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Prevalence and Risk Factors of Renal Impairment among Rheumatoid Arthritis Patients Attending Outpatient Department of Tikur Anbessa Specialized Hospital

Jima B1, Dejene G2 and Hailemariam T3*

1Addis Ababa Health Bureau Public Health Research and Emergency Core Processes: Immuno hematology and Clinical Chemistry, Addis Ababa, Ethiopia

2JSI Research and Training Institutes, Universal Immunization Improving through Family Health services Monitoring & Evaluation and Learning Specialist, Hawassa, Ethiopia

3Department of Health Informatics, Hawassa College of Health Science, Hawassa, Ethiopia

*Corresponding Author:
Hailemariam T
Department of Health Informatics
Hawassa College of Health Science
Hawassa, Ethiopia
Tel: +251913305250
E-mail: [email protected]

Received date: August 22, 2016; Accepted date: December 21, 2016; Published date: December 28, 2016

Citation: Jima B, Dejene G, Hailemariam T (2016) Prevalence and Risk Factors of Renal Impairment among Rheumatoid Arthritis Patients Attending Outpatient Department of Tikur Anbessa Specialized Hospital. Intern Med 6:230. doi: 10.4172/2165-8048.1000230

Copyright: © 2016 Jima B, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Background: The global burden of chronic degenerative disease is increasing worldwide. Most developing countries have dual burden with infectious and non-infectious diseases. Kidney disease is a long term health condition and defined as the gradual loss of body, renal function and death over time. Renal abnormalities were quite prevalent in rheumatoid arthritis patients and there is a significant increase of renal derangement with duration of disease and severity of disease activity. Methods: A hospital based cross-sectional study was conducted. Blood sample was collected for assessment of urea and creatinine. Urine sample was also collected for protein and blood detection. Serum creatinine was analyzed by an automated biochemistry machine Mindray 200 BS. Urine protein and blood was detected by chemical test. Descriptive, bivariate and multivariate analyses were used to analyze the data. Odds ratio with 95%CI was estimated to assess the predictors of renal impairment. Result: Out of 219 rheumatoid arthritis patients, 49 (22.4%) had renal impairment. Serum creatinine level in mg/dl of the patients were with mean and standard deviation (SD) of (1.67 ± 0.47 SD) with adjusted odd ratio (AOR) and (95%CI):14.07 (5.09, 38.91), Mean (± SD) age of the participants was 43.82 (± 14.03) years and about 75.3% were females. Protienuria 44 (20.1%) with AOR (95%CI):1.93 (1.68, 5.58) and Body Mass Index (BMI) above 25 with AOR (95%CI): 0.1 (0.02, 0.45) shows significant association with the prevalence of renal impairment. Conclusion: The study revealed that the prevalence of renal impairment in patients’ with rheumatoid arthritis is high. Screening for renal impairment for patients with rheumatoid arthritis will be very helpful to peak kidney disease at earlier stage.


Cross sectional study; Rheumatoid arthritis; Prevalence; Renal impairment; Predictors; Bivariate and multivariate analyses


The global burden of chronic degenerative disease is increasing worldwide. Among those, kidney disease is an increasing global health problem [1]. Due to the fact that it is a silent condition and its prevalence is considered to be underestimating [2]. According to World Health Organization’s report, 2003, the prevalence of impaired kidney function was estimated to range between 10% to 20% of the adult population in most countries worldwide [3,4].

However, a recent study suggests that the incidence of kidney disease is increasing globally [5]. Chronic kidney disease is reported to be 3-4 times more common in Africa than in developed countries [6]. The incidence of chronic kidney disease in Ethiopia is rising because of increased risk factors such as rheumatoid arthritis, high blood pressure and diabetes mellitus [7,8].

