GLUCOSE INTOLERANCE IN RHEUMATOID ARTHRITIS AND SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS

Document Type : Original Article

Authors

1 Departments of Internal Medicine, Faculty of medicine, Al-Azhar University

2 Departments of Clinical Pathology, Faculty of medicine, Al-Azhar University

Abstract

Background: Glucose intolerance is an important contributor to the increased cardiovascular risk attributed to the metabolic syndrome, a constellation of cardiovascular risk factors that includes central obesity, dyslipidemia, hypertension, and disturbed glucose metabolism in patients with rheumatoid arthritis or systemic lupus erytheromatosus.
Objective: To assess glucose intolerance percentage in rheumatoid arthritis and systemic lupus erythreromatosus patients.
Patients and methods: The present study was a prospective study conducted on 90 subjects. The studied patients were recruited from Internal Medicine Clinic at Al-HusseinUniversityHospital during the period from January 2020 to January 2021. Patients were divided into three groups, group I: thirty patients with Systemic lupus erythromatosus (SLE), group II: thirty patients with Rheumatoid arthritis (RA) group III: included thirty healthy individuals as control group. The following laboratories were done for all groups to assess glucose intolerance (CBC, CRP, ESR, Fasting blood sugar(FBG),Post prandial blood sugar (PPBS), Haemoglobin A1C (HbA1C), Complement3 (C3), Complement4 (C4) and Albumin/creatnin (ALB/Creat ratio).
Results: There were statistically significant difference between studied groups as regard blood glucose level assessment (FBS, PPBS & HbA1C), glucose intolerance, hemoglobin, ESR, Albumin/Creatinine ratio, complement 3, glucose intolerance and (FBS, PPBS & HbA1C) in SLE, glucose intolerance and (FBS, PPBS& HbA1C) in RA group, glucose intolerance and hemoglobin in SLE group however there were no statistically significant difference between studied groups as regard CRP, WBCs, PLTs and C4.
Conclusion: SLE and RA patients appeared to have higher incidence of glucose intolerance than normal subjects.

Keywords

Main Subjects


GLUCOSE INTOLERANCE IN RHEUMATOID ARTHRITIS AND SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS

By

Rabie Ismaeil Eid, Mohamed Nabil Rafat, Mohamed Hassan Attia Hassan and Ahmed Ali Ali Asem

Departments of Internal Medicine and Clinical Pathology*, Faculty of medicine, Al-AzharUniversity

Corresponding Author: Rabie Ismaeil Eid, E-mail: rabieismaeil2015@gmail.com

ABSTRACT

Background: Glucose intolerance is an important contributor to the increased cardiovascular risk attributed to the metabolic syndrome, a constellation of cardiovascular risk factors that includes central obesity, dyslipidemia, hypertension, and disturbed glucose metabolism in patients with rheumatoid arthritis or systemic lupus erytheromatosus.

Objective: To assess glucose intolerance percentage in rheumatoid arthritis and systemic lupus erythreromatosus patients.

Patients and methods: The present study was a prospective study conducted on 90 subjects. The studied patients were recruited from Internal Medicine Clinic at Al-HusseinUniversityHospital during the period from January 2020 to January 2021. Patients were divided into three groups, group I: thirty patients with Systemic lupus erythromatosus (SLE), group II: thirty patients with Rheumatoid arthritis (RA) group III: included thirty healthy individuals as control group. The following laboratories were done for all groups to assess glucose intolerance (CBC, CRP, ESR, Fasting blood sugar(FBG),Post prandial blood sugar (PPBS), Haemoglobin A1C (HbA1C), Complement3 (C3), Complement4 (C4) and Albumin/creatnin (ALB/Creat ratio).

Results: There were statistically significant difference between studied groups as regard blood glucose level assessment (FBS, PPBS & HbA1C), glucose intolerance, hemoglobin, ESR, Albumin/Creatinine ratio, complement 3, glucose intolerance and (FBS, PPBS & HbA1C) in SLE, glucose intolerance and (FBS, PPBS& HbA1C) in RA group, glucose intolerance and hemoglobin in SLE group however there were no statistically significant difference between studied groups as regard CRP, WBCs, PLTs and C4.

Conclusion: SLE and RA patients appeared to have higher incidence of glucose intolerance than normal subjects.

Keywords: Glucose intolerance, Rheumatoid arthritis, Systemic lupus erytheromatosus.

