Abstract
Background
Chronic kidney disease (CKD) is a common condition among people living with HIV worldwide, but it is more common in patients from Africa. Both opportunistic infections and chronic illnesses are responsible for a large proportion of people living with HIV in low-resource settings like Ethiopia, which are linked to higher rates of morbidity and mortality. Further, as CKD is acknowledged as a major global public health issue affecting productivity, health, and healthcare costs, the goal of this systematic review and meta-analysis was to ascertain the pooled prevalence of CKD among people living with HIV in Ethiopia.
Methods
The Preferred Reporting Items for Systematic Reviews and Meta-Analysis criteria were followed by us when we carried out a systematic review and meta-analysis. Electronic databases like PubMed, Google Scholar, African Journal Online, Science Direct, Embase, Research Gate, Scopus, and Web of Sciences were searched in order to find pertinent articles. Domain-based assessment was used to evaluate the listed studies' quality. Stata version 14.0 software was used to conduct the statistical analysis. We used the Cochran's Q test and I2 statistics to assess heterogeneity. Using Egger's test and a funnel plot analysis, publication bias was evaluated. Using a random effect model, the pooled prevalence was calculated. Sub-group and sensitivity studies were also carried out.
Results
This systematic review and meta-analysis included 12 articles from Ethiopia, and 3364 People living with HIV were included. The overall pooled prevalence of chronic kidney disease (CKD) among People living with HIV in Ethiopia was 18.10% (95% CI: 14.17–22.03). According to the CKD calculation, the pooled prevalence of CKD was 18.06 (95% CI: 10.62–25.49) by using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula and 18.38 (95% CI: 15.75–21.02) by using the Modification of Diet in Renal Diseases (MDRD) formula. Using random-effect model, the I2 test result showed high heterogeneity I2 = 89.7% and P < 0.001. Additionally, Egger’s test of publication bias P-value was 0.017.
Conclusion
People living with HIV had a high prevalence of CKD, according to this systematic review and meta-analysis. Consequently, frequent CKD diagnosis at baseline, antiretroviral therapy follow-up and screening improves the quality of life for People living with HIV. Systematic review registration: PROSPERO (2023: CRD42023431245).
Keywords: Chronic kidney disease, Ethiopia, Meta-analysis, People living with HIV, Prevalence, Systematic review
Introduction
Chronic kidney disease (CKD) is a growing public health concern on a global scale. Its characteristic features include albuminuria and a glomerular filtration rate (GFR) of 60 mL/min/1.73 m5 for at least three months [1]. From 2015 to 2030, it is estimated that approximately 4.9 to 7.1 million people will need renal replacement therapy due to end-stage kidney disease (ESKD). Additionally, the global prevalence of CKD is projected to be around 13.4%, with a range between 11.7% and 15.1% [2]. In 2016, an estimated 36.7 million people worldwide were living with HIV [3]. CKD is prevalent in Africa, notably elevating the rates of illness and death, especially in sub-Saharan regions. A recent meta-analysis focusing on sub-Saharan Africa revealed that 6.42% of People living with HIV also suffered from CKD, with stage 3 CKD representing the largest proportion of these cases [4].
Currently, people living with HIV are often burdened by additional health issues like heart disease, diabetes, strokes, and diseases affecting the kidneys and liver [5]. These comorbidities are increasingly common and can lead to serious complications. If not addressed, they may ultimately result in fatal outcomes [6, 7] people living with HIV have a significantly higher risk of developing kidney disease, with studies showing they are five times more likely to experience this condition than those who are not infected [8]. According to estimates, there were 722,248 HIV infections among Ethiopian adults in 2017, up 3,748 from 2016 [9]. Antiretroviral therapy has been extensively utilized to enhance the life expectancy of individual living with HIV [10].
A decline in renal function has been observed in patients undergoing treatment for HIV/AIDS, particularly with the use of tenofovir disoproxil fumarate (TDF), as highlighted by the World Health Organization [11]. This medication is linked to nephrotoxicity and reduced glomerular filtration rates. Furthermore, the transition to certain antiretroviral therapies can heighten the risk of renal complications, as several drugs, such as raltegravir, cobicistat, rilpivirine, and ritonavir, can impair the renal proximal tubules'capacity to eliminate creatinine effectively [12, 13].
