, Abd Elhafez MA, Abd El-Hamed AE, Sherief HG. Red blood cell distribution width to estimate lupus activity. Menoufia Med J 2018;31:449-54

How to cite this URL:
Shoeib SA, Abd Elhafez MA, Abd El-Hamed AE, Sherief HG. Red blood cell distribution width to estimate lupus activity. Menoufia Med J [serial online] 2018 [cited 2018 Sep 24];31:449-54. Available from: http://www.mmj.eg.net/text.asp?2018/31/2/449/239752




  Introduction Top


Systemic lupus erythematous (SLE) is a multifactorial systemic autoimmune disease that can affect multiple organs such as skin, joints, central nervous system, or kidneys. Even though hormonal, environmental, and genetic factors have been associated with SLE, the general pathogenesis of this disease still needs a better understanding [1]. SLE is considered a B-cell disease as most lupus patients present high titers of autoreactive antibodies mainly raised against nuclear antigens [such as double-stranded DNA (dsDNA) and ribonucleoproteins] associated with their targets (autoantigens) and to complement factors, forming circulating immune complexes. Circulating immune complexe deposition in target organs initiates and maintains an inflammatory response leading to the symptomatology of the disease. Disease activity is known to correlate with autoantibody titers, especially anti-dsDNA immunoglobulin (Ig) of G isotypes (IgG) [2]. Overproduction of high-affinity autoantibodies in SLE is a consequence of several aberrant immunological processes involving both adaptive and innate immune systems. Many environmental and genetic factors can influence the loss of tolerance of B and T cells. Indeed, different T helper (TH) cell subsets, such as TH1, TH2, TH17, T follicular helper, or even regulatory T cells, have been involved in the inflammatory process of the disease [3]. Concerning the innate immune system, neutrophils, as a different source of autoantigens (neutrophil extracellular traps) [4], plasmacytoid dendritic cells, as one of the dominant producers of interferon-α [5], and basophils and autoreactive IgE as amplifiers of autoantibody production contribute to the activation of the adaptive immune system and perpetuate the inflammatory response [1].

Biomarkers are very useful in diagnosis, evaluation, and management of SLE and can be of help in early detection of a disease flare and monitoring disease activity. An ideal biomarker should accurately detect disease activity and guide therapy at every stage of SLE [6].

Mean corpuscular volume (MCV) is an index of red blood cell (RBC) size. Red cell distribution width (RDW) is a measure of the size variation (i.e., anisocytosis) and is used for classification of anemia [7].

RDW demonstrates the heterogeneity of red cell volume and is a component of the complete blood count. The RDW is also a widely available, inexpensive, and easily repeatable marker that measures RBC volume variability [8].

Increased RDW may be seen in other hematological disorders such as hemolytic anemia, sickle cell/β-thalassemia, anemia of chronic disorders, hereditary spherocytosis, and sickle cell anemia, and has also been associated with nonhematological diseases such as chronic hepatobiliary disease, hypothyroidism, hyperthyroidism, Behcet's disease, SLE, and inflammatory bowel disease [7].

The aim of this study was to study RDW in SLE patients as a lupus activity marker.


  Patients and Methods Top


Patients

This study was carried out in the Internal Medicine Department, Menoufia University Hospital, from March 2016 to August 2016. It followed the ethical standards of our institution. Informed consent from all patients was obtained in accordance with the local ethical committee. This study included 58 SLE patients. All patients diagnosed as SLE fulfilled at least four of the 2012 Systemic Lupus International Collaborating Clinics Classification (SLICC) criteria. Activity of patients was measured with the Systemic Lupus Erythematous Disease Activity Index (SLEDAI). They were divided into the following groups according to lupus activity: group I included 20 SLE patients with high activity and group II included 38 SLE patients with very high activity.

Methods

All participants underwent full history taking and the following clinical and laboratory investigations: (a) complete blood count, blood films, and reticulocytes; (b) lupus serology antinuclear antibody, anti-dsDNA; (c) serum C3 and C4; (d) serum CRP and erythrocyte sedimentation rate (ESR); (e) liver function tests; (f) kidney function tests; and (g) urine analysis and protein/creatinine ratio. In this study we excluded any patients with infections, other connective tissue diseases, malignant diseases, pregnancy, or any other causes of anemia, such as iron deficiency, heredity, etc. RDW is reported on the Sysmex XT (1-5-1, Wakinohama-kaigandori, Chuo-ku, Kobe, Hyogo 651-0073, Japan) as a coefficient of variation from the mean red blood cell size.

