|Year : 2019 | Volume
| Issue : 6 | Page : 1190-1200
|Chronic kidney disease among human immunodeficiency virus positive patients on antiretroviral therapy in sub-Saharan Africa: A systematic review and meta-analysis
Habtamu Wondifraw Baynes1, Markos Negash2, Demeke Geremew2, Zegeye Getaneh3
1 Department of Clinical Chemistry, School of Biomedical and Laboratory Sciences, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
2 Department of Immunology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
3 Department of Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia
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|Date of Submission||02-Jan-2019|
|Date of Decision||08-Mar-2019|
|Date of Acceptance||12-Mar-2019|
|Date of Web Publication||9-Jan-2020|
| Abstract|| |
Human immunodeficiency virus (HIV)-infected patients are at risk for renal disease as a consequence of complications of antiretroviral treatment. Particularly, the complication of kidney disease is high in patients who switched to Tenofovir Disoproxil Fumarate. The treatment is associated with nephrotoxicity, decrease in glomerular filtration rate, leading to kidney disease. This review focused on assessing the effect of antiretroviral therapy (ART) on kidney function among HIV-positive patients. Initially, the study protocol was registered on Prospero and given a unique identification number of CRD42018087686. We then conducted a systematic search of PubMed, Google Scholar, the Cochrane library, and Google from 2008 to September 2018. We found 742 study results eligible for this review. After stringent filtration mechanism, 15 qualified studies were used for systematic review and meta-analysis process. Cross-sectional, cohort, randomized controlled trials, and prospective studies were eligible for inclusion in the study. The overall pooled prevalence found in this meta-analysis was 6.42% with high statistical heterogeneity (I2 = 96.7%). The highest subgroup prevalence was reported from Ghana, with subgroup prevalence of 13.65% without statistical heterogeneity (I2 = 0.0%). Majority of chronic kidney disease (CKD) was in stage 3 with subgroup prevalence of 6.78% and tolerable statistical heterogeneity (I2 = 66.7%). There was high pooled prevalence of CKD among HIV-positive patients on ART in Sub-Saharan Africa. The highest subgroup prevalence was reported from Ghana. Majority of CKD was reported in stage 3.
|How to cite this article:|
Baynes HW, Negash M, Geremew D, Getaneh Z. Chronic kidney disease among human immunodeficiency virus positive patients on antiretroviral therapy in sub-Saharan Africa: A systematic review and meta-analysis. Saudi J Kidney Dis Transpl 2019;30:1190-200
|How to cite this URL:|
Baynes HW, Negash M, Geremew D, Getaneh Z. Chronic kidney disease among human immunodeficiency virus positive patients on antiretroviral therapy in sub-Saharan Africa: A systematic review and meta-analysis. Saudi J Kidney Dis Transpl [serial online] 2019 [cited 2020 Oct 31];30:1190-200. Available from: https://www.sjkdt.org/text.asp?2019/30/6/1190/275462
| Introduction|| |
Chronic kidney disease (CKD) is the impairment of kidney function which persists for more than three months. It is becoming a major health problem as current researches indicating it as being underdiagnosed and undertreated., In 2017, an estimated 36.9 million people were living with human immunodeficiency virus (HIV). The vast majority of people living with HIV are located in low-and middle-income countries, with an estimated 66% (24.4 million) living in sub-Saharan Africa. Among this group, 19.6 million are living in East and Southern Africa. Of all persons living with HIV, 59% (44%-73%) had received antiretroviral therapy (ART) in 2017. In the WHO African Region, 60% (45%-73%)] of people living with HIV were able to access life-saving medicines., The successful rollout of ART has resulted in the increased life of HIV-infected patients and decreased HIV-related mortality and morbidity. On the other hand, HIV-infected patients are at risk of developing comorbidities since HIV decreases the immune status of the patients which exposes them to different coinfections and, due to ART that impairs the normal metabolism process. These HIV/AIDS-infected patients nowadays suffer from comorbidities such as heart disease, diabetes, stroke, kidney, and liver disease, which are found highly prevalent and lead to complications and then if untreated results in death. Particularly, HIV-infected patients are likely to develop kidney disease five times as compared to noninfected ones. Inevitable age-related degenerative changes (possibly accelerated in HIV infection), cumulative exposure to ART drug toxicities, effects of ongoing inflammation, progressive immune dysfunction, and long-term infection by the virus itself are postulated to drive these noncommunicable diseases in HIV., Particularly, the complication of kidney disease is increased in patients switched to Tenofovir Disoproxil Fumarate. The treatment is associated with nephro-toxicity, decrease in glomerular filtration rate finally leading to kidney disease., Different studies from sub-Saharan Africa showed that there was a high prevalence of ART-associated kidney impairment in HIV-infected patients. People living in low-income countries, particularly in sub-Saharan Africa, estimated more than 70% for end-stage renal disease as of 2030., This estimation is from the view of the previous baseline point, that the global prevalence of maintenance dialysis patients has doubled since 1990. On the other hand, renal transplantation has been performed in 18 million people worldwide by 2004 and <5% of the population from sub-Saharan Africa have access to it., Because ART is massively used in developing countries, the status in Africa should be investigated in terms of how to use, the impact and attitude toward ART., Therefore, this review tried to see the burden of CKD on HIV-positive patients taking ART in sub-Saharan Africa.
