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Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models

The incidence of chronic kidney disease (CKD) is increasing among people living with HIV (PLWH). Routine monitoring of indicators such as CD4:CD8 ratio might improve the early detection of CKD. Our objective was to identify clinically relevant CD4:CD8 ratio trajectories indicative of CKD risk. Parti...

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Autores principales: Fonseca-Cuevas, Alejandra, Newsome, Patrick, Wang, Lu, Chen, Michelle Y., Richardson, Chris G., Hull, Mark, McLinden, Taylor, Guillemi, Silvia, Barrios, Rolando, Montaner, Julio S. G., Lima, Viviane D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963117/
https://www.ncbi.nlm.nih.gov/pubmed/36851599
http://dx.doi.org/10.3390/v15020385
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author Fonseca-Cuevas, Alejandra
Newsome, Patrick
Wang, Lu
Chen, Michelle Y.
Richardson, Chris G.
Hull, Mark
McLinden, Taylor
Guillemi, Silvia
Barrios, Rolando
Montaner, Julio S. G.
Lima, Viviane D.
author_facet Fonseca-Cuevas, Alejandra
Newsome, Patrick
Wang, Lu
Chen, Michelle Y.
Richardson, Chris G.
Hull, Mark
McLinden, Taylor
Guillemi, Silvia
Barrios, Rolando
Montaner, Julio S. G.
Lima, Viviane D.
author_sort Fonseca-Cuevas, Alejandra
collection PubMed
description The incidence of chronic kidney disease (CKD) is increasing among people living with HIV (PLWH). Routine monitoring of indicators such as CD4:CD8 ratio might improve the early detection of CKD. Our objective was to identify clinically relevant CD4:CD8 ratio trajectories indicative of CKD risk. Participants were ≥ 18 years old, initiated antiretroviral therapy between 2000 and 2016, and were followed for ≥6 months until 31 March 2017 or last contact date. Outcome was incidence of CKD. Growth mixture models (GMMs) and decay models were used to compare CD4:CD8 ratio trajectories. Following GMM, 4547 (93.5%) participants were classified in Class 1 with 5.4% developing CKD, and 316 (6.5%) participants were classified in Class 2 with 20.9% developing CKD. The final model suggested that participants in Class 2 had 8.72 times the incidence rate of developing CKD than those in Class 1. Exponential decay models indicated a significant CD4:CD8 ratio decline among Class 2 participants who developed CKD. Among those who developed CKD in Class 2, starting at 5.5 years of follow-up, the slope of their ratio trajectory curve changed significantly, and the rate of decline increased dramatically. Routine monitored CD4:CD8 ratios can be an effective strategy to identify early CKD risk among PLWH.
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spelling pubmed-99631172023-02-26 Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models Fonseca-Cuevas, Alejandra Newsome, Patrick Wang, Lu Chen, Michelle Y. Richardson, Chris G. Hull, Mark McLinden, Taylor Guillemi, Silvia Barrios, Rolando Montaner, Julio S. G. Lima, Viviane D. Viruses Article The incidence of chronic kidney disease (CKD) is increasing among people living with HIV (PLWH). Routine monitoring of indicators such as CD4:CD8 ratio might improve the early detection of CKD. Our objective was to identify clinically relevant CD4:CD8 ratio trajectories indicative of CKD risk. Participants were ≥ 18 years old, initiated antiretroviral therapy between 2000 and 2016, and were followed for ≥6 months until 31 March 2017 or last contact date. Outcome was incidence of CKD. Growth mixture models (GMMs) and decay models were used to compare CD4:CD8 ratio trajectories. Following GMM, 4547 (93.5%) participants were classified in Class 1 with 5.4% developing CKD, and 316 (6.5%) participants were classified in Class 2 with 20.9% developing CKD. The final model suggested that participants in Class 2 had 8.72 times the incidence rate of developing CKD than those in Class 1. Exponential decay models indicated a significant CD4:CD8 ratio decline among Class 2 participants who developed CKD. Among those who developed CKD in Class 2, starting at 5.5 years of follow-up, the slope of their ratio trajectory curve changed significantly, and the rate of decline increased dramatically. Routine monitored CD4:CD8 ratios can be an effective strategy to identify early CKD risk among PLWH. MDPI 2023-01-29 /pmc/articles/PMC9963117/ /pubmed/36851599 http://dx.doi.org/10.3390/v15020385 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fonseca-Cuevas, Alejandra
Newsome, Patrick
Wang, Lu
Chen, Michelle Y.
Richardson, Chris G.
Hull, Mark
McLinden, Taylor
Guillemi, Silvia
Barrios, Rolando
Montaner, Julio S. G.
Lima, Viviane D.
Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models
title Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models
title_full Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models
title_fullStr Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models
title_full_unstemmed Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models
title_short Identifying Longitudinal CD4:CD8 Ratio Trajectories Indicative of Chronic Renal Disease Risk among People Living with HIV: An Application of Growth Mixture Models
title_sort identifying longitudinal cd4:cd8 ratio trajectories indicative of chronic renal disease risk among people living with hiv: an application of growth mixture models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963117/
https://www.ncbi.nlm.nih.gov/pubmed/36851599
http://dx.doi.org/10.3390/v15020385
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