Statistical analysis

All data were collected, tabulated, and statistically analyzed using SPSS 20.0 for Windows (SPSS Inc., Chicago, Illinois, USA) and MedCalc 13 for Windows (MedCalc Software bvba, Ostend, Belgium). Quantitative data were expressed as mean ± SD and analyzed by applying the t-test for comparison between two groups of normally distributed variables, whereas for comparison between two groups of not normally distributed variables the Mann–Whitney test was applied. Qualitative data were expressed as number and percentage and analyzed by applying the χ2-test for comparison between two or more independent qualitative variables that were normally distributed. The Fisher exact test was used for comparison between two independent qualitative variables with one of the observed cells less than 5, and R (Pearson's correlation coefficient) was used for comparison of two dependent quantitative variables that were normally distributed.

P value more than 0.05 was considered statistically nonsignificant.

P value less than 0.05 was considered statistically significant.

P value less than 0.001 was considered statistically highly significant.


  Results Top


The study included 58 patients who were divided into two groups: 20 systemic lupus patients with high activity (group I) and 38 systemic lupus patients with very high activity (group II). All patients diagnosed with SLE fulfilled at least four of the 2012 SLICC classification criteria. The activity in patients was measured with SLEDAI.

There was no statistically significant difference between the studied groups as regards age and sex. The mean age in group I was 29.1 ± 11.1 years. The mean age in group II was 27.7 ± 9.6 years. There were 20 (100%) female patients in group I and 34 (89.5%) patients in group II. There were four (10.5%) male patients in group II and no male patient in group I [Table 1].
Table 1: Demographic data of the studied groups

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There was no statistically significant difference between groups I and II as regards malar rash, photosensitivity, oral ulcers, discoid rash, arthritis, serositis, hair loss, renal manifestation, and cerebral manifestations [Table 2].
Table 2: Distribution of diagnostic features of systemic lupus erythematous in the studied patients

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There was a statistically significant difference between the studied groups as regards anti-dsDNA: 96.4 ± 35.7 μ/ml in group I and 290.3 ± 101.2 μ/ml in group II. There was no statistically significant difference between the studied groups as regards C3: 85 ± 32.2 mg/l in group I and 76.7 ± 39.4 mg/l in group II. There was a statistically significant difference between the studied groups as regards C4: 11.9 ± 5.4 mg/l in group I and 9.2 ± 3 mg/l in group II. There was a statistically significant difference between the studied groups as regards hemoglobin (Hb): 9.2 ± 2.3 g/dl in group I and 8 ± 0.7 g/dl in group II. There was a statistically highly significant difference between the studied groups as regards RDW: 15.5 ± 2% in group I and 18.5 ± 1.2% in group II.

There was a statistically significant difference between the studied groups as regards creatinine: 0.7 ± 0.5 mg/dl in group I and 1.7 ± 1.07 mg/dl in group II. There was a statistically significant difference between the studied groups as regards protein/creatinine ratio: 2.5 ± 2.1 mg/g in group I and 4 ± 3.1 mg/g in group II. There was no statistically significant difference between the studied groups as regards reticulocytes, MCV, WBCS, platelets (PLT), blood urea nitrogen, prothrombin time, international normalized ratio, aspartate aminotransferase, alanine aminotransferase, and potassium [Table 3].
Table 3: Laboratory parameters of studied groups

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There was a significant correlation between the SLEDI score and anti-dsDNA, blood urea nitrogen, and protein/creatinine ratio. There was a highly significant correlation between the SLEDI score and RDW and creatinine. There was a significant negative correlation between the SLEDI score and Hb, PLT, and C3. There was a highly significant negative correlation between the SLEDI score and C4. There was no significant correlation between the SLEDI score and MCV, WBC, reticulocytes, potassium, prothrombin time, international normalized ratio, aspartate aminotransferase, and alanine aminotransferase [Table 4].
Table 4: Correlation coefficient (r) between Systemic Lupus Erythematosus Disease Activity Index and laboratory data

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There was a highly significant correlation between RDW and ESR [Table 5] [Figure 1] and [Figure 2].
Table 5: Correlation coefficient (r) between red cell distribution width and inflammatory markers

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Figure 1: Correlation coefficient (r) between SLEDI and RDW. RDW, red cell distribution width; SLEDI, Systemic Lupus Erythematosus Disease Activity Index.

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Figure 2: Correlation coefficient (r) between RDW and ESR. ESR, erythrocyte sedimentation rate; RDW, red cell distribution width.