| Methods|| |
Search strategy and selection criteria
We searched for published articles after registering on Prospero and obtaining a unique identification number of CRD42018087686. The data were extracted by following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We searched using PubMed, Google Scholar, the Cochrane library, and Google for studies published on CKD among HIV patients who took ART in Sub-Saharan Africa. Search for studies for this systematic review and meta-analysis was limited to studies conducted on human subjects and published in English up to September 30, 2018. We used the following search engines from PubMed “[ART (MeSH Terms) AND HIV patients (MeSH Terms) OR CKD (MeSH Terms) OR kidney failure (MeSH Terms) OR chronic kidney failure (MeSH Terms) AND Sub-Saharan Africa (MeSH Terms)].” The full version of data extraction method is presented in [Figure 1].
|Figure 1: Flow chart of the steps of the articles selection mechanism based on the objective of the review process.|
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Two reviewers assessed the articles independently for eligibility to the study. Consultation to the third person was also applied for disagreements. Titles, abstracts, and full documents were screened for eligibility using prior defined data extraction tool. The type of participants (human or animal), outcome of the study, study design, and country where the study was conducted were used as eligibility criteria of published articles for this systematic review and meta-analysis. Pharmacokinetics studies, pilot studies, reviews, and case reports were excluded from this review. Published studies that used study design of cross-sectional, cohort, randomized controlled trials, and prospective were recruited to this systematic review and meta-analysis. The published articles that estimated the estimated glomerular filtration rate (eGFR) using Modification of Diet in Renal Disease (MDRD), CKD Epidemiology Collaboration (CKD-EPI) and Cockcroft Gault (CG), reported in prevalence were also recruited to the review.
Quality assessment and data extraction
The quality of included articles was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. We assessed the feasibility between the outcome variables in each study based on the variables identified (year, design of the study, age of participants, methods of measurement, and cutoff values used). Two reviewers independently extracted the studies based on the preformulated extraction tool. The other two reviewers checked the extracted data for their accuracy. Data collected from each published study included the following: the authors involved in the study, year of study, country where the study conducted, study design, age in mean/median of the participants, method used for eGFR estimation, prevalence of CKD, and distribution of CKD in stages were gathered from each published study. CKD was defined by either kidney damage or GFR <60 mL/min/ 1.73 m2 for ≥3 months, regardless of the cause. CKD stages were categorized based on the classification system established by the National Kidney Foundation – Kidney Disease Outcomes Quality Initiative classification.
| Statistical Analysis|| |
The extracted data from published studies were entered into Microsoft Excel and transferred to STATA version 11 (StataCorp LLC, Texas, USA) for analysis. Statistical heterogeneity between published studies was calculated using the index of heterogeneity (I) statistics. i = 25%, 50%, and 75% are assumed to represent low, medium, and high heterogeneity, respectively. The individual prevalence, the pooled prevalence and the subgroup prevalence as a weighted mean among all the study groups was estimated. Subgroup analysis was made between countries to decrease the risk of heterogeneity. Since there was a difference between studies, the combined results of the random effect model were used. The sensitivity analysis was also performed for the effect of each study on the overall prevalence. The risk of bias between studies was also evaluated using eggers test.
| Results|| |
Quantity of the articles available
We found a total of 738 results from PubMed and four studies from other sources with a total of 742 screened for eligibility in this review. On further scrutiny, 703 articles were excluded based on their unrelated title. Thus, 39 studies were further screened for their meeting of the target of this review, 19 studies were rejected following which, 20 studies were left. After following the stringent filtration mechanism, 15 qualified articles were included for systematic review and meta-analysis process [Figure 1].