It has been estimated that more than 500 million individuals globally have chronic kidney disease, defined by either kidney damage or glomerular filtration rate <60 ml/min/1.73 m2 [9]. The main epidemiologic significance of disease is due to asymptomatic chronic kidney disease patients in the early stages of the disease process. Renal abnormalities were quite prevalent in rheumatoid arthritis patients and there was significant increase of renal derangement with duration of disease and severity of disease activity [10]. The reported kidney disease prevalence in patients with rheumatoid arthritis ranges from 5% to 50% based on studies of different designs and the true prevalence of kidney disease remains unclear [11].

The prevalence of kidney disease is more in blacks than whites’ counterparts [12,13]. The higher prevalence among Africans has been attributed to genetic predisposition, low socio-economic status and inequities in access to healthcare [14]. As reports of many researches reveal, rheumatoid arthritis related kidney disease is one of the leading causes of chronic morbidity in the developed world, but little is known about the disease burden in Africa [15,16].

Renal disease is a common cause of mortality in patients with rheumatoid arthritis. This may be as a result of the disease itself, drugs used in treatment and other rheumatoid nephropathy [7]. Since rheumatoid arthritis patients have not experienced the same improvement in survival as the general population, the mortality gap between rheumatoid arthritis patients and individuals without rheumatoid arthritis has widened [17].

Rheumatoid arthritis is a heterogeneous and progressive autoimmune disease which affects all ethnic groups throughout the world [18]. The World Health Organization considers it as one of the diseases with the greatest impact on society [19]. And it is the 42nd highest contributor to global disability [20].

Rheumatoid arthritis is often seen as a minor health problem and has been neglected in research and resource allocation throughout Africa despite its potentially fatal systemic manifestations [21]. This is also true in Ethiopia, which implies that awareness creation on the disease burden and disease process is necessary.

The prevention and management of rheumatoid arthritis could help to reduce other related disease by reducing shared risk factors and prevalence of systemic manifestations like chronic kidney disease which is serious health problems but treatable disease if caught in the early stages [22].

If patients take the treatment without knowing that they have kidney disease, it causes series health conditions; such that early diagnosis is become vital. Some of the drugs used for treatment of rheumatoid arthritis have severe toxic effects on the kidney even in patients with only mild renal insufficiency and therefore they require some dosage adjustment [7]. Therefore, assessment of kidney function using different laboratory diagnosis system in patients with rheumatoid arthritis is necessary for appropriate choosing and dosing of drugs.

In general, the topic inevitably has value for clinical diagnosis and monitoring of rheumatoid arthritis patients with early or mild kidney progress to prevent further damage. Therefore, this study uses as baseline survey on the magnitude of renal dysfunction in rheumatoid arthritis patients, associated factors and informs on modes of intervention. Knowing the risk factor and creating awareness may also provide a means of optimizing care.

Therefore, this research would help in identifying key gaps and provide a good means of understanding the disease and the associated risk factors in the treatment courses.

Materials and Method

Study area and period

This study was conducted at Tikur Anbassa Teaching and Specialized Hospital which is located at Lideta sub city, Addis Ababa, Ethiopia. It is one of the largest general public hospitals under the Federal Ministry of Health located in Addis Ababa and also it is the training center for undergraduate and postgraduate medical students, dentists, nurses, pharmacists, laboratory technicians and others who shoulder the health problems of the community and the country at large. It also gives patient diagnostic service for many people in the community.

The hospital is selected as study site for it is the only specialized referral hospital in Addis Ababa involved in the diagnosis and treatment of RA patients. This cross sectional study was conducted for a period of 6 months from July 2015 to January 2016 study design and study period.

Study design and source population

Cross sectional study was conducted. All Patients with rheumatology case seen at the rheumatology clinic during the study period were used. Confirmed rheumatoid arthritis cases that have seen at Tikur Anbessa Specialised Hospital during the study period and having a baseline data.

Sample size and sampling procedures

The sample size is calculated based on single sample size estimation. The value of p is taken considering 95% confidence interval, 5% margin of error and; the value of p taken was 18% from the previous study conducted on prevalence of kidney disease on rheumatoid arthritis patients [23]. The sample size is calculated using the following standard formula.