This meta-analysis and systematic review aim to determine the overall prevalence of CKD among People living with HIV in Ethiopia. Although there has been an increase in studies addressing CKD rates among People living with HIV across Africa, specific studies for Ethiopia are limited [11]. Gathering comprehensive data on this issue is crucial for researchers, policymakers, and public health stakeholders, as it will enable them to formulate effective health policies, allocate resources appropriately, and prioritize monitoring efforts for evolving health trends.
Methods
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were followed in the conduct of this systematic review and meta-analysis [14]. The studies focusing on CKD among people living with HIV in Ethiopia were the primary focus of this systematic review and meta-analysis. Under registration number CRD42023431245, the protocol for this study was registered at the International Prospective Register of Systematic Reviews (PROSPERO).
Study area
Systematic review and meta-analysis to determine the pooled prevalence of CKD among people living with HIV in Ethiopia and Two studies were from Addis Ababa, four from Gondar, two from Jimma, and rest of them from Bahrdar, Mehal Meda, Mekella, and Mettu.
Source of data and search strategies
A systematic and comprehensive search of the existing literature was carried out using multiple electronic databases, including PubMed, Wiley Online Library, Science Direct, Research Gate, African Journal Online (AJOL), Google Scholar, and Web of Sciences and The remaining 1 was found through a manual search (repositories of Jimma University)were used to retrieve potentially eligible studies reporting. The prevalence of CKD among People living with HIV in Ethiopia. Search parameters for chronic renal disorders and review question keywords were combined.. All research that may be accepted was located using the combination keys provided below: The Boolean operators"OR"and"AND,"when necessary, were used with the expressions"prevalence OR epidemiology"AND"chronic kidney diseases OR renal insufficiency OR renal failure OR end-stage renal failure"OR"impaired kidney diseases"AND"HIV patients"AND"Ethiopia."EndNote 20 software was used for reference management and duplicate removal. Among the papers we located were research articles written in English. University repositories and professional association proceedings were also examined. In order to locate further relevant research that escaped our electronic database searches, we also conducted a direct Google search utilizing the mentioned papers.
Inclusion criteria
All observational studies addressing the prevalence of CKD in people living with HIV in Ethiopia and published in English through May 20, 2023, were considered for inclusion. These studies were selected regardless of the antiretroviral therapy status of the participants, meaning both those receiving treatment and those not on treatments were eligible for analysis.
Exclusion criteria
Certain studies were not included in the analysis. These exclusions comprised case reports, narrative reviews, conference abstracts, lacking complete information, qualitative research studies, review articles, and any publications that failed to present quantitative data regarding the prevalence of CKD in Ethiopia. Additionally, studies that reported CKD prevalence involving fewer than 50 patients were also omitted and according to the specified criteria, they had a low-quality score. It is also important to note that case–control studies were not included as the majority of relevant research identified was predominantly retrospective or cross-sectional in nature; had any case–control studies presented quantitative prevalence data, they would have been considered for inclusion in our review.
Study selection
After evaluating titles and abstracts independently, two investigators (BE and ZM) were able to access the full texts of pertinent studies. When the two reviewers couldn't agree while working alone, a third reviewer (AG) helped to mediate the issue through discussion. This collaborative process produced the final list of papers that were chosen for review, ensuring that the selection was thorough and reflected a consensus among the reviewers. This approach not only enhanced the quality of the review but also minimized potential biases in the study selection process.
Data collection and quality assessment
Original research publications to find relevant publications from the years 2000 to 2023, searches were conducted on PubMed, Google Scholar, Google, and Science Direct. From the search results, papers were filtered based on their titles and abstracts to determine which ones would undergo a full-text review.
The "EndNote reference software version 20 citation manager" was used to export all of the articles in order to clean, organize, and eliminate any potential duplication. We assessed the quality of the selected studies using a critical appraisal tool for evaluating papers included in systematic reviews that address prevalence issues. The articles analyzed were scrutinized across seven domains to identify potential biases by using reviewer manger 5.4 software: representative sampling, participant recruitment, sufficient sample size, accurate descriptions of participants and settings, data completeness and nonresponse rates, unbiased assessment of outcomes, and appropriate statistical methods. We classified the risk of bias in each domain as either low risk, high risk, or unclear [15].