 

 

INTRODUCTION

     Systemic lupus erytheromatosus (SLE) is a chronic, multifaceted inflammatory disease that can attack every organ system of the body. SLE is protean in its manifestations and follows a relapsing and remitting course. Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease of unknown etiology. The classic feature of this disease is persistent symmetric polyarthritis that usually involves the peripheral joints in a symmetric distribution but can affect any joint lined by a synovial membrane (Gazareen et al., 2014).

     Rheumatology is a medical science devoted to the study of rheumatic diseases that include a range of musculoskeletal and systemic disorders that share the clinical involvement of joins and periarticular tissues. Rheumatoid arthritis (RA) is a systemic, autoimmune disorder that causes chronic synovial inflammation of multiple joints affecting 0.5–1% of population all over the world (Balasubramanyam et al., 2014).

     It affects women three times more than the men. Recent studies have shown increasing prevalence of dysglycemia in rheumatoid arthritis patients. Impaired glucose handling in RA patients is secondary to peripheral insulin resistance mediated by the inflammatory response. Role of various pro-inflammatory cytokines (including tumor necrosis factor [TNF] and interleukin-6 [IL-6]) in RA, insulin resistance (IR), and type 2 diabetes mellitus (T2DM) has been reported by several independent studies (Hoet and Tripathy, 2016).

     RA patients with diabetes mellitus (DM) prevalence rate was about 15% to 19%, which was significantly higher than the prevalence rate of 4% to 8% of global middle-aged population DM (Simard and Mittleman, 2011).

     In a study, which consists of 48,718 cases of RA patients and 40,346 cases of non-rheumatic subjects, the incidence of RA patients with DM was 0.86% higher than the 0.58% in the control group which was observed, and DM risk was 1.5-fold in RA patients when compared with control group (Solomon et al., 2010).

     Consistently, a study described that abnormal glucose metabolism in RA patients was up to 46% after 2 years when compared with the time point of recruitment (Hoes et al., 2011).

     Systemic lupus erytheromatosus is a systemic connective tissue disorder affecting mainly females. Female: male ratio was 9:1 with peak onset in the second and third decade. Systemic inflammation has been suggested as the main physiologic link between IR and SLE (Escarcega et al., 2010).

     The aim of the present study was to assess glucose intolerance percentage in rheumatoid arthritis and systemic lupus erytheromatosus patients.

PATIENTS AND METHODS

     The present study was a prospective study conducted on 90 subjects. The studied patients were recruited from Internal Medicine Clinic at Al-HusseinUniversityHospital during the period from July 2020 to January 2021.

Patients were classified into three equal groups:

•     Group I: Patients newly diagnosed with SLE based on positive ANA and anti-ds DNA tests.

•     Group II: Patients with rheumatoid arthritis disease based on American Criteria for Rheumatoid Arthritis.

•     Group III: Apparently healthy subjects not known to chronic diseases.

Exclusion criteria:

1.   Patients having co-morbid illness like diabetes mellitus, hypertension, and coronary artery disease.

2.   Family history of DM.

3.   Patients on steroid treatment.

All patients were subjected to full history taking, physical examination (general and local), and laboratory investigations included:

•     CBC was performed using automated CELL-DYN Ruby hematology analyzer.

•     Blood glucose tests (fasting blood glucose, 2h postprandial blood glucose and HBA1c).

•     C-reactive protein (CRP).

•     Erythrocyte sedimentation rate (ESR).

•     Complement (C3, C4).

•     Alb / creat ratio.

Statistical analysis:

     The collected data were coded, processed and analyzed using the SPSS (Statistical Package for the Social Sciences) version 22 for Windows® (IBM SPSS Inc, Chicago, IL, USA). Data were tested for normal distribution using the Shapiro Wilk test. Qualitative data were represented as frequencies and relative percentages. Chi square test (χ2) to calculate difference between two or more groups of qualitative variables. Quantitative data were expressed as mean ± SD (Standard deviation). Independent samples t-test was used to compare between two independent groups of normally distributed variables (parametric data). Mann–Whitney U test was used when comparing between two means (for abnormal distributed data). Kruskal wills test was used when comparing between more than two means (for abnormal distributed data). P value < 0.05 was considered significant.