Fifteen studies were included in the meta-analysis process. Of these, seven studies were cross-sectional,,,,,, and the remaining eight were performed by cohort study design.,,,,,,, Nine studies estimated the eGFR and CKD by using MDRD method of estimation,,,,,,,, two studies used the CG method of estimation, and the remaining three studies used CKD-EPI estimation method.,,,
The published studies had a varied number of participants of which Mulenga et al, Sarfo et al, Kalayjian et al, De Waal et al, and Deckert et al, conducted their studies with large number of study participants, in decreasing order. Owiredu et al and Peck et al performed their study with small number of participants. Some of the studies reported the age of participants by mean ± standard deviation (SD) while others used median. The studies reported the participants’ age by mean (±SD), which ranged from 33.13 (±12.3) to 41.4 (±9.2) years,,,, and in the studies reporting median age, it ranged from 33 (2839) to 40.1 (33–46.5) years.,,,,,,,,, [Table 1] and [Figure 2].
|Table 1: Characteristics of the study participants included in the systematic review and meta-analysis from studies in sub-Saharan Africa.|
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|Figure 2: Subgroup analysis that shows the pooled sample size of the studies derived from categories of different authors in sub-Saharan Africa.|
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The overall pooled prevalence of this review was 6.42%, 95% confidence interval (CI) (5.2, 7.59 mL/min/1.73 m2) with heterogeneity of (I2 = 97.6 %). Two studies that were performed in Ethiopia had subgroup prevalence of 9.53%, 95% CI (5.61, 13.44 mL/min/1.73 m2). The statistical heterogeneity of this subgroup was low (I2 = 57%). Another two studies that were performed in Ghana had 13.65% subgroup prevalence, 95% CI (12.47, 14.82) with heterogeneity of (I2 = 00%). The remaining three studies and seven other studies were conducted in South Africa and Tanzania, respectively and had high statistical heterogeneity [Figure 3].
|Figure 3: Subgroup analysis of the pooled prevalence of CKD between countries in sub-Saharan Africa.|
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The overall prevalence of CKD stage 3 was 6.78 %, 95% CI % (3.58, 9.97) and (I2 = 66.7%), stage 4, it was 0.69%, 95% CI (0.002, 1.36) and (I2 = 29.5%) and stage 5 with 95% CI (-0.23, 1.55) and (I2 = 00%) [Figure 4].
|Figure 4: The pooled prevalence of chronic kidney disease among the different stages of kidney disease. The odds of stages were calculated by dividing positives in each stage by sum of stages.|
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In the 15 studies involved, the CI did not lie within the pooled CI; therefore, the influential ability of each study over the total prevalence of CKD is minimal. The prevalence and confidence interval ranged from 5.1159449 (4.200563, 6.0313263) to 7.5550871 (5.2209311, 9.8892431) [Table 2]. There was no significant bias among the articles with a variable number of sample sizes with metabias result of coefficient = 0.598 and P = 0.155. The funnel plot results of the articles showed that most of the articles lied on top of the funnel plot which indicates that the influential articles had a high probability of publishing, while some with small sample size articles were in the bottom of the right side from symmetrical line, indicating subjective judgment and presence of bias [Figure 5].
|Table 2: Characterizing the effect of omitting each article over the pooled prevalence.|
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|Figure 5: Funnel plot results of the articles. As shown above, most of the articles lied on top of the funnel plot which indicates the influential articles have a high probability of publishing. However, articles with small sample size were at the bottom of the right side from symmetrical line, indicating subjective judgment presence of bias. Unfortunately, the meta-bias analysis shows as there was no bias (coefficient = 0.598 and P = 0.155).|
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| Discussion|| |
CKD is common in Africa, particularly in sub-Saharan Africa and cause high morbidity and mortality. The current systematic review tries to see the burden of CKD among HIV-infected individuals who are active with different anti-retroviral regimens. As indicated from 15 studies included in this review and meta-analysis the overall pooled prevalence of CKD was 6.42% with a CI of (5.25, 7.59). This finding was in line with the systematic review and meta-analysis done on HIV patients globally which had pooled prevalence of (6.4%) with MDRD estimation method. The prevalence in the current review was comparable with the study conducted among HIV patients on ART in France; using large scale study with sample size of 7378 showed that 349 (4.73%) had CKD. The prevalence in the current review was slightly lower than the study from America, which was a large scale cohort study involving 16,405 participants that took ART and, a systematic review performed on HIV patients involving 43,114 participants of which 8.5% and 7.3% had CKD, respectively., On the other hand, it was higher than the study from the Netherlands (2.3%) involving 16,836 participants that took ART.