Date synthesis and analysis
The data were extracted into Microsoft Excel version 13 software and subsequently imported into STATA version 14.0 software for statistical analysis. To assess the heterogeneity among the studies, Cochran’s Q test was applied, accompanied by its corresponding p-value and I2 statistics. A significant level of heterogeneity was determined based on the I2 test statistic exceeding 50%. When the Q test and its corresponding p-value were less than 0.05. In line with the protocol, which accounted for potential differences across studies, a random effect model was employed to estimate the pooled prevalence of CKD among people living with HIV across multiple studies, providing a 95% confidence interval, and the findings were illustrated using a forest plot. Evidence of publication bias was suggested by the asymmetries noted in the funnel plot, alongside a p-value below 0.05 from Egger’s test. Subgroup analyses, such as study design, study participant age, and the glomerular filtration rate equations used in the studies, were taken into consideration. Furthermore, methods of trim and fill analysis were applied when publication bias was present. A sensitivity analysis was conducted to evaluate how individual studies influenced the overall pooled estimate.
Result
Description of included studies
Six hundred one published articles were found using a combination of database searches and other methods, such as a total of 601 articles. Of these, 601 articles were retrieved from PubMed (55), Scopus (48), Google Scholar (139), Web of Science (39), Wiley Online Library (23), African Journals Online (237), Research Gate (34), and Science Direct (25). The remaining 1 was found through a manual search (repositories of Jimma University), for studies that were done to estimate the prevalence of CKD among People living with HIV in Ethiopia. Redundancy resulted in the elimination of 345 articles. The titles and abstracts of about 289 papers were then filtered. A total of 56 full-text papers were reviewed for eligibility requirements. For various reasons, 44 full-text papers were then removed from the analysis: studies that did not reflect the total prevalence of CKD, studies that were not done in Ethiopia, and studies without a main outcome. This systematic review and meta-analysis ultimately included 12 studies (Figs. 1 and 2).
Fig. 1.
Risk bias assessment of included study
Fig. 2.
Flow diagram of the included studies for the systematic review and meta-analysis
Characteristics of the included studies
This systematic review and meta-analysis covered a total of 12 original papers published in Ethiopia. There were two of these in Addis Ababa [12, 16], 4 from Gondar City [13, 17–19] and 2 studies were from jimma religion [20, 21]. On the other hand, only 1 study was from Mettu, Mekella, Bahir Dar and Mehal Meda [22–25]. With respect to study design, seven of the studies were cross-sectional, and the remaining five were retrospective studies. The cities of Addis Ababa (13) and Bahir Dar (22) had the highest rates of CKD (25.4%). And in 2021, Addis Ababa similarly reported the lowest prevalence (4.23%) (12). Additionally, creatinine based on the GFR equation estimator was utilized in approximately six studies using the CKD-EPI formula, and six studies using the MDRD formula, The findings from the risk of bias assessment are shown in Table 1. Most of the 10 articles analyzed demonstrated sufficient sample sizes and adequate data completeness and response rates, resulting in a low risk of bias. However, only two articles could be clearly evaluated as having appropriate participant recruitment, detailed descriptions of study participants, and sound data analysis. Despite this, they were classified as having a high risk of bias due to their small sample size. (Table 1).
Table 1.
