A new clinical multivariable model that predicts postoperative acute kidney injury

Impact of endogenous ouabain

Marco Simonini, Chiara Lanzani, Elena Bignami, Nunzia Casamassima, Elena Frati, Roberta Meroni, Elisabetta Messaggio, Ottavio Alfieri, John Hamlyn, Simon C. Body, C. David Collard, J. Daniel Muehlschlegel, Stanton K. Shernan, Amanda A. Fox, Alberto Zangrillo, Paolo Manunta

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

Background. Acute kidney injury (AKI) is an important complication of cardiac surgery. Recently, elevated levels of endogenous ouabain (EO), an adrenal stress hormone with haemodynamic and renal effects, have been associated with worse renal outcome after cardiac surgery. Our aim was to develop and evaluate a new risk model of AKI using simple preoperative clinical parameters and to investigate the utility of EO. Methods. The primary outcome was AKI according to Acute Kidney Injury Network stage II or III. We selected the Northern New England Cardiovascular Disease Study Group (NNECDSG) as a reference model. We built a new internal predictive risk model considering common clinical variables (CLIN-RISK), compared this model with the NNECDSG model and determined whether the addition of preoperative plasma EO improved prediction of AKI. Results. All models were tested on >800 patients admitted for elective cardiac surgery in our hospital. Seventy-nine patients developed AKI (9.9%). Preoperative EO levels were strongly associated with the incidence of AKI and clinical complication (total ICU stay and in-hospital mortality). The NNECDSG model was confirmed as a good predictor of AKI (AUC 0.74, comparable to the NNECDSG reference population). Our CLIN-RISK model had improved predictive power for AKI (AUC 0.79, CI 95% 0.73-0.84). Furthermore, addition of preoperative EO levels to both clinical models improved AUC to 0.79 and to 0.83, respectively (ΔAUC +0.05 and +0.04, respectively, P < 0.01). Conclusion. In a population where the predictive power of the NNECDSG model was con firmed, CLIN-RISK was more powerful. Both clinical models were further improved by the addition of preoperative plasma EO levels. These new models provide improved predictability of the relative risk for the development of AKI following cardiac surgery and suggest that EO is a marker for renal vascular injury.

Original languageEnglish (US)
Pages (from-to)1696-1701
Number of pages6
JournalNephrology Dialysis Transplantation
Volume29
Issue number9
DOIs
StatePublished - 2014

Fingerprint

Ouabain
Acute Kidney Injury
New England
Cardiovascular Diseases
Thoracic Surgery
Area Under Curve
Kidney
Vascular System Injuries
Hospital Mortality
Population Groups
Hemodynamics
Hormones
Incidence

Keywords

  • Acute renal failure
  • Blood pressure
  • Cardiovascular disease
  • Na transport
  • Renal injury

ASJC Scopus subject areas

  • Nephrology
  • Transplantation

Cite this

Simonini, M., Lanzani, C., Bignami, E., Casamassima, N., Frati, E., Meroni, R., ... Manunta, P. (2014). A new clinical multivariable model that predicts postoperative acute kidney injury: Impact of endogenous ouabain. Nephrology Dialysis Transplantation, 29(9), 1696-1701. https://doi.org/10.1093/ndt/gfu200

A new clinical multivariable model that predicts postoperative acute kidney injury : Impact of endogenous ouabain. / Simonini, Marco; Lanzani, Chiara; Bignami, Elena; Casamassima, Nunzia; Frati, Elena; Meroni, Roberta; Messaggio, Elisabetta; Alfieri, Ottavio; Hamlyn, John; Body, Simon C.; Collard, C. David; Muehlschlegel, J. Daniel; Shernan, Stanton K.; Fox, Amanda A.; Zangrillo, Alberto; Manunta, Paolo.

In: Nephrology Dialysis Transplantation, Vol. 29, No. 9, 2014, p. 1696-1701.