The sample size n=z(α2)2p (1-p)/d2

Where n=sample size

z(α 2)2=At 95% confidence interval Z value (α=0.05)=1.96

p=Proportion of occurrence of the event to be studied

d=Margin of error at (5%)(0.05)

n= (1.96)2·0.18 (1-0.18)/(0.05)2


As computed above, the sample size for this study is 227. However, we were only able to obtain 219 samples in a given time frame. Consecutive sampling technique was employed to include study participants who meet the inclusion criteria during the study period.

Measurement and study variables

Independent variable: Independent variables include age, sex, weight, smoking, obesity, urine blood and medication use in the treatment course.

Dependent variables: Creatinine, urea, and estimated GFR (Glomerular Filtration Rate)

Data collection and quality control: Data collectors or nurses was identified, trained and informed to collect the data as per the prestructured questionnaire. The purpose of the study as well as any related harm and benefit was explained to the study participants accordingly. Demographic data and potential risk factor of rheumatoid arthritis like cigarette smoking, habit coincident remote site infections and other risk factors were recorded.

Blood sample: During the study, blood sample was collected by using sterile needle, taken carefully, from those patients that come to rheumatology clinic and screened for rheumatoid arthritis by physician. Cooler boxes with ice packs were used for temporary storage until the sample reach to laboratory. Samples were delivered to the laboratories at the end of the day’s collection. Analysis was done immediately after delivery.

Urine sample: A minimum of 10 ml of urine sample was collected by using sterile, capped urine collection. The urine sample was analyzed for protienuria and hematuria at the clinic by dipstick. Results obtained were recorded immediately during the study performed.

Transportation of specimens: Following collection from patients, specimens was transported carefully to clinical chemistry laboratory within 30 min.

Sample processing

Serum urea, creatinine was determined and finally estimated glomerular filtration was calculated using cockcroft gault formula and urine protein and blood was determined using urine strip method. Serum creatinine was analyzed in the renal unit laboratory using the Mindray 01 which is an automatic biochemistry analyzer and also urine analysis was performed by the principal investigator at the site of collection using the urine chemical test. It was assessed of with the parameters on a colored visual scale.

Creatinine determination

Method: Berthelote enzymatic colorimetric method

Reaction principle:


The intensity of the color formed is proportional to the urea concentration in the sample.

Estimation of GFR: Monitor GFR

Using cockcroft gault formula: Cockcroft gault formula: GFR (ml/ min)=k × (140-age) × body weight/SCr (in μmol/l). Where, k =1.04 (female) or 1.23 (male).

Kidney disease prevalence was estimated from apparent kidney damage and kidney function and categorized according to the NKF classification as follows [24].

Stage 1: GFR ≥ 90 ml/min: normal Renal Impairment.

Stage 2: GFR 60 ml/min to 89 ml/min: mild renal impairment.

Stage 3: GFR 30 ml/min to 59 ml/min: moderate renal impairment.

Stage 4: GFR 15 ml/min to 29 ml/min: severe renal impairment

Stage 5: GFR<15 ml/min: kidney failure.

Urinary protein and blood determination

Blood: This test is based on the peroxidase like activity of hemoglobin, which catalyzes the reaction of diisopropylbenzene dihydroperoxide and 3,3’,5,5’tetramethylbenzidine. The resulting color ranges from orange through green and very high levels of blood may cause the color development to continue to blue.

Protein: This test is based on the protein error of indicators principle. At a constant pH, the development of any green color is due to the presence of protein. Colors range from yellow for “Negative” through yellow green and green to green blue for “Positive” reactions.

Data quality was ensured through use of standardized data collection materials, pretesting of the questionnaires, proper training before the start of data collection and intensive supervision during data collection by the principal investigator. For laboratory analysis pre analytical, analytical and post analytical stages of quality assurance that is incorporated in standard operating procedures (SOPs) of the Tikur Anbessa clinical chemistry laboratory was strictly followed. In addition, well trained and experienced laboratory professionals were participate in the laboratory analysis procedure.