Characteristics of studies in systematic review and meta- analysis on the prevalence of CKD among People living with HIV in Ethiopia
| Authors | Years of Data collection | Age | Sex | City | Study design | Sample size | Prevalence (%) | Calculation of CKD | |
|---|---|---|---|---|---|---|---|---|---|
| Female | Male | ||||||||
| Yazie et al. [16] | 2017 | > 18 age groups | 43 | 20 | Addis Ababa | Retrospective cohort study | 63 | 25.40 | CKD-EPI |
| Belete et al. [12] | 2019 | > 18 age groups | 144 | 94 | Addis Ababa | Cross –sectional | 243 | 4.53 | CKD-EPI |
| Kahsu et al. [24] | 2014 | > 18 age groups | 45 | 19 | Bahr dar | Retrospective cohort | 63 | 25.40 | CKD-EPI |
| Wondifraw et al. [17] | 2010–2015 | All age groups | 171 | 104 | Gondar | Retrospective cohort | 275 | 15.30 | MDRD |
| Manaye et al. [26] | 2017 | All age groups | 215 | 121 | Gondar | Cross sectional | 336 | 16.10 | CKD-EPI |
| Endris et al. [13] | 2015 | > 18 age groups | 233 | 173 | Gondar | Cross sectional | 290 | 25.20 | MDRD |
| Debeb et al. [19] | 2015–2019 | > 18 age groups | 238 | 162 | Gondar | Retrospective cohort study | 400 | 20.25 | CKD-EPI |
| Mekuria et al. [20] | 2014 | > 18 age groups | 60 | 21 | Jimma | cross- sectional | 446 | 18.2 | MDRD |
| Yishak et al. [21] | 2012 | > 18 age groups | 187 | 134 | Jimma | Cross-sectional | 311 | 15.9 | MDRD |
| Fiseha et al. [27] | 2012–2018 | > 18 age groups | 208 | 145 | Mehal meda | Retrospective cohort | 353 | 19.8 | MDRD |
| Fisha et al. [23] | 2019 | > 18 age groups | 112 | 120 | Mekella | Cross- sectional | 232 | 16.80 | MDRD |
| Kefeni et al. [22] | 2020 | > 18 age groups | 154 | 198 | Mettu | Cross-sectional | 352 | 20.7 | CKD-EPI |
Characteristics of included studies
Pooled prevalence of chronic kidney disease among people living with HIV in Ethiopia
Twelve published studies were included in this systematic review and meta-analysis, and all of these studies were used to estimate the pooled prevalence of CKD among HIV patients. The minimum prevalence of CKD was 4.53% in a retrospective study done in Addis Ababa and the maximum prevalence of CKD were reported both Bahir Dar and Addis Ababa 25.40% [16, 24]. The pooled prevalence of CKD among HIV patients was found to be 18.10% (95% CI: 14.17- 22.03) using random-effect model. The I2 test result showed high heterogeneity (I 2 = 89.7%, P = < 0.001). (Fig. 3).
Fig. 3.
Forest plot showing the pooled prevalence of CKD among People living with HIV in Ethiopia from random-effect model analysis
Sub-groups analysis
Chronic kidney disease by age groups of study participants
Chronic kidney disease by Age groups of study participants based on results from subgroup analysis by age groups, the pooled prevalence of CKD in > =18 age groups was 18.19% (95% CI: 13.53–22.86) and all age groups 18.00% (95% CI: 12.71–23.30). (Fig. 4).
Fig. 4.
Forest plot showing the pooled prevalence of CKD by Age groups of study participants
Chronic kidney disease by study design
The subgroup analysis by study design showed that the overall prevalence of CKD using a retrospective study design was 19.48 (95% CI: 16.44–22.52) higher than a cross-sectional study design of 16.65 (95% CI: 11.05–22.25) (Fig. 5
Fig. 5.
Forest plot showing the pooled prevalence of CKD by Study design
Chronic kidney disease by creatinine –based equation
Additionally, subgroup analysis done based on renal function, estimated by creatinine-based equations, was comparable among Modification Diet Renal Disease (MDRD) and CKD-Epidemiology (CKD-EPI) in HIV patients: 18.38 (95% CI: 15.75–21.02) and 18.06 (95% CI: 10.62–25.49), respectively. (Fig. 6).
Fig. 6.
Forest plot showing the pooled prevalence of CKD by Creatinine based equation
Publication bias
The included studies were assessed for potential publication bias visually by funnel plot. The funnel plot was asymmetrical which indicate the presence of publication bias (Fig. 7). Besides, the result of Egger’s test indicated there was publication bias, P-value < 0.05. The P-value was found to be 0.017 (Table 2).Trim and fill method was used to correct the results. A bias-adjusted effect estimate of CKD showed 14.216 (95%CI: 10.511, 17.922), assuming there are missing studies.
Fig. 7.
Funnel plot on the prevalence of CKD among People living with HIV in Ethiopia
Table 2.
Egger's test showing publication bias
| Std_Eff | Coef | Std. Err | T | P > t | [95% CI] |
|---|---|---|---|---|---|
| Slope | 2.592084 | 4.803599 | 0.54 | 0.601 | [−8.111001–13.29517] |
| Bias | 6.438714 | 2.24699 | 2.84 | 0.017 | [1.432109–11.44532] |
Trim and fill analysis of pooled prevalence of CKD
Due to the presence of publication bias, a trim and fill analysis was performed. Following the inclusion of five additional studies, the revised pooled prevalence of CKD was determined to be (95%CI: 10.511- 17.922) (Table 3).
Table 3.