 

RESULTS

 

 

     There were statistically significant difference between studied groups as regard blood glucose level assessment (FBS, PPBS& HbA1C), glucose intolerance, Hb, ESR, ALB/Creat ratio, C3, glucose intolerance and (FBS, PPBS & HbA1C) in SLE, glucose intolerance and (FBS, PPBS & HbA1C) in RA group, glucose intolerance and Hb in SLE group but no statistical significant difference between studied groups as regard CRP, WBCs, PLTs and C4.

     There was no statistical significant difference between studied groups as regard WBCs and PLTs. There was a statistically significant difference between studied groups as regard ALB/Creat ratio. There was a statistically significant difference between studied groups as regard C3. There was no statistical significant difference between studied groups as regard C4 (Table 1).


 

 

 

 

 

 

 

Table (1):   Comparisons between studied groups as regard demographic data, blood glucose level assessment, glucose intolerance, ESR & CRP, CBC, ALB/Creat ratio, and C3 & C4

Groups

Parameters

SLE

(n = 30)

RA

(n = 30)

Control

(n = 30)

Stat. test

P-value

Sex

Male

9

30%

9

30%

6

20%

X² = 1.02

0.6

Female

21

70%

21

70%

24

80%

X² = 1.02

Age (years)

Median

21.5

40.5

37.5

KW = 28.06

< 0.001

IQR

17 – 30.25

30 – 48.3

21 – 47.3

KW = 28.06

FBS (mg/dl)

Median

95.5

109.5

86

KW

0.006

10.1

IQR

86.3 – 114.3

86.8 – 117.3

79.8 – 94

10.1

PPBS (mg/dl)

Median

104

144

99

9.2

0.01

IQR

95.5 – 167.5

101 – 166.5

90 – 120.5

9.2

HbA1C (%)

Median

5.3

5.7

5.05

14.9

0.001

IQR

5 - 6

5.3 – 6.1

4.8 – 5.4

14.9

Glucose intolerance

No

19

63.3%

14

46.7%

26

86.7%

Stat. test

0.005

X² = 10.7

Yes

11

36.7%

16

53.3%

4

13.3%

X² = 10.7

ESR (mm/h)

Median

33.5

22.4

15

KW

0.003

11.8

IQR

15.8 – 50

10 – 40

10 – 25

11.8

CRP (mg/L)

Median

5

7

5

3.79

0.150

IQR

2 – 8.25

4 – 11.25

4 - 9

3.79

Hb (g/dl)

Median

11.25

11

12.3

KW

0.049

6.04

IQR

10.4 – 13

9.9 – 13

11.8 – 13.6

6.04

WBCs (x10³/ul)

Median

5.8

5.5

5.6

0.46

0.794

IQR

4.75 – 7.9

4.6 – 7.5

4.9 – 7.02

0.46

PLTs (x10³/ul)

Median

237.5

289

259.5

4.05

0.132

IQR

154.3 – 318.8

233 – 401.5

189.3 – 287.5

4.05

ALB / Creat

Median

26

15.5

15.5

KW

0.001

14.4

IQR

17 - 81

10 – 25

10 – 24.3

14.4

C3 (mg/dl)

Median

104.5

98

116.5

KW

0.045

6.2

IQR

77 – 129

86.8 – 114.3

94.5 – 150

6.2

C4 (mg/dl)

Median

31

33.5

34

2.45

0.294

IQR

23.8 – 39.3

25 – 41

28.8           - 40

2.45

 

 

 

     There was no statistical significant relation between glucose intolerance and age, ESR, CRP, WBCs, PLTs, ALB/Creat ratio, C3 and C4 in SLE group. There was a statistical significant relation between glucose intolerance and FBS, PPBS and HbA1C in SLE group. There was a statistically significant relation between glucose intolerance and Hb in SLE group (Table 2).

 

 

Table (2):   Post-Hoc test for multiple comparisons between studied groups as regard significant laboratory data

Groups

Parameters

SLE vs RA

SLE vs Control

RA vs Control

age

LSD

-16.2

-12.4

3.8

p-value

< 0.001 HS

< 0.001 HS

0.177 NS

FBS

LSD

-3.7

8.6

12.3

p-value

0.336 NS

0.025 S

0.002 S

PPBS

LSD

-10.7

15.7

26.4

p-value

0.203 NS

0.063 NS

0.002 S

HbA1C

LSD

-0.2

0.3

0.5

p-value

0.087 NS

0.015 S

< 0.001 HS

ESR

LSD

6.4

16.8

10.4

p-value

0.214 NS

0.001 S

0.044 S

Hb

LSD

-0.1

-1.1

-1.0

p-value

0.84 NS

0.028 S

0.045 S

ALB/Creat

LSD

95.0

96.9

1.9

p-value

0.001 S

0.001 S

0.947 NS

C3

LSD

-3.9

-19.2

-15.2

p-value

0.626 NS

0.019 S

0.62           NS

 

 

     As regard age, there were significant differences between SLE and RA and control groups, while no statistical significant difference between SLE and RA groups.