Data management and analysis procedures

Data entry and analysis was done using SPSS statistical software version [20]. The descriptive statistics was calculated & logistic regression analysis was done. Variables that show a significant association were selected for further analysis. In all cases P-value less than 0.05 was considered as statistically significant. The strength of the association was interpreted using an odds ratio in a 95% confidence interval. Finally, the results were presented using figures, and tables.

Ethical issues

This research project was approved by “Departmental Ethics and Research Committee” of the Department of Medical Laboratory Sciences, College of Health Science and School of Allied Health Science of Addis Ababa University. Permission was obtained from Tikur Anbessa hospital administrator. Informed verbal consent was obtained for each study subjects. Each respondent was informed about the objective of the study and assurance of confidentiality, risks and benefits. Only blood samples intended for study were drawn and thereafter discarded after analysis. The study results shall be disseminated to health care providers to aid in patient care.


Out of 227 sample size, 219 (96%) of respondents who had at least one year follow-up at rheumatoid clinic at Tikur Anbessa Specialized and Teaching Hospital were identified and participated in the study.

A total of 219 respondents were interviewed and among all, 83 (37.9%) of the respondents were in the age range 25 years to 39 years and 78 (35%) were in age range of 40 years to 59 years, while 36 (16.4%) were above 59 years and 22 (10%) were in the age range of 15 years to 24 years. The mean age of the respondents was 43.82 years with Standard deviation (SD) of 14.03. Majority of respondents were 123 (56.2%) from Amhara ethinic group.

Regarding education status, 50 (22.8%) were illiterates (unable to read and write), 53 (24.2%) have attended primary education, 60 (27.4%) were in secondary education, and 56 (25.6) have attended college or university level education (Table 1). Majority of the study participants 189 (86.3%) had belief that the cause of the disease were unknown. While others 30 (13.7%) had strong belief that the cause of the disease reported as cold, curse, some viral disease and others.

Variables   Frequency Percentage (%)
Age 15-24 22 10
25-39 83 37.9
40-59 78 35
>60 36 16.4
Marital status Un married 55  25.1
Married 120 54.8
Other* 44 20.1
Level of education Unable to read and write 50 22.8
Primary 53 24.2
Secondary 60 27.4
College/University 56 25.6
Sex of the respondent Female 165 75.3
Male 54 24.7
Alcohol Yes 53 24.2
No 124 56.2
Sometimes 42 19.2
Ethnicity Amhara 123 56.2
Oromo 53 24.2
Tigray 13 5.9
Others 30 13.7

Table 1: Socio demographic characteristics of respondents, Addis Ababa, 2016.

Vast majority of the respondents 128 (58.4%), 54 (24.7%) and 37 (16.9%) live with the disease for the last one to five years, 6 years to 10 years and greater than 10 years respectively. The study revealed that 43 (19.6%) respondents have been reported RA in the family history (Table 2). As presented in the Table 3, Majority of the respondents 90 (41.1%) and 72 (32.9%) have greater than 90 mL/min and 60 mL/min to 90 mL/min GFR result.

Variables Frequency Percentage
Perception on the cause of the disease    
Unknown 189 86.3
Other cause 30 13.7
Having RA family history    
Yes 43 19.6
No 176 80.4
Smoking history    
Yes 26 11.9
No 193 88.1
Having regular exercise    
Yes 23 10.5
No 159 72.6
Sometimes 37 16.9
Work history of the respondent    
Government 62 28.3
Farmer 15 6.8
Housewife 58 26.6
Student 10 4.6
House made 6 2.7
Private 32 14.6
No work 36 16.4
Disease duration    
1-5years 128 58.4
6-10 years 54 24.7
>10 years 37 16.9
Respondent income    
Dependent 67 30.6
<1000birr 63 28.8
1001-3000birr 63 28.8
>3000birr 26 11.9

Table 2: Past history and clinical finding of the respondents, Addis Ababa, January 2016.

