BACKGROUND: Cardiac surgery-related acute kidney injury (CS-AKI) results in increased morbidity and mortality. Different models have been developed to identify patients at risk of CS-AKI. While models that predict dialysis and CS-AKI defined by the RIFLE criteria are available, their predictive power and clinical applicability have not been compared head to head. METHODS: Of 1388 consecutive adult cardiac surgery patients operated with cardiopulmonary bypass, risk scores of eight prediction models were calculated. Four models were only applicable to a subgroup of patients. The area under the receiver operating curve (AUROC) was calculated for all levels of CS-AKI and for need for dialysis (AKI-D) for each risk model and compared for the models applicable to the largest subgroup (n = 1243). RESULTS: The incidence of AKI-D was 1.9% and for CS-AKI 9.3%. The models of Rahmanian, Palomba and Aronson could not be used for preoperative risk assessment as postoperative data are necessary. The three best AUROCs for AKI-D were of the model of Thakar: 0.93 [95% confidence interval (CI) 0.91-0.94], Fortescue: 0.88 (95% CI 0.87-0.90) and Wijeysundera: 0.87 (95% CI 0.85-0.89). The three best AUROCs for CS-AKI-risk were 0.75 (95% CI 0.73-0.78), 0.74 (95% CI 0.71-0.76) and 0.70 (95% CI 0.73-0.78), for Thakar, Mehta and both Fortescue and Wijeysundera, respectively. The model of Thakar performed significantly better compared with the models of Mehta, Rahmanian, Fortescue and Wijeysundera (all P-values <0.01) at different levels of severity of CS-AKI. CONCLUSIONS: The Thakar model offers the best discriminative value to predict CS-AKI and is applicable in a preoperative setting and for all patients undergoing cardiac surgery.
BACKGROUND: Cardiac surgery-related acute kidney injury (CS-AKI) results in increased morbidity and mortality. Different models have been developed to identify patients at risk of CS-AKI. While models that predict dialysis and CS-AKI defined by the RIFLE criteria are available, their predictive power and clinical applicability have not been compared head to head. METHODS: Of 1388 consecutive adult cardiac surgery patients operated with cardiopulmonary bypass, risk scores of eight prediction models were calculated. Four models were only applicable to a subgroup of patients. The area under the receiver operating curve (AUROC) was calculated for all levels of CS-AKI and for need for dialysis (AKI-D) for each risk model and compared for the models applicable to the largest subgroup (n = 1243). RESULTS: The incidence of AKI-D was 1.9% and for CS-AKI 9.3%. The models of Rahmanian, Palomba and Aronson could not be used for preoperative risk assessment as postoperative data are necessary. The three best AUROCs for AKI-D were of the model of Thakar: 0.93 [95% confidence interval (CI) 0.91-0.94], Fortescue: 0.88 (95% CI 0.87-0.90) and Wijeysundera: 0.87 (95% CI 0.85-0.89). The three best AUROCs for CS-AKI-risk were 0.75 (95% CI 0.73-0.78), 0.74 (95% CI 0.71-0.76) and 0.70 (95% CI 0.73-0.78), for Thakar, Mehta and both Fortescue and Wijeysundera, respectively. The model of Thakar performed significantly better compared with the models of Mehta, Rahmanian, Fortescue and Wijeysundera (all P-values <0.01) at different levels of severity of CS-AKI. CONCLUSIONS: The Thakar model offers the best discriminative value to predict CS-AKI and is applicable in a preoperative setting and for all patients undergoing cardiac surgery.
Authors: Donald S Likosky; Robert A Baker; Timothy A Dickinson; Daniel J FitzGerald; M Filip De Somer; Robert C Groom; David FitzGerald; Kenneth G Shann; Michael Poullis; Bruce D Spiess; Karim Jabr; Mark T Lucas; James D Ferguson; Shahna L Bronson Journal: J Extra Corpor Technol Date: 2015-06
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Authors: Emily M Bucholz; Richard P Whitlock; Michael Zappitelli; Prasad Devarajan; John Eikelboom; Amit X Garg; Heather Thiessen Philbrook; Philip J Devereaux; Catherine D Krawczeski; Peter Kavsak; Colleen Shortt; Chirag R Parikh Journal: Pediatrics Date: 2015-03-09 Impact factor: 7.124
Authors: Ferdinand Vogt; Janez Zibert; Alenka Bahovec; Francesco Pollari; Joachim Sirch; Matthias Fittkau; Thomas Bertsch; Martin Czerny; Giuseppe Santarpino; Theodor Fischlein; Jurij M Kalisnik Journal: Interact Cardiovasc Thorac Surg Date: 2021-06-28