     As regard FBS, there were no statistical significant difference between SLE and RA groups, while significant difference between SLE, RA and Control groups.

     As regard PPBS, there were no statistical significant difference between SLE, RA and control groups, while significant difference between SLE and RA groups.

As regard HbA1C, there were no statistical significant difference between SLE and RA groups, while significant difference between SLE, RA and Control groups.

     As regard ESR, there no statistical significant difference between SLE and RA groups, while there were significant difference between SLE, RA and Control groups.

     As regard Hb, there were no statistical significant difference between SLE and RA groups, while there were significant difference between SLE and Control group’s significant difference between SLE and RA groups.

     As regard ALB/Creat, there were statistically significant differences between SLE, RA and control groups. But no statistical significant difference between SLE and RA groups.

     As regard C3, there were no statistical significant difference between SLE and RA groups but there were a significant difference between SLE and control groups Table (3).

 

Table (3):   Relation between glucose intolerance & studied data in SLE group

Glucose intolerance

SLE groups

No

(n = 19)

Yes

(n = 11)

Stat. test

P-value

Age (years)

Mean

24.3

22.5

MW = 96

0.735

±SD

9.3

7.0

FBS (mg/dl)

Mean

89.3

115.5

T = 11.1

< 0.001

±SD

5.7

7.1

T = 11.1

PPBS (mg/dl)

Mean

98.6

170.5

T = 17.4

< 0.001

±SD

10.5

11.4

T = 17.4

HbA1C (%)

Mean

5.1

6.1

T = 9.5

< 0.001

±SD

0.3

0.2

T = 9.5

ESR (mm/h)

Mean

33.3

37.7

MW = 97.5

0.767

±SD

18.5

25.1

CRP (mg/L)

Median

4

7

MW = 73

0.185

IQR

2 - 7

2 – 29

MW = 73

Hb (g/dl)

Mean

12.0

10.3

T = 2.26

0.032

±SD

2.1

1.8

T = 2.26

WBCs (x10³/ul)

Mean

6.7

5.7

MW = 79

0.287

±SD

2.6

2.1

PLTs (x10³/ul)

Mean

247.7

246.7

MW = 97

0.767

±SD

126.3

95.2

ALB / Creat

Median

25

27

MW = 89

0.525

IQR

16 – 123

20 – 67

MW = 89

C3 (mg/dl)

Median

110

78

MW = 64

0.085

IQR

89 - 132

70 - 128

MW = 64

C4 (mg/dl)

Mean

31.5

30.1

MW = 90

0.553

±SD

9.4

8.1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     There was no statistical significant relation between glucose intolerance and age, ESR, CRP, Hb, WBCs, PLTs, ALB/Creat ratio, C3 and C4 in RA group. There was a statistical significant relation between glucose intolerance and FBS, PPBS and HbA1C in RA group (Table 4).

 

 

Table (4):   Relation between glucose intolerance & studied data in RA group

Glucose intolerance

RA groups

No

(n = 14)

Yes

(n = 15)

Stat. test

P-value

Age (years)

Mean

40.4

39.4

MW = 108

0.886

±SD

10.7

10.4

FBS (mg/dl)

Mean

86.6

116.5

T = 18.4

< 0.001

±SD

4.0

4.8

T = 18.4

PPBS (mg/dl)

Mean

105.9

161.7

T = 10.3

< 0.001

±SD

16.2

13.2

T = 10.3

HbA1C (%)

Mean

5.2

6.1

T = 9.5

< 0.001

±SD

0.3

0.2

T = 9.5

ESR (mm/h)

Median

23.8

32.8

MW = 77.5

0.154

IQR

8.75 – 33.5

16.3 – 43.8

MW = 77.5

CRP (mg/L)

Median

15.1

11.2

MW = 107

0.854

IQR

4 – 11.25

4.3 – 11.5

MW = 107

Hb (g/dl)