Variables Frequency Percentage (%)
GFR result in ml/min    
<15 3 1.4
15-29 8 3.7
30-59 38 17.4
60-90 80 36.6
>90 90 41.1
Abnormal 72 32.9
Normal 146 67.1
>50 4 1.4
<10 24 11
10-50 191 87
Urine protein    
≥1+ 44 20.1
<1 175 79.9
≥1+ 9 4.1
<1 210 95.5

Table 3: Laboratory and clinical finding of the respondents, Addis Ababa, January 2016.

GFR CATAGORIES(ml/min) Description Percentage (%)
Stage 1 (GFR ≥ 90 ml/min) Normal renal impairment 41.1
Stage2 (GFR 60ml/min to 89 ml/min) Mildrenal impairment 36.6
Stage 3 (GFR 30ml/min to 59 ml/min) Moderate renal impairment 17.4
Stage4 (GFR 15ml/min to 29ml/min) Severe renal impairment 3.7
Stage5 (GFR<15 ml/min) Kidney failure 1.4

Table 4: Kidney disease classification and result based on NKF classification, at TikurAnbessaAnbessa Hospital,Addis Ababa,January2016.

Variables Frequency Percentage
Types of medication used in the management
Prediensolon,methotriexate,indomethacin and others* 89 40.6
Prediensolon 27 12.3
Indomethacin 30 13.7
OtherNSAID+Prediensolon 54 24.7
Prediesolon and methotriexate 6 2.7
Methotriexate 13 5.9
Duration of medication taken    
<10years 200 91.3
>10years 19 8.7

Table 5: Drug used for RA treatment, at TikurAnbessa Specialized Hospital,Addis Ababa,January2016.

Among all subjects, 175 (79.9%) and 146 (67.1%) have normal urine protein and creatinine level which is less than one respectively. Majority 101 (46.1%) and 17 (7.8%) of the respondents have been developed deformity and swelling, while other have been reported normal body functions.

Most of the respondents 200 (91.3%), had been on taking medication less than ten years while other taking different medications above 10 years. The frequency of prediensolone, methotreixate, indomethacine and others is 89 (40.6%).

Multivariate logistic regression analysis was carried out by using a model of Hosmer-lemeshow goodness of fit test and enter modal to determine the most important statistically significant variables to look for strength of association as shown (Table 6). Result from bivariate analysis revealed that renal impairment associated with age of the study participant, sex, type of medication taking, duration of medication taken, urine protein and BMI significantly.

Factors Renal Impairment Crude OR Adjusted OR
  eGFR eGFR Pvalue  OR 95%CI P-value OR 95%CI
ml/min ml/min
n<60 n>60
>59 1 21 0.02 7.14(1.45,35.29) 0.02** 24.15(2.09,279)
40-59 16 67 0.01 4.23(1.72,10.41) 0.05** 3.22(1.04,10.24)
25-39 16 62 0.12 1.94 (0.85,4.45) 0.02** 3.97(1.22,12.94)
18-24 16 20 1      
Female 44 121 0.01 3.56 (1.33,9.52) *** ***4
Male 5 49 1      
No.of medication type ≥2 medication 43 89 0 6.52(2.64,12.05) 0.00* 8.16(2.38,28.05)
Only one 6 81 1      
Duration of medication            
>10 10 9 0 4.20(2.01,8.57) *** ***
<10 39 161        
Urine protein            
≥1+ 20 24 0 4.20(2.01,8.57) 0.02* 1.93(1.68,5.53)
<1 29 146 1      
<18.5 20 31 1      
 18.5-24.5 24 108 0.57 0.73(0.08,0.75) *** ***
>25 5 31 0.01 0.25(0.26,2.06) 0.03* 0.1(0.02,0.45)

Table 6 : Bivariate and multivariate analysis of factors associated with renal impairment on RA patients, at TikurAnbassa Teaching and Specialized Hospital, January 2016, Addis Ababa.

Out of the total covariate shows significant association in the bivariate, age of the study participant, sex, type of medication taking, duration of medication taken, creatinine level, urine protein and body mass index were significantly associated with renal impairment. But sex and duration of medication taken have no significant association in multivariate analysis.