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  Discussion Top


SLE is a chronic, multifaceted autoimmune inflammatory disease that can affect any part of the body [9]. Measurement of disease activity in SLE is central to evaluating outcomes, differences among SLE patient groups, responses to a new drug proposed, and also for assessing the disease [10]. RDW is a measure of RBC volume variations (anisocytosis) [11]. In the current study we aimed to evaluate RDW in SLE patients as an activity maker. In the current study, we examined 58 lupus patients, who were divided into two groups. Group I included 20 systemic lupus patients with high activity and group II included 38 systemic lupus patients with very high activity.

According to the laboratory findings of the studied groups, there was a statistically significant difference between systemic lupus patients with high activity (group I) and lupus patients with very high activity (group II) as regards anti-dsDNA. ANA and anti-dsDNA were used in the diagnosis of patient with SLE. In our study all patients had positive ANA and anti-dsDNA. Hochberg et al. [12] reported positive ANA and anti-dsDNA in American College of Rheumatology Revised Criteria, which were used in the diagnosis of SLE patients.

Petri et al. [13] reported positive ANA and anti-dsDNA in the SLICC classification criteria, which were used in the diagnosis of SLE patients. Bombardier et al. [14] reported that elevation of anti-dsDNA more than 25% binding by Farr assay or above normal range for testing laboratory presented an SLEDAI score of 2. Our study showed that there was a statistically significant difference between systemic lupus patients with high activity (group I) and lupus patients with very high activity (group II) as regards complement 4 (C4). There was a greater decrease in complement 4 (C4) in group II than in group I. Lui et al. [15] reported that C4 level was correlated with SLE disease activity. Papp et al. [16] reported that in SLE patients consumption of C4 led to deficiency of its level. He also reported that C4 level decreased in patient with SLE activity. There was no statistically significant difference between systemic lupus patients with high activity (group I) and lupus patients with very high activity (group II) as regards complement 3 (C3). C3 plays a role in the pathology of SLE patients similar to C4, and hence their consumption leads to decrease in its levels in SLE patients. Narayanan et al. [17] reported that C3 can be used to assess lupus activity. Li et al. [18] observed a low level of either C3 or C4 in patients with active SLE. In the SLEDAI, deceased level of C3 or C4 below normal represented an SLEDAI score of 2. Thus, decreased level of one complement can assess the activity.

The study showed that there was a statistically significant difference between systemic lupus patients with high activity (group I) and lupus patients with very high activity (group II) as regards Hb level. Voulgarelis et al. [19] reported that SLE patients with anemia of chronic disease had a significantly higher disease activity. They also reported that the severity of anemia correlated with disease activity among iron deficiency SLE patients.

This study showed that there was a statistically significant difference between systemic lupus patients with high activity (group I) and lupus patients with very high activity (group II) as regards proteinuria. Bombardier et al. [14] reported that proteinuria greater than 0.5-g of urinary protein excreted per 24 h, new onset or recent increase of more than 0.5 g/24 h represented an SLEDAI score of 4.

There was a highly statistically significant difference between systemic lupus patients with high activity (group I) and lupus patients with very high activity (group II) as regards RDW. Vayá et al. [20] reported that RDW was high in anemic and nonanemic SLE patients, indicating that RDW could also be related to inflammation and not only to anemia. Nada [21] reported that higher RDW in diabetic patients than in healthy controls occurred in the presence of chronic inflammation and increased level of oxidative stress. Lee et al. [22] reported that in multiple myeloma, RDW level was influenced by anemia. Anemia of multiple myeloma did not simply reflect a decrease in red cell counts, but it was also associated with impaired iron release from reticuloendothelial macrophages, which could be observed in anemia of inflammatory conditions. This suggested that RDW could reflect the overall inflammatory condition of multiple myeloma.

There was a significant correlation between the SLEDI score and anti-dsDNA and protein/creatinine ratio. There was a significant negative correlation between the SLEDI score and Hb, PLT, and C3. There was a highly significant negative correlation between the SLEDI score and C4. Bombardier et al. [14] reported that anti-dsDNA, C3, C4, PLTs, and proteinuria were used in the SLEDAI score to assess the activity of SLE. In this study there was a highly significant correlation coefficient (r) between SLEDI and RDW; RDW increased with increased activity of SLE and could be used as a lupus activity marker.

In our study there was a highly significant correlation between RDW and ESR.

Lippi et al. [23] reported a strong, graded association of RDW with ESR.


  Conclusion Top


There was a statistically higher increase in RDW in lupus patients with very high activity than in those with high activity; hence RDW can be used as a lupus activity marker. RDW was associated with the inflammatory process of SLE.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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    Figures

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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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