Mean

11.9

11.1

T = 1.25

0.221

±SD

1.8

1.8

T = 1.25

WBCs (x10³/ul)

Mean

6.4

5.7

MW = 82

0.331

±SD

2.2

2.2

PLTs (x10³/ul)

Median

324.6

338.4

MW = 111

0.984

IQR

246 – 370

185 – 441.5

MW = 111

ALB / Creat

Median

18.9

19.3

MW = 87.5

0.313

IQR

12.3 – 25.3

10 -22.3

MW = 87.5

C3 (mg/dl)

Mean

105.7

107.9

MW = 104.5

0.759

±SD

29.1

31.9

C4 (mg/dl)

Mean

31.1

34.4

MW = 93

0.448

±SD

10.2

8.6

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     There was no statistical significant relation (p-value > 0.05) between glucose intolerance and studied laboratory data except for (FBS, PPBS and HbA1C) (Table 5).

 

 

Table (5):   Relation between glucose intolerance and studied data in control group

Glucose intolerance

Control group

No

(n = 26)

Yes

(n = 4)

MW

p-value

Age (years)

Mean

36.9

30.0

38.5

0.425

±SD

13.6

11.5

FBS (mg/dl)

Mean

85.4

121.8

0.0

< 0.001

±SD

6.7

3.3

PPBS (mg/dl)

Mean

100.0

169.3

0.0

< 0.001

±SD

14.0

15.2

HbA1C (%)

Mean

5.0

5.9

0.0

< 0.001

±SD

0.3

0.1

ESR (mm/h)

Mean

16.2

31.3

44.5

0.659

±SD

9.7

34.2

CRP (mg/L)

Mean

5.7

6.3

44.5

0.659

±SD

3.2

2.5

Hb (g/dl)

Mean

12.5

12.6

42.5

0.576

±SD

1.3

2.7

WBCs (x10³/ul)

Mean

6.3

6.2

41.5

0.536

±SD

1.8

2.7

PLTs (x10³/ul)

Mean

252.9

313.3

28

0.157

±SD

76.2

81.9

ALB / Creat

Mean

17.4

16.5

46

0.746

±SD

9.1

9.3

C3 (mg/dl)

Mean

123.2

114.8

47

0.791

±SD

32.0

19.5

C4 (mg/dl)

Mean

34.2

34.5

50.5

0.930

±SD

6.7

6.6

 

 

DISCUSSION

     In the present study in comparing between studied groups as regard demographic data, there was a statistical significant difference, between SLE and RA groups, and between SLE & control groups as regard age with. No statistical significant difference between studied groups as regard sex. This was in agreement with El-gendi et al. (2018) who reported that no significant sex difference between studied diseased groups. This result was in contrast with Julie and Chaim (2012), who showed that SLE typically affects females more than males. However, male SLE patients often have more severe disease than females.

     In the current study, there were statistically significant differences between studied groups as regard blood glucose level assessment (FBS, PPBS & HbA1C). This result was in agreement with Chung et al. (2010) and Gazareena et al. (2014) who reported that RA patients have significantly higher fasting blood glucose, fasting insulin than SLE patients. This can be explained by some factors such as older age in RA patients than SLE and longer duration of disease in RA patients reflecting the burden of such disease.

     In the current study, there was a statistically significant difference between studied groups as regard ESR. However, there was no statistical significant difference between studied groups as regard CRP. These results were in agreement with Seriolo et al. (2010) and Ormseth et al. (2012) who reported that there were statistically significances higher ESR and CRP in RA patients than in controls. Also, these results were in agreement with Lozovoy et al. (2011), who showed that SLE patients with hyperinsulinemia had significantly higher ESR and CRP.

     In the present study, there was a statistically significant difference between studied groups as regard Hb, while, no statistical significant difference between SLE and RA groups. There were statistically significant differences between SLE and control groups and statistically significant difference between RA and control groups. These results were in agreement with Rattarittamrong et al. (2016) who reported that 64% of SLE patients in the study suffered from anemia.

    Anemia was found in about 50% of SLE patients. Many mechanisms contribute to the development of anemia, including inflammation, renal insufficiency, blood loss, dietary insufficiency, medications, haemolysis, infection, hypersplenism, myelofibrosis, myelodysplasia, and aplastic anemia that is suspected to have an autoimmune pathogenesis (Schett et al., 2010).

