Development and validation of risk models to predict chronic kidney disease among people living with HIV: protocol for a systematic review

INTRODUCTION: Chronic kidney disease (CKD) is estimated to affect about 9.1% of the global population with a substantially increased risk of the condition (6.8%–17.2%) among people living with HIV (PLWH). This increased risk is attributed to HIV infection itself, antiretroviral therapy, coexisting viral infections, non-infectious comorbidities and traditional risk factors for CKD. Predictive models have been employed in the estimation of prevalent and incident CKD risk in both PLWH and the general population. A predictive model showing an individual’s risk of prevalent and/or progression to kidney failure is useful for initiating timely interventions that prevent further worsening of kidney function. This study will systematically review published prediction models developed and/or validated for prevalent and incident CKD in PLWH, describe their characteristics, compare performance and assess methodological quality and applicability. METHODS AND ANALYSIS: Studies with predictive models of interest will be identified by searching MEDLINE, Web of Science, Cumulative Index to Nursing and Allied Health Literature, Cochrane library and Scopus from inception to May 2022. Title and abstract screening, full-text review and data extraction will be completed independently by two reviewers. Using appropriate tools designed for predictive modelling investigations, the included papers will be rigorously assessed for bias and applicability. Extracted data will be presented in tables, so that published prediction models can be compared qualitatively. Quantitative data on the predictive performance of these models will be synthesised with meta-analyses if appropriate. ETHICS AND DISSEMINATION: The findings of the review will be disseminated in peer-reviewed journals and seminar presentations. Ethical approval is not required as this is a protocol for a systematic review. PROSPERO REGISTRATION NUMBER: CRD42021279694.