Chronic kidney disease in the global adult HIV-infected population: A systematic review and meta-analysis

Abstract

Introduction: The widespread use of antiretroviral therapies (ART) has increased life expectancy in HIV patients, predisposing them to chronic non-communicable diseases including Chronic Kidney Disease (CKD). We performed a systematic review and meta-analysis (PROSPERO registration number CRD42016036246) to determine the global and regional prevalence of CKD in HIV patients.

Methods: We searched PubMed, Web of Science, EBSCO and AJOL for articles published between January 1982 and May 2016. CKD was defined as estimated glomerular filtration rate (eGFR) <60ml/min using the MDRD, Cockcroft-Gault or CKD-EPI equations. Random effects model was used to combine prevalence estimates from across studies after variance stabilization via Freeman-Tukey transformation.

Result: Sixty-one eligible articles (n = 209,078 HIV patients) in 60 countries were selected. The overall CKD prevalence was 6.4% (95%CI 5.2-7.7%) with MDRD, 4.8% (95%CI 2.9-7.1%) with CKD-EPI and 12.3% (95%CI 8.4-16.7%) with Cockcroft-Gault; p = 0.003 for difference across estimators. Sub-group analysis identified differences in prevalence by WHO region with Africa having the highest MDRD-based prevalence at 7.9% (95%CI 5.2-11.1%). Within Africa, the pooled MDRD-based prevalence was highest in West Africa [14.6% (95%CI 9.9-20.0%)] and lowest in Southern Africa (3.2%, 95%CI 3.0-3.4%). The heterogeneity observed could be explained by WHO region, comorbid hypertension and diabetes mellitus, but not by gender, hepatitis B or C coinfection, CD4 count or antiretroviral status.

Conclusion: CKD is common in HIV-infected people, particularly in Africa. HIV treatment programs need to intensify screening for CKD with added need to introduce global guidelines for CKD identification and treatment in HIV positive patients.

Fig 1. Flow diagram for the selection of studies.

Fig 2. Forest plot showing the overall CKD prevalence in the HIV-infected using the MDRD, CKD-EPI and CG equations.

For each study the black box represents the study estimate (prevalence of CKD) and the horizontal bar represents the 95% confidence intervals (95%CI). The yellow diamond at the lower tail for each equation is the pooled effect estimates from random effects models.

Fig 3. Funnel plots for included studies across different serum creatinine-based GFR equations.

For each estimation equation, the arcsine transformed proportion of participants with CKD (relative to the total sample) for each relevant study (horizontal axis) is plotted against its standard error (vertical axis), and represented by the dots. When the dots distribute symmetrically in a funnel shape, this implies an absence of bias. All p-values were >0.05 (Egger test) indicating no evidence of significant publication bias.

Fig 4. Summary of pooled prevalence of CKD in HIV populations across WHO regions.

Fig 5. Summary of pooled prevalence of CKD in HIV populations of the African sub-regions.