     On the contrary, Levine and Erkan (2011) disagreed with the current study, as they reported leukocyte abnormalities in up to 75% of the patients in the study. Also, El-gendi et al. (2018) reported that that WBCs, MCV and MCH had no significant different between difference groups.

     In the present study, there was a statistically significant difference between studied groups as regard ALB/Creatinine ratio, SLE and RA groups, SLE and control groups. However, there was no statistical significant difference between RA and control groups with. These results were in agreement with Sui et al. (2014) who reported that those patients with inactive SLE nephritis had significantly higher 24h-protien in comparison to those without nephritis and the control group.

     In the current study, there were statistically significant difference between studied groups as regard C3, statistically significant differences between SLE and control groups with, and RA and control groups.

     These results were in agreement with the results of El-gendi et al. (2018) who reported that patients without SLE nephritis had significantly higher level of C3 and C4 in comparison to control group. There results were disagreed with Narayanan et al. (2010) who observed in their prospective study that 92.3% SLE patients had low C3 levels, and 84.6% had low C4 levels. Birmingham et al. (2010) demonstrated the poor clinical utility of serial serum C3 or C4 measurements alone to forecast or identify an SLE renal flare. The reasons for the discrepancies across studies are multifactorial including differences in study design, ethnicity, baseline clinical characteristics and renal parameters.

     In the present study, there were statistical significant relations between glucose intolerance and FBS, PPBS and HbA1C in SLE group, and RA group. These results were in agreement with Magadmi et al. (2010) who reported that SLE patients had significantly worsened insulin resistance than healthy control patients. Also, Gazareen et al. (2014) reported that, with respect to insulin sensitivity profile, SLE patients have significantly higher fasting insulin, HOMA IR, HOMA b-cell, and C-peptide than controls, and there is a positive correlation between IR and fasting glucose, HOMA b-cell, and c-peptide in SLE patients. This relationship is independent of age, sex, BMI, total cholesterol, LDL, and HDL. There was a statistically significant higher ESR and CRP in RA patients with IR, and there was positive correlation between IR and fasting insulin, ESR, and serum CRP. This was similar to what was reported by other investigators such as Gheita et al. (2012) who found that SLE patients had high HOMA IR and HOMA b-cell and are associated with increase in disease activity and damage. In contrast, Ormseth et al. (2012) found no statistically significant difference between SLE patients and controls with respect to HOMA IR.

     This did not agree with the studies by Karimi et al. (2011), and Stagakis et al. (2012), who found no statistically significant higher ESR and CRP in RA patients with and without IR depending on activity of disease.

 

CONCLUSION

     SLE and RA patients appeared to have higher incidence of glucose intolerance than normal subjects.

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  11. Karimi M, Mazloomzadeh S and Kafan S. (2011): The frequency of metabolic syndrome in women with rheumatoid arthritis and in controls. Int J Rheum Dis., 14:248–254.
  12. Levine AB and Erkan D. (2011): Clinical assessment and management of cytopenias in lupus patients. Curr Rheumatol Rep., 13(4): 291–9.
  13. Lozovoy MAB, Simão ANC and Hohmann MSN. (2011): Inflammatory biomarkers and oxidative stress measurements in patients with systemic lupus erythematosus with or without metabolic syndrome. Lupus, 11: 1356–1364.
  14. Magadmi ME, Ahmad Y and Turkie W. (2010): Hyperinsulinemia, insulin resistance, and circulating oxidized low density lipoprotein in women with systemic lupus erythematosus. J Rheumatol., 33: 50–56.
  15. Narayanan K, Marwaha V, Shanmuganandan K and Shankar S. (2010): Correlation between Systemic Lupus Erythematosus Disease Activity Index, C3, C4 and Anti-dsDNA Antibodies. Med J Armed Forces India, 66(2):102-107.
  16. Ormseth MJ, Swift LL and Fazio S. (2012): Free fatty acids are associated with metabolic syndrome and insulin resistance, but not inflammation in SLE patients. Lupus, 12:1–8.
  17. Rattarittamrong E, Eiamprapai P and Tantiworawit A. (2016): Clinical characteristics and long-term outcomes of warm-type autoimmune hemolytic anemia. Hematology, 21(6): 368–74.
  18. Schett G, Firbas U, Füreder W, Hiesberger H, Winkler S, Wachauer D, Köller M, Kapiotis S and Smolen J. (2010): Decreased serum erythropoietin and its relation to antierythropoietin antibodies in anaemia of systemic lupus erythematosus. Rheumatology (Oxford), 40:424-431.
  19. Seriolo B, Ferrone C and Cutolo M. (2010): Long term anti-tumor necrosis factoralpha treatment in patients with refractory rheumatoid arthritis: relationship between insulin resistance and disease activity. J Rheumatol., 35:355–357.
  20. Simard JF and Mittleman MA. (2011): Prevalent rheumatoid arthritis and diabetes among NHANES III participants aged 60 and older. Journal of Rheumatology, 34: 469–473.
  21. Solomon DH, Love TJ, Canning C and Schneeweiss S. (2010): Risk of diabetes among patients with rheumatoid arthritis, psoriatic arthritis and psoriasis. Annals of the Rheumatic Diseases, 69: 2114–2117.
  22. Stagakis I, Bertsias G, Karvounaris S, Kavousanaki M, Virla D, Raptopoulou A, Kardassis D, Boumpas DT and Sidiropoulos PI. (2012): Anti-tumor necrosis factor therapy improves insulin resistance, beta cell function and insulin signaling in active rheumatoid arthritis patients with high insulin resistance. Arthritis Res Ther., 14: 141-146.
  23. Sui M, Jia X, Yu C, Guo X, Liu X, Ji Y, Mu S, Wu H and Xie R. (2014): Relationship between hypoalbuminemia, hyperlipidemia and renal severity in patients with lupus nephritis: A prospective study. Centr. Eur. J. Immunol., 39 (2): 243-252.