Figure 1: Prevalence of renal impairment among RA patients, Addis Ababa, January 2016. The prevalence of 22.37% with mean and SD [1.78 ± 0.418 SD].

Age of rheumatoid arthritis patient was one of strong factors associated with renal impairment. The study shows that older age greater 59 years old AOR (95%CI): 24.15(2.09, 279) p-value 0.02, age 40-59 AOR (95%CI): 3.22 (1.01, 10,234), age 25-39 AOR (95%CI): 3.97 (1.22, 12,936) were more likely developed renal impairment than younger (15-24) respectively.

Patients who have taken more than two type of medications had 8.16 times more likely to develop renal impairment than who has taken one type of non-steroidal anti-inflammatory drugs or methetroxin or predinsolon drugs or other steroidal drugs AOR (95%CI): 8.16 (2.38, 28.05).

The level of urine protein as determined by dipstick was associated with the degree of renal impairment. Urine protein level greater than one AOR (95%CI): 1.93 (1.68, 5, 53) were more likely developed kidney disease than protein level less than one. Body mass index of rheumatoid arthritis patient was one of strong factors associated with renal impairment. This study shows that those who have body mass index greater 25 are AOR (95%CI): 0.01 (0.02, 0.45), p-value of 0.03 less likely develops renal impairment.


Prevalence value of 22.4% renal impairment was observed in this study. This is higher than the study conducted before which was 18% [25] and 12.75% in Europe [26]. However, it is a bit lower than similar study conducted in Kenya that was resulted 28% [1]. Majority of the study participants’ age distribution in this study were older than 40 years of age 114 (52%) with mean age 43.82 years and standard deviation of 14.03 which is significantly lower than related studies conducted abroad. The study subjects considered in our study were younger than subjects participated in related studies in Kenya, France, USA and England with a mean age of 48.7 years, 55.2 years, 56 years and 61.6 years respectively [26-28] and nearly one fourth, 91 (41.6%) have been living with RA for the last 6 years to 40 years.

The higher prevalence of kidney disease among Africans has been attributed to genetic predisposition, low socio-economic status and inequities in access to health care [14]. This is possibly supported by majority 130 (59.4%) of study participants have no income or less than 1000 birr per month. Duration of disease and first visit of modern health care registered with mean of 7.32 and 1.38 respectively. This shows that health seeking behavior of study participant significantly varies from the Kenyan study [1].

High incidence of kidney disease in our study might be explained by late coming of patients to modern health care treatment after attending traditional healer, spiritual care, habitual consumption of analgesics and disease progression. The finding of this research revealed that age of study participant was one of strong predictors associated with kidney disease. This is consistent with studies in [1,26]. And the older the patient the significant is the risk propensity of kidney disease than younger age. This might possibly be explained by the fact that old age is a known independent risk factor for kidney disease. As age increases there is a gradual decrement in the nephrons number and associated decline in glomerular filtration rate.

The average rheumatoid arthritis patient has approximately 1.6 comorbidities and the number increases with the patient's age may be expected more. And a variety of renal disorders can occur in patients with rheumatoid arthritis due to the underlying disease to drugs used to treat the inflammatory process and to concurrent renal disease unrelated to rheumatoid arthritis which is more likely in elderly patients [17].

Drug induced protein urea was associated with age over 50 years and elevation of C-reactive protein levels. Even though we did not include hypertension and diabetic mellitus, other studies show that the prevalence of hypertension and diabetic mellitus among rheumatoid arthritis patients are higher as compared to age and sex matched controls a finding in the general population. The study shows that sex of study participant was not significantly associated in multivariate analysis. This is against study in Helsinki and Russia. This might be possible explained by age of female study participant even if the incidence of rheumatoid arthritis was common among female sex. The prevalence of kidney disease in Helsinki significantly associated with the problem than this study. This might be because of the fact that the mean age of study participants in Helsinki was higher than this study. The mean age of this study is less than other similar studies done [1, 27].

