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Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care
BACKGROUND: Outcomes after acute kidney injury (AKI) are well described, but not for those already under nephrology clinic care. This is where discussions about kidney failure risk are commonplace. We evaluated whether the established kidney failure risk equation (KFRE) should account for previous A...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203563/ https://www.ncbi.nlm.nih.gov/pubmed/30325464 http://dx.doi.org/10.1093/ndt/gfy294 |
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author | Sawhney, Simon Beaulieu, Monica Black, Corri Djurdjev, Ognjenka Espino-Hernandez, Gabriela Marks, Angharad McLernon, David J Sheriff, Zainab Levin, Adeera |
author_facet | Sawhney, Simon Beaulieu, Monica Black, Corri Djurdjev, Ognjenka Espino-Hernandez, Gabriela Marks, Angharad McLernon, David J Sheriff, Zainab Levin, Adeera |
author_sort | Sawhney, Simon |
collection | PubMed |
description | BACKGROUND: Outcomes after acute kidney injury (AKI) are well described, but not for those already under nephrology clinic care. This is where discussions about kidney failure risk are commonplace. We evaluated whether the established kidney failure risk equation (KFRE) should account for previous AKI episodes when used in this setting. METHODS: This observational cohort study included 7491 people referred for nephrology clinic care in British Columbia in 2003–09 followed to 2016. Predictors were previous Kidney Disease: Improving Global Outcomes–based AKI, age, sex, proteinuria, estimated glomerular filtration rate (eGFR) and renal diagnosis. Outcomes were 5-year kidney failure and death. We developed cause-specific Cox models (AKI versus no AKI) for kidney failure and death, stratified by eGFR (</≥30 mL/min/1.73 m(2)). We also compared prediction models comparing the 5-year KFRE with two refitted models, one with and one without AKI as a predictor. RESULTS: AKI was associated with increased kidney failure (33.1% versus 26.3%) and death (23.8% versus 16.8%) (P < 0.001). In Cox models, AKI was independently associated with increased kidney failure in those with an eGFR ≥30 mL/min/1.73 m(2) {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m(2) ([HR 1.05 95% CI 0.91–1.21)] and increased mortality in both subgroups [respective HRs 1.89 (95% CI 1.56–2.30) and 1.43 (1.16–1.75)]. Incorporating AKI into a refitted kidney failure prediction model did not improve predictions on comparison of receiver operating characteristics (P = 0.16) or decision curve analysis. The original KFRE calibrated poorly in this setting, underpredicting risk. CONCLUSIONS: AKI carries a poorer long-term prognosis among those already under nephrology care. AKI may not alter kidney failure risk predictions, but the use of prediction models without appreciating the full impact of AKI, including increased mortality, would be simplistic. People with kidney diseases have risks beyond simply kidney failure. This complexity and variability of outcomes of individuals is important. |
format | Online Article Text |
id | pubmed-7203563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-72035632020-05-11 Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care Sawhney, Simon Beaulieu, Monica Black, Corri Djurdjev, Ognjenka Espino-Hernandez, Gabriela Marks, Angharad McLernon, David J Sheriff, Zainab Levin, Adeera Nephrol Dial Transplant ORIGINAL ARTICLES BACKGROUND: Outcomes after acute kidney injury (AKI) are well described, but not for those already under nephrology clinic care. This is where discussions about kidney failure risk are commonplace. We evaluated whether the established kidney failure risk equation (KFRE) should account for previous AKI episodes when used in this setting. METHODS: This observational cohort study included 7491 people referred for nephrology clinic care in British Columbia in 2003–09 followed to 2016. Predictors were previous Kidney Disease: Improving Global Outcomes–based AKI, age, sex, proteinuria, estimated glomerular filtration rate (eGFR) and renal diagnosis. Outcomes were 5-year kidney failure and death. We developed cause-specific Cox models (AKI versus no AKI) for kidney failure and death, stratified by eGFR (</≥30 mL/min/1.73 m(2)). We also compared prediction models comparing the 5-year KFRE with two refitted models, one with and one without AKI as a predictor. RESULTS: AKI was associated with increased kidney failure (33.1% versus 26.3%) and death (23.8% versus 16.8%) (P < 0.001). In Cox models, AKI was independently associated with increased kidney failure in those with an eGFR ≥30 mL/min/1.73 m(2) {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m(2) ([HR 1.05 95% CI 0.91–1.21)] and increased mortality in both subgroups [respective HRs 1.89 (95% CI 1.56–2.30) and 1.43 (1.16–1.75)]. Incorporating AKI into a refitted kidney failure prediction model did not improve predictions on comparison of receiver operating characteristics (P = 0.16) or decision curve analysis. The original KFRE calibrated poorly in this setting, underpredicting risk. CONCLUSIONS: AKI carries a poorer long-term prognosis among those already under nephrology care. AKI may not alter kidney failure risk predictions, but the use of prediction models without appreciating the full impact of AKI, including increased mortality, would be simplistic. People with kidney diseases have risks beyond simply kidney failure. This complexity and variability of outcomes of individuals is important. Oxford University Press 2018-10-15 /pmc/articles/PMC7203563/ /pubmed/30325464 http://dx.doi.org/10.1093/ndt/gfy294 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of ERA-EDTA. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | ORIGINAL ARTICLES Sawhney, Simon Beaulieu, Monica Black, Corri Djurdjev, Ognjenka Espino-Hernandez, Gabriela Marks, Angharad McLernon, David J Sheriff, Zainab Levin, Adeera Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
title | Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
title_full | Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
title_fullStr | Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
title_full_unstemmed | Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
title_short | Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
title_sort | predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care |
topic | ORIGINAL ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203563/ https://www.ncbi.nlm.nih.gov/pubmed/30325464 http://dx.doi.org/10.1093/ndt/gfy294 |
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