The studies included in this review had prevalence ranging from 1.2% from Tanzania to 18.7% from Benin. The difference in prevalence from article to article may be challenged with limitation of CKD estimation methods as they are confronted with different variables for eGFR equation models.
Subgroup analysis was performed for this review using models of eGFR estimation (MDRD, CKD-EPI, or CG) and showed 7.92%, 3.1%, and 13.2% prevalence rates, respectively. This finding was comparable with a systematic review done globally which had a prevalence of 6.4%, 4.8%, and 13.3 % for MDRD, CKD-EPI, and CG methods, respectively. Since there was high heterogeneity with in all of the above models (I2 = 98.4%, 72.1 % and 94.9 %) for MDRD, CKD-EPI, and CG, respectively, we attempted to analyze the data using study methods (designs) of original articles. Based on the analysis, the heterogeneity ( = 94.6%, 98.5%) for cross-sectional and cohort study designs, respectively, showed high variability. The possible cause of high heterogeneity between study designs might be the variation in outcome between cross-sectional and cohort study design. In our study, further subgroup analysis was performed between countries where the studies had been conducted. We found tolerable heterogeneity which indicates that countries are not the possible source of heterogeneity. The studies from Ethiopia showed subgroup prevalence of 9.53%, 95% CI (5.61, 13.44) and tolerable heterogeneity (I2 = 57%, P = 0.127). There was no heterogeneity between studies from Ghana (I2 = 00%) with subgroup 13.65%, 95% CI (12.47, 14.82). However, studies from S.Africa and Tanzania showed high heterogeneity (I2 = 89.8%, 96.1%), respectively.
CKD was defined by GFR <60 mL/min/1.73 m2 for ≥3 months, regardless of the cause and the stages were categorized based on the classification system established by the National Kidney Foundation -Kidney Disease Outcomes Quality Initiative classification as stages of 3, 4, and 5. For the meta-analysis between stages, the study by Kalayjian et al, did not classify CKD into stages and it was excluded for stage analysis. As a result, the subgroup analysis for stages of CKD in the current meta-analysis was made only using 14 articles. Thus, on the bases of sub-group analysis, there was low heterogeneity among all stages. Majority (thirteen) of the articles had CKD in Stage 3, with a prevalence of 6.78%, 95% CI (3.58, 9.97), and tolerable heterogeneity (I2 = 66.7%). It indicates that most of the patients did not develop complex kidney disease, and if well managed, the patients can have a probability of cure. The subgroup prevalence in this stage was comparable to the large scale cohort study performed in America (5.9%) using 16,405 participants that took ART. On the other hand, seven studies had CKD in stage 4 with prevalence of 0.69%, 95% CI (0.02, 1.36) and low heterogeneity (I2 = 29.1%), which is in line with the study of Choi et al. Three studies had CKD in stage 5 with prevalence of 0.66%, 95%CI (-0.23, 1.55) and there was no heterogeneity between them (I2 = 0.0%). The sub-group prevalence in this stage was lower than the study from America, where, 4.9% had CKD stage 5. Therefore, the staging of CKD is not the cause of heterogeneity, and hence, it is important to see the risk of CKD by categorizing among the different stages.
In general, there was no single influential study on the overall prevalence of CKD. A study which had a slightly greater effect on the overall prevalence of CKD was performed by Mulenga et al and De Waal et al. Omitting this article from the review process resulted in 7.55% pooled prevalence, which was higher than the 6.42% prevalence if they were included in the review (6.42%). On the other hand, the study by Sarfo et al, resulted in the decrement of the total prevalence. Since this study had a higher prevalence by itself, omitting it resulted in the dropping of the overall prevalence (5.11%) as compared to its inclusion to the review.
| Conclusion|| |
The pooled prevalence of CKD among HIV positive patients on ART in Sub-Saharan Africa was relatively high (6.42%). The highest subgroup prevalence was reported from Ghana (13.65%) with no statistical heterogeneity (I2 = 0.0%). Majority of CKD was reported in stage 3 with subgroup prevalence of 6.78% and tolerable statistical heterogeneity (I2 = 66.7%). There was high kidney disease in association with ART.
Conflict of interest: None declared.
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Habtamu Wondifraw Baynes
Department of Clinical Chemistry, School of Biomedical and Laboratory Sciences, College of Medicine and Health Science, University of Gondar, Gondar
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
[Table 1], [Table 2]
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