Duration of medication taken was significant in the bivariate analysis. However, it was not as such significant in the multivariate analysis but patient who have taken more than two type of medication were more likely to develop renal impairment. This is inconsistent with Kenyan study [1]. In our study, rheumatoid arthritis patients who have been taking combination of three type medication like that of predinsolon, methotrixate, indomethaxin and other were significantly associated with renal impairment.

Use of either one or combination of two predinsolon, methotrixate, non-steroidal anti-inflammatory drugs were not correlated with renal impairment. And lack of association might be explained due to drug compliance by our study population although this was not assessed by this study [1]. Since this cross sectional study affected by chicken-egg dilemma or can't establish cause effect relationships we are not able to establish cause of renal impairment among the drugs.

The association might be confounded by habitual analgesic intake for management of pain which is un-prescribed by clinician [28]. This is true in all countryside of Ethiopia and it is also supported by different authors who have cited the habitual consumption of analgesics or analgesic abuse as contributing to the increasing nephrotoxicity contribute to high prevalence of kidney disease.

Finally, other possible general explanation might be the attributed by other drugs use manage for co-morbidity in rheumatoid arthritis patients. More number of drugs shows that disease severity in rheumatoid arthritis was uncontrolled disease activity. The fact that a given patient uses poly-pharmacy could indicate that the disease is uncontrolled or the time of the drug combination is delayed and enhanced disease activity and renal injury. The blood urea was 28 (12.8%) and it was not significantly associated with renal impairment. Concomitant elevations of blood urea imply renal excretory failure but only at an advanced stage of kidney damage. Hematuria, proteinuria and creatinine are sign of abnormal clinical findings. The clinical finding shows that hematuria and proteinurea was 9 (4.1%) and 44 (20.1%) respectively and proteinuria and hematuria, as detected by urine dipstick analysis, is suggestive of glomerulonephritis and massive proteinuria is a hallmark of membranous lupus nephritis, amyloid-A amyloidosis or certain drug toxicities [28].

Abnormal serum creatinine level of the study was 72 (32.9%). Most studies show that creatinine is not credible measurement. However, the use of serum concentration of creatinine as an index for the glomerular filtration rate [24]. Urine protein level was one of factors correlated with renal impairment in this study. This is similarly to study consucted in South Africa and Finland [7]. Macro protein in the urine is one of sign glomerular injury according to different studies. Production of protein in the urine (protienuria) might be explained by systemic rheumatoid arthritis related vacuities, glomerular injury and micro vascular injury related to co-morbid chronic medical conditions. So, the longer the duration of protienuria is the more the kidney disease progression [24].

High value body mass index is one of basic parameter used to measure risk chronic degenerative disease like hypertension, diabetic mellitus and then consequently chronic kidney disease. But according to this study, participant with body mass index greater than 25 were less likely develop renal impairment. It was found to be statistically significantly associated with renal impairment in this study. This is inconsistent with study in South Africa. This is possibly explained by the inverse relationship of body mass index and eGFR calculation. Even if the association of body mass index and renal impairment are statistically significant in this study it is not enough to establish causeeffect relationship and biological plausibility.


This study indicates that the prevalence of renal impairment among study participants was high. Though protein-urea can be from different causes, it is a marker of progression in renal impairment.

Old age is a known independent risk factor for renal impairment irrespective of the underlying diseases. As age increases there is a gradual decrement in the nephrons number and associated decline in glomerular filtration rate.

The three drugs listed above, protein-urea and body mass index were found to be significantly associated with renal impairment. This still implies that patients with rheumatoid arthritis require screening for kidney disease, regular monitoring of progression and initiation of appropriate management especially with long-term follow up.


The authors would like to thank Addis Ababa University School of Allied Health Sciences and Department of Medical Laboratory Sciences for covering the expenses needed during the thesis work and for the academic support in the research process. We also would like to thank all friends and colleagues for their unreserved support during this study and Tikur Anbessa Hospital Laboratory staffs and all nurses at Rheumatology Clinic.


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