قابلية إختلال السكر فى مرضى الروماتويد المفصلى والذئبة الحمراء

ربيع إسماعيل عيد، محمد نبيل رأفت، محمد حسن عطية حسن، أحمد على على عاصم

قسمي الباطنة العامة، الباثولوجيا الاكلينيكية، كلية الطب، جامعة الأزهر

E-mail: rabieismaeil2015@gmail.com

خلفية البحث: يعد قابلية اختلال السكر مساهماً مهماً في زيادة مخاطر القلب والأوعية الدموية المنسوبة إلى متلازمة التمثيل الغذائي، وهي مجموعة من عوامل الخطورة القلبية الوعائية التي تشمل السمنة المركزية، وخلل شحميات الدم، وارتفاع ضغط الدم، واستقلاب الجلوكوز المضطرب، في المرضى الذين يعانون من التهاب المفاصل الروماتويدي و الذئبة الحمراء.

الهدف من البحث: تقييم نسبة قابلية إختلال السكر في مرضى إلتهاب المفاصل الروماتويدي ومرضى الذئبة الحمراء.

المرضى وطرق البحث: الدراسة الحالية عبارة عن دراسة إستباقية أجريت على 90 شخصًا. تم إستقدام المرضى الخاضعين للدراسة من عيادة الباطنة العامة بمستشفى الحسين الجامعي خلال الفترة من يناير2020 إلى يناير 2021. تم تقسيم المرضى الى ثلاثة مجموعات: ثلاثون مريضا مصاب بالروماتويد المفصلى وثلاثون مريضا مصاب بالدئبة الحمراء وثلاثون شخص طبيعى وتم عمل الفحوصات ومقارنة المجموعات الثلاث.

نتائج البحث: كان هناك فرقا يعتد به إحصائيا بين المجموعات المدروسة فيما يتعلق بتقييم مستوى السكر في الدم (سكر صائم وسكر فاطر وسكر تراكمى)، وقابلية اختلال السكر، هيموجلوبين، سرعة الترسيب، نسبة البومين/كرياتنين، الاختبار التكميلى3في مرضى الذئبة الحمراء، كذلك هناك فرقا يعتد به احصائيا وقابلية اختلال السكر و (سكر صائم، سكر فاطر و سكر تراكمى) في مجموعة الروماتويد المفصلى، ولكن لا يوجد فرق إحصائي مهم بين المجموعات المدروسة فيما يتعلق البروتين المتفاعل سي و كرات الدم البيضاءوالصفائح الدموية و الاختبار التكميلى 4.

الاستنتاج: مرضى الروماتويد المفصلى والذئبة الحمراء يمتلكون معدلات أعلى لحدوث إختلال السكر من الاشخاص العاديين.

الكلمات الدالة: إختلال السكر، إلتهاب المفاصل الروماتويدي، الذئبة الحمراء الجهازية.

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