Research output: Contribution to journalArticle

Simonini, M, Lanzani, C, Bignami, E, Casamassima, N, Frati, E, Meroni, R, Messaggio, E, Alfieri, O, Hamlyn, J, Body, SC, Collard, CD, Muehlschlegel, JD, Shernan, SK, Fox, AA, Zangrillo, A & Manunta, P 2014, 'A new clinical multivariable model that predicts postoperative acute kidney injury: Impact of endogenous ouabain', Nephrology Dialysis Transplantation, vol. 29, no. 9, pp. 1696-1701. https://doi.org/10.1093/ndt/gfu200
Simonini, Marco ; Lanzani, Chiara ; Bignami, Elena ; Casamassima, Nunzia ; Frati, Elena ; Meroni, Roberta ; Messaggio, Elisabetta ; Alfieri, Ottavio ; Hamlyn, John ; Body, Simon C. ; Collard, C. David ; Muehlschlegel, J. Daniel ; Shernan, Stanton K. ; Fox, Amanda A. ; Zangrillo, Alberto ; Manunta, Paolo. / A new clinical multivariable model that predicts postoperative acute kidney injury : Impact of endogenous ouabain. In: Nephrology Dialysis Transplantation. 2014 ; Vol. 29, No. 9. pp. 1696-1701.
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abstract = "Background. Acute kidney injury (AKI) is an important complication of cardiac surgery. Recently, elevated levels of endogenous ouabain (EO), an adrenal stress hormone with haemodynamic and renal effects, have been associated with worse renal outcome after cardiac surgery. Our aim was to develop and evaluate a new risk model of AKI using simple preoperative clinical parameters and to investigate the utility of EO. Methods. The primary outcome was AKI according to Acute Kidney Injury Network stage II or III. We selected the Northern New England Cardiovascular Disease Study Group (NNECDSG) as a reference model. We built a new internal predictive risk model considering common clinical variables (CLIN-RISK), compared this model with the NNECDSG model and determined whether the addition of preoperative plasma EO improved prediction of AKI. Results. All models were tested on >800 patients admitted for elective cardiac surgery in our hospital. Seventy-nine patients developed AKI (9.9{\%}). Preoperative EO levels were strongly associated with the incidence of AKI and clinical complication (total ICU stay and in-hospital mortality). The NNECDSG model was confirmed as a good predictor of AKI (AUC 0.74, comparable to the NNECDSG reference population). Our CLIN-RISK model had improved predictive power for AKI (AUC 0.79, CI 95{\%} 0.73-0.84). Furthermore, addition of preoperative EO levels to both clinical models improved AUC to 0.79 and to 0.83, respectively (ΔAUC +0.05 and +0.04, respectively, P < 0.01). Conclusion. In a population where the predictive power of the NNECDSG model was con firmed, CLIN-RISK was more powerful. Both clinical models were further improved by the addition of preoperative plasma EO levels. These new models provide improved predictability of the relative risk for the development of AKI following cardiac surgery and suggest that EO is a marker for renal vascular injury.",
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T2 - Impact of endogenous ouabain

AU - Simonini, Marco

AU - Lanzani, Chiara

AU - Bignami, Elena

AU - Casamassima, Nunzia

AU - Frati, Elena

AU - Meroni, Roberta

AU - Messaggio, Elisabetta

AU - Alfieri, Ottavio

AU - Hamlyn, John

AU - Body, Simon C.

AU - Collard, C. David

AU - Muehlschlegel, J. Daniel

AU - Shernan, Stanton K.

AU - Fox, Amanda A.

AU - Zangrillo, Alberto

AU - Manunta, Paolo

PY - 2014

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N2 - Background. Acute kidney injury (AKI) is an important complication of cardiac surgery. Recently, elevated levels of endogenous ouabain (EO), an adrenal stress hormone with haemodynamic and renal effects, have been associated with worse renal outcome after cardiac surgery. Our aim was to develop and evaluate a new risk model of AKI using simple preoperative clinical parameters and to investigate the utility of EO. Methods. The primary outcome was AKI according to Acute Kidney Injury Network stage II or III. We selected the Northern New England Cardiovascular Disease Study Group (NNECDSG) as a reference model. We built a new internal predictive risk model considering common clinical variables (CLIN-RISK), compared this model with the NNECDSG model and determined whether the addition of preoperative plasma EO improved prediction of AKI. Results. All models were tested on >800 patients admitted for elective cardiac surgery in our hospital. Seventy-nine patients developed AKI (9.9%). Preoperative EO levels were strongly associated with the incidence of AKI and clinical complication (total ICU stay and in-hospital mortality). The NNECDSG model was confirmed as a good predictor of AKI (AUC 0.74, comparable to the NNECDSG reference population). Our CLIN-RISK model had improved predictive power for AKI (AUC 0.79, CI 95% 0.73-0.84). Furthermore, addition of preoperative EO levels to both clinical models improved AUC to 0.79 and to 0.83, respectively (ΔAUC +0.05 and +0.04, respectively, P < 0.01). Conclusion. In a population where the predictive power of the NNECDSG model was con firmed, CLIN-RISK was more powerful. Both clinical models were further improved by the addition of preoperative plasma EO levels. These new models provide improved predictability of the relative risk for the development of AKI following cardiac surgery and suggest that EO is a marker for renal vascular injury.

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KW - Acute renal failure

KW - Blood pressure

KW - Cardiovascular disease

KW - Na transport

KW - Renal injury

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