"Validation of the D:A:D Chronic Kidney Disease Risk Score Incorporating Proteinuria in People Living with HIV in Harare, Zimbabwe"​​.

Anderson, Matthew A; Chimbetete, Cleophas; Shamu, Tinei; Dahwa, Rumbizai; Gracey, David M (2022). "Validation of the D:A:D Chronic Kidney Disease Risk Score Incorporating Proteinuria in People Living with HIV in Harare, Zimbabwe"​​. Journal of acquired immune deficiency syndromes JAIDS, 90(5), pp. 562-566. Lippincott Williams & Wilkins 10.1097/QAI.0000000000003002

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OBJECTIVE

We sought to validate the D:A:D risk score for chronic kidney disease (CKD) in people living with HIV (PLWH) in a cohort from Harare, Zimbabwe. Additionally, we aimed to evaluate proteinuria as a predictive variable in the risk score model, being the first study to do so.

DESIGN

Data from PLWH attending a clinic in Harare was evaluated. Those with a baseline estimated glomerular filtration rate >60ml/min/1.73m2 and at least two subsequent eGFR measurements were included. A modified version of the D:A:D risk score model was applied to categorise participants as 'low', 'medium' and 'high-risk' of progression to CKD. Potential predictors of renal impairment were assessed by logistic regression in univariate and multivariate models. Proteinuria was evaluated in a nested model using D:A:D risk categories.

RESULTS

2793 participants were included. 40 participants (1.4% of the cohort) progressed to CKD during the median follow-up time of 4.2 years. Progression rates were 1%, 3% and 12% in the low, medium, and high-risk groups respectively. Proteinuria data was available for 2251 participants. Presence of proteinuria was strongly associated with progression to CKD [OR 7.8, 95% CI 3.9-15.7], and its inclusion in the risk score improved the discrimination of the model with the c-statistic increasing from 0.658 to 0.853).

CONCLUSION

A modified version of the D:A:D CKD risk score performed well in predicting CKD events among this Sub-Saharan African cohort of people living with HIV. Inclusion of proteinuria into the risk score model significantly improved predictability.

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