Prevalence, incidence and predictors of renal impairment in persons with HIV receiving protease-inhibitors in rural Tanzania

Abstract

Objective Ritonavir-boosted protease inhibitors (bPI) in people living with HIV (PLWH) have been associated with renal impairment. Limited data are available from rural sub-Saharan Africa. Methods Using data from the Kilombero and Ulanga Antiretroviral Cohort Study (KIULARCO) in rural Tanzania from 2005-01/2020, we assessed the prevalence of renal impairment (estimated glomerular filtration rate <60 mL/min/1.73m2) at the time of switch from first-line antiretroviral treatment (ART) to bPI-regimen and the incidence of renal impairment on bPI. We assessed risk factors for renal impairment using logistic and Cox regression models. Results Renal impairment was present in 52/687 PLWH (7.6%) at the switch to bPI. Among 556 participants with normal kidney function at switch, 41 (7.4%) developed renal impairment after a median time of 3.5 (IQR 1.6–5.1) years (incidence 22/1,000 person-years (95%CI 16.1–29.8)). Factors associated with renal impairment at switch were older age (adjusted odds ratio (aOR) 1.55 per 10 years; 95%CI 1.15–2.11), body mass index (BMI) <18.5 kg/m2 (aOR 2.80 versus ≥18kg/m2; 95%CI 1.28–6.14) and arterial hypertension (aOR 2.33; 95%CI 1.03–5.28). The risk of renal impairment was lower with increased duration of ART use (aOR 0.78 per one-year increase; 95%CI 0.67–0.91). The renal impairment incidence under bPI was associated with older age (adjusted hazard ratio 2.01 per 10 years; 95%CI 1.46–2.78). Conclusions In PLWH in rural sub-Saharan Africa, prevalence and incidence of renal impairment among those who were switched from first-line to bPI-regimens were high. We found associations between renal impairment and older age, arterial hypertension, low BMI and time on ART.

Prevalence and Risk Factors for Renal Insufficiency among Adults Living with HIV in Tanzania: Results from a Cross-Sectional Study in 2020–2021

“…In this study, age was a strong predictor of reduced eGFR, a finding similar to other studies in SSA [ 10 , 11 , 12 ]. Studies have shown that chronic HIV infection accelerates aging and, even among ALHIV well controlled on ART, there is still an increased risk of age-related renal function loss [ 26 ].…”

“…eGFR was estimated from serum creatinine using the 2021 CKD-EPI equation and was used as a continuous outcome in the regression analysis. The 2021 CKD-EPI formula is a race-free formulae that has been widely used to assess renal insufficiency among Africans in SSA [ 11 , 12 ]. Use of race-based CKD-EPI has been shown to overestimate eGFR if applied among African populations, consequently resulting in delayed initiation of nephrological care including dialysis initiation [ 31 , 32 , 33 ].…”

“…In Sub-Saharan Africa (SSA), where over two-thirds of the world’s population of ALHIV reside [ 3 ], the pooled prevalence of renal insufficiency among ALHIV is reported to be as high as 12% [ 8 , 9 ]. Renal insufficiency is also common among ALHIV in Tanzania, with prevalence ranging from 7 to 11% [ 10 , 11 , 12 , 13 ].…”

“…Other HIV infection-related risk factors include low CD4+ T cell counts, high HIV viral loads (VLs), and coinfection with hepatitis C and/or Hepatitis B virus [ 17 ]. ALHIV are also at risk for renal insufficiency from traditional risk factors [ 11 , 12 , 17 ], including older age, high BP, diabetes mellitus, dyslipidemia, obesity, and smoking, which are increasingly common among ALHIV in Tanzania [ 13 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. Studies from the US have shown that persons of African descent are also at increased risk for renal insufficiency and disease due to polymorphisms in the apolipoprotein L1 (APOL1) gene [ 25 , 26 ].…”

The Chronic Diseases Clinic of Ifakara (CDCI)—Establishing a Model Clinic for Chronic Care Delivery in Rural Sub-Saharan Africa

“…The long-term nature of the cohort—currently 17 years—and the large set of systematic clinical and laboratory data collected together with a large biobank make this cohort unique [ 2 , 5 ]. Based on its data and biobank important scientific manuscripts on treatment outcomes [ 3 , 6 , 7 ], mother to child transmission [ 8 , 9 , 10 ], comorbidities [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ], mortality [ 5 , 6 ] and other aspects were published and helped to adjust HIV service delivery to better meet patients’ needs.…”