Trim and fill analysis of the prevalence of CKD among people living with HIV
| Method | Pooled est. | 95% CI | Asymptotic | No. of studies | |||
|---|---|---|---|---|---|---|---|
| Lower | Upper | z-value | p-value | ||||
| Fixed | 15.675 | 14.465 | 16.884 | 25.399 | 0.001 | 12 | |
| Random | 18.101 | 14.168 | 22.033 | 9.022 | 0.001 | ||
| Test for heterogeneity: Q= 106.626 on 11 degrees of freedom (p= 0.001) | |||||||
| Moment-based estimate of between studies variance =41.042 | |||||||
| Trimming estimator: Linear | |||||||
| Meta-analysis type: Fixed-effects model | |||||||
| Iteration | Estimate | Tn | # to trim | Diff | |||
| 1 | 15.675 | 64 | 4 | 78 | |||
| 2 | 14.219 | 69 | 5 | 10 | |||
| 3 | 13.450 | 69 | 5 | 0 | |||
|
Filled Meta-analysis | |||||||
| Method | Pooled est. | 95%CI | Asymptotic | No. of studies | |||
| Lower | Upper | z-value | p-value | ||||
| Fixed | 13.450 | 12.373 | 14.528 | 24.464 | 0.001 | 17 | |
| Random | 14.216 | 10.511 | 17.922 | 7.519 | 0.001 | ||
| Test for heterogeneity: Q= 820.895 on 23 degrees of freedom (p= 0.001) | |||||||
| Moment-based estimate of between studies variance = 51.787 | |||||||
Sensitivity analysis
Sensitivity analysis was performed to evaluate the effect of individual studies on the pooled estimated. When individual study was omitted, the pooled prevalence obtained was within the 95% CI of the overall pooled prevalence. This confirms the absence of single study impact on the overall pooled effect size (Table 4).
Table 4.
Sensitivity analysis of the prevalence of CKD among People living with HIV in Ethiopia
| Study omitted | Estimate | 95% CI |
|---|---|---|
| Belete et al. (2021) | 18.94 | 17.05–20.83 |
| Debeb et al. (2021) | 17.92 | 13.67–22.15 |
| Endris et al. [13] | 17.41 | 13.44–21.37 |
| Fiseha et al.(2021) | 17.96 | 13.72–22.21 |
| Kahsu et al. [24] | 17.66 | 13.62–21.69 |
| Kenfeni et al. (2021) | 17.86 | 13.66–22.07 |
| Manaye et al.(2020) | 18.34 | 13.99–22.69 |
| Mekuria et al. [20] | 18.13 | 13.78–22.49 |
| Wondifraw et al.(2016) | 18.41 | 14.09–22.72 |
| Yazie et al.(2019) | 17.66 | 13.62–21.69 |
| Fisha et al.(2020) | 18.255 | 13.98–22.52 |
| Yishak et al. (2021) | 18.35 | 14.02–22.69 |
| Combined | 18.10 | 14.16–22.03 |
Discussion
This systematic review and meta- analysis focuses on the burden of CKD in Ethiopia. CKD is currently regarded as a significant contributor to the non-communicable disease epidemic in economically developed and low-income/middle-income countries [28]. The range of kidney diseases in people living with HIV has expanded, from mild variations in renal function, such as proteinuria, electrolyte imbalances, and acute kidney injury brought on by diarrheal illnesses, to various degrees of chronic non-communicable disease-related renal damage or HIV-associated nephropathy (HIVAN) [29].
People living with HIV are one of the causes contributing to the rise in CKD. Due to noncollapsing focal segmental glomerulosclerosis, immune-complex kidney disease, concomitant renal disease, HIV-associated nephropathy, kidney damage from opportunistic infections, particularly ritonavir (RTV), and prolonged exposure to antiretroviral therapy [30]. It has been identified as an inhibitor of the active tubular secretion of TDF mediated by the MRP-2 transporter and is frequently given in conjunction with TDF [31]. Thus, this inhibition may cause TDF to accumulate intracellular within the tubules, thereby increasing renal tubular toxicity [32].
