Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care

Simon Sawhney (Corresponding Author), Monica Beaulieu, Corri Black, Ognjenka Djurdjev, Gabriela Espino-Hernandez, Angharad Marks, David J McLernon, Zainab Sheriff, Adeera Levin

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Abstract

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 m2). 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 m2 {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m2 ([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.
Original languageEnglish
JournalNephrology Dialysis Transplantation
Early online date15 Oct 2018
DOIs
Publication statusE-pub ahead of print - 15 Oct 2018

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Nephrology
Acute Kidney Injury
Renal Insufficiency
Glomerular Filtration Rate
Kidney Diseases
Confidence Intervals
Proportional Hazards Models
British Columbia
Decision Support Techniques
Mortality
Proteinuria
ROC Curve
Observational Studies
Cohort Studies
Kidney

Keywords

  • acute kidney injury
  • kidney failure
  • prediction
  • prognosis
  • survival
  • epidemiology

Cite this

Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care. / Sawhney, Simon (Corresponding Author); Beaulieu, Monica; Black, Corri; Djurdjev, Ognjenka; Espino-Hernandez, Gabriela ; Marks, Angharad; McLernon, David J; Sheriff, Zainab; Levin, Adeera.

In: Nephrology Dialysis Transplantation, 15.10.2018.

Research output: Contribution to journalArticle

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title = "Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care",
abstract = "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 m2). 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 m2 {hazard ratio [HR] 1.35 [95{\%} confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m2 ([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.",
keywords = "acute kidney injury, kidney failure, prediction , prognosis, survival, epidemiology",
author = "Simon Sawhney and Monica Beaulieu and Corri Black and Ognjenka Djurdjev and Gabriela Espino-Hernandez and Angharad Marks and McLernon, {David J} and Zainab Sheriff and Adeera Levin",
note = "SS was supported by a research training fellowship from the Wellcome Trust (102729/Z/13/Z). We are grateful to Dr Nadia Zalunardo for her comments on this study.",
year = "2018",
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doi = "10.1093/ndt/gfy294",
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T1 - Predicting kidney failure risk after acute kidney injury among people receiving nephrology clinic care

AU - Sawhney, Simon

AU - Beaulieu, Monica

AU - Black, Corri

AU - Djurdjev, Ognjenka

AU - Espino-Hernandez, Gabriela

AU - Marks, Angharad

AU - McLernon, David J

AU - Sheriff, Zainab

AU - Levin, Adeera

N1 - SS was supported by a research training fellowship from the Wellcome Trust (102729/Z/13/Z). We are grateful to Dr Nadia Zalunardo for her comments on this study.

PY - 2018/10/15

Y1 - 2018/10/15

N2 - 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 m2). 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 m2 {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m2 ([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.

AB - 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 m2). 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 m2 {hazard ratio [HR] 1.35 [95% confidence interval (CI) 1.07–1.70]}, no increase in those with eGFR <30 mL/min/1.73 m2 ([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.

KW - acute kidney injury

KW - kidney failure

KW - prediction

KW - prognosis

KW - survival

KW - epidemiology

U2 - 10.1093/ndt/gfy294

DO - 10.1093/ndt/gfy294

M3 - Article

JO - Nephrology Dialysis Transplantation

JF - Nephrology Dialysis Transplantation

SN - 0931-0509

ER -