A Poda1, N F Kabore2, K Malateste3, N De Rekeneire2, A Semde4, Y Bikinga5, A Patassi6, H Chenal7, E Messou8, F Dabis9, D K Ekouevi10, A Jaquet3, A Cournil11. 1. Department of Infectious Diseases, Sourô Sanou University Hospital, Bobo Dioulasso, Burkina Faso. 2. Clinical Research Department, Centre MURAZ, Bobo Dioulasso, Burkina Faso. 3. Inserm 1219 & Institut de Santé Publique d'épidémiologie et de développement, Bordeaux University, Bordeaux, France. 4. Department of Nephrology, Sourô Sanou University Hospital, Bobo Dioulasso, Burkina Faso. 5. Department of Nephrology, Bogodogo University Hospital, Ouagadougou, Burkina Faso. 6. Department of Infectious and Tropical Diseases, Sylvanus Olympio University Hospital, Lomé, Togo. 7. Centre Intégré de Recherches Biocliniques d'Abidjan (CIRBA), Abidjan, Côte d'Ivoire. 8. Centre de Prise en charge, de Recherche et de Formation (CePReF), Abidjan, Côte d'Ivoire. 9. Institut national de la santé et de la recherche médicale-ANRS (France REcherche Nord&Sud Sida-hiv Hépatites), Paris, France. 10. Public Health Department, Lomé University, Lome, Togo. 11. Pathogenesis & Control of Chronic Infections, INSERM U1058, Montpellier University, Montpellier, France.
Abstract
OBJECTIVES: A risk score for long-term prediction of chronic kidney disease (CKD) in people living with HIV (PLHIV) has been developed using data from the D:A:D cohort. We assessed the performance of the D:A:D risk score in a cohort of PLHIV in West Africa. METHODS: Data from PLHIV starting antiretroviral treatment in four clinics in Burkina Faso, Côte d'Ivoire and Togo participating in the IeDEA West Africa collaboration were analysed. CKD was defined as two consecutive estimated glomerular filtration rates (eGFRs) of ≤ 60 mL/min/1.73 m2 . The D:A:D score (short version) was calculated using age, gender, nadir CD4 and baseline eGFR and was categorized into low, medium, and high-risk groups. RESULTS: In 14 930 participants (70% female, median age = 38 years; median nadir CD4 count = 183 cells/µL) followed for a median duration of 5.7 years, 660 (4.4%) progressed to CKD, with an incidence [95% confidence interval (CI)] of 7.8 (7.2-8.4) per 1000 person-years (PY). CKD incidence rates were 2.4 (2.0-2.8), 8.1 (6.8-9.6) and, 30.9 (28.0-34.1) per 1000 PY in the low-, medium- and high-risk groups, respectively. In the high-risk group, 14.7% (95% CI: 13.3; 16.3) had progressed to CKD at 5 years. Discrimination was good [C-statistics = 0.81 (0.79-0.83)]. In all, 79.4% of people who progressed to CKD were classified in the medium- to high-risk group at baseline (sensitivity) and 66.5% of people classified in the low risk group at baseline did not progress to CKD (specificity). CONCLUSIONS: These findings confirm the validity of the D:A:D score in identifying individuals at risk of developing CKD who could benefit from enhanced kidney monitoring in West African HIV clinics.
OBJECTIVES: A risk score for long-term prediction of chronic kidney disease (CKD) in people living with HIV (PLHIV) has been developed using data from the D:A:D cohort. We assessed the performance of the D:A:D risk score in a cohort of PLHIV in West Africa. METHODS: Data from PLHIV starting antiretroviral treatment in four clinics in Burkina Faso, Côte d'Ivoire and Togo participating in the IeDEA West Africa collaboration were analysed. CKD was defined as two consecutive estimated glomerular filtration rates (eGFRs) of ≤ 60 mL/min/1.73 m2 . The D:A:D score (short version) was calculated using age, gender, nadir CD4 and baseline eGFR and was categorized into low, medium, and high-risk groups. RESULTS: In 14 930 participants (70% female, median age = 38 years; median nadir CD4 count = 183 cells/µL) followed for a median duration of 5.7 years, 660 (4.4%) progressed to CKD, with an incidence [95% confidence interval (CI)] of 7.8 (7.2-8.4) per 1000 person-years (PY). CKD incidence rates were 2.4 (2.0-2.8), 8.1 (6.8-9.6) and, 30.9 (28.0-34.1) per 1000 PY in the low-, medium- and high-risk groups, respectively. In the high-risk group, 14.7% (95% CI: 13.3; 16.3) had progressed to CKD at 5 years. Discrimination was good [C-statistics = 0.81 (0.79-0.83)]. In all, 79.4% of people who progressed to CKD were classified in the medium- to high-risk group at baseline (sensitivity) and 66.5% of people classified in the low risk group at baseline did not progress to CKD (specificity). CONCLUSIONS: These findings confirm the validity of the D:A:D score in identifying individuals at risk of developing CKD who could benefit from enhanced kidney monitoring in West African HIV clinics.
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