In this review the pooled prevalence of CKD in people living with HIV in Ethiopia was 18.10 (95%CI: 14.17–22.03)) result was higher than the systematic review and meta-analysis done in Africa. The prevalence of CKD in the general population and high-risk groups, particularly people living with HIV, was pooled at 10.1% (95% CI: 9.8% to 10.5%) and 5.6% (95% CI: 5.4% to 5.8%), respectively [28].The estimated prevalence of CKD in the people living with HIV ranges from 2.5% in Europe to 7.4% in North America [29, 33].Our finding also higher than study conducted in Cameron was 6.6% [34],Ivory coast (10.44%) [35], the prevalence of CKD in Nigeria was 15.3% [36],and epidemiology of CKD in sub-Saharan African was 13·9% (95% CI 12·2–15·7) [37].
However our finding was lower than result reported from CKD in global population (23%) [29]. The overall prevalence of renal dysfunction in Tanzania was 20.7%, [38] and in South Africa was 28% [39]. The reasons for these discrepancies could be explained by variations in the research subjects, number of studies, sample size, measurement technique, or definition of renal impairment; prevalence estimates can range significantly even among groups that are identical. Genetic diversity, preventative initiatives, health care system accessibility, and the start of combination antiretroviral therapy [39].
Additionally, subgroup analysis done based on renal function, estimated by creatinine-based equations, was comparable among Modification Diet Renal Disease (MDRD) and CKD-Epidemiology (CKD-EPI) in people living with HIV: 18.38 (95% CI: 15.75–21.02)and 18.06 (95% CI: 10.62–25.49), respectively. Our finding was higher than Globally, renal function impairment among adults living with HIV estimated using the MDRD was 6.4%, using the CKD-EPI equation was 4.8% [29],
HIV-related kidney disease, including CKD, acute kidney injury (AKI), and treatment-related kidney toxicity, is among the various forms of renal illness that can affect people living with the HIV. All people living with HIV should undergo screening for renal dysfunction both upon diagnosis and at the onset of antiretroviral therapy. The goal of antiretroviral therapy medications is to slow the spread of HIV infection over an extended period of time. Given the lifetime nature of antiretroviral therapy and its potential long-term effects on renal function. The WHO advises measuring patients'creatinine clearance"if feasible"at the beginning of tenofovir treatment and every six months [22, 30, 40].
Additionally, there are certain strengths and limitations to this review. A key strength of our review is that it enhances the understanding of the prevalence of CKD among People living with HIV in Ethiopia. This study provides valuable insights into the current health challenges faced by this population, highlighting the need for targeted interventions; however, the review has limitations. It was unable to assess factors linked to the combined prevalence of CKD, meaning that critical insights into underlying causes remain unexplored. Moreover, the absence of subgroup analyses based on HIV infection control such as those on antiretroviral therapy versus those who are not.
Conclusion and recommendation
These findings indicate a robust correlation between CKD and HIV. Consequently, it is recommended that HIV treatment programs establish ongoing screening initiatives, enhance routine CKD assessments during initial evaluations and antiretroviral therapy follow-ups, and devise comprehensive management strategies to prevent the progression of CKD in People living with HIV [10].
Acknowledgements
The authors would like to express their gratitude to the authors of the included research as well as the participants in their investigations.
Abbreviations
- ART
Antiretroviral therapy
- CKD
Chronic kidney diseases
- CKD-EPI
Chronic kidney diseases epidemiology
- HAART
Highly active antiretroviral therapy
- HIV
Human immunodeficiency virus
- MDRD
Modification Diet Renal Disease
- RTV
Ritonavir
- TDF
Tenofovir disoproxil fumarate
Authors’ contributions
BE conceptualized and designed the study, searched for articles, screened and extracted data, evaluated the quality of the included articles, performed statistical analysis, and wrote the manuscript. OM, MAB, ZM, HD, AG, DGW, EA, AS, AG, MT, SGT and HE were involved in searching for articles, screening and extracting data, assessing the quality of the included data, and assisting in the analysis, reviewing, and editing of the manuscript. All authors read and approved the final draft of the manuscript.
Funding
There is no specific funding for this review.
Data availability
The article contains all of the data needed for this study. If more information is required, it can be obtained from the corresponding authors upon request.
Declarations
Ethics approval and consent to participate
Ethical approval and consent to participate are not required because this is a systematic review and meta-analysis that does not involve human or animal experiments. This review was conducted in accordance with the principles outlined in the Declaration of Helsinki (World Medical Association, 2013).
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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The article contains all of the data needed for this study. If more information is required, it can be obtained from the corresponding authors upon request.