Literature DB >> 30078648

Validation of renal-risk models for the prediction of non-renal replacement therapy cardiac surgery-associated acute kidney injury.

Marco Ranucci1, Tommaso Aloisio2, Anna Cazzaniga2, Umberto Di Dedda2, Chiara Gallazzi2, Valeria Pistuddi2.   

Abstract

BACKGROUND: Cardiac surgery-associated acute kidney injury (AKI) is a serious complication of cardiac surgery, even when renal replacement therapy (RRT) is not required. The existing risk models for cardiac surgery associated AKI are designed to predict AKI requiring RRT (RRT-AKI). The aim of this study is to validate three risk models for the prediction of RRT-dependent and non-RRT AKI after cardiac surgery.
METHODS: Retrospective analysis on 7675 consecutive adult patients undergoing cardiac surgery with cardiopulmonary bypass. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for stage 1 and 2. RRT AKI and non-RRT AKI were defined according to the need for RRT. Three risk models were validated separately for RRT and non-RRT AKI: the Cleveland Risk Score, the Bedside Risk Score, and the Simplified Renal Index Scoring Scheme. Discrimination power was assessed with Receiver Operating Characteristics analysis and c-statistics.
RESULTS: There were 502 (6.5%) non-RRT AKI events, 128 (1.7%) RRT-AKI events, and 7045 (91.8%) no-events. The three models performed well for predicting RRT-AKI (c-statistics 0.75-0.79) and poorly for predicting non-RRT AKI (c-statistics 0.54-0.59). The models had an excellent calibration for RRT-AKI but not for non-RRT AKI. Preoperative serum creatinine and estimated glomerular filtration rate were associated with RRT AKI but not with non-RRT AKI. Mortality was 12.2% in non-RRT AKI and 46.9% in RRT-AKI, significantly (P = 0.001) higher than in patients without AKI (1.3%).
CONCLUSIONS: The existing risk models are inadequate for predicting non-RRT AKI following cardiac surgery, both in terms of discrimination and calibration.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acute kidney injury; Cardiac surgery; Risk scores

Mesh:

Year:  2018        PMID: 30078648     DOI: 10.1016/j.ijcard.2018.07.114

Source DB:  PubMed          Journal:  Int J Cardiol        ISSN: 0167-5273            Impact factor:   4.164


  6 in total

1.  The prognosis and risk factors for acute kidney injury in high-risk patients after surgery for type A aortic dissection in the ICU.

Authors:  Kun Zhang; Jiuyan Shang; Yuhong Chen; Yan Huo; Bin Li; Zhenjie Hu
Journal:  J Thorac Dis       Date:  2021-07       Impact factor: 2.895

2.  Optimal timing of renal replacement therapy for favourable outcome in patients of acute renal failure following cardiac surgery.

Authors:  Shanshank Tripathi; Shantanu Pande; Pulkit Malhotra; Supaksh Mahindru; Ankit Thukral; Ankush Singh Kotwal; Gauranga Majumdar; Surendra Kumar Agarwal; Amit Gupta
Journal:  Indian J Thorac Cardiovasc Surg       Date:  2019-09-05

3.  Impact of preoperative SYNTAX Scores on short-term outcome following coronary artery bypass grafting surgery in the patients with multi-vessels coronary artery disease.

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Journal:  Egypt Heart J       Date:  2020-07-02

4.  A novel machine learning algorithm, Bayesian networks model, to predict the high-risk patients with cardiac surgery-associated acute kidney injury.

Authors:  Yang Li; Jiarui Xu; Yimei Wang; Yunlu Zhang; Wuhua Jiang; Bo Shen; Xiaoqiang Ding
Journal:  Clin Cardiol       Date:  2020-05-12       Impact factor: 2.882

5.  Activating Transcription Factor 3 Based Early Alarm Model of Acute Kidney Injury after Cardiopulmonary Bypass in Adults.

Authors:  Xiao-Yun Wu; Xiang-Lan Jin; Qiang Liu; Feng Qiu; Jian Zhou
Journal:  Dis Markers       Date:  2022-10-11       Impact factor: 3.464

6.  Derivation and Validation a Risk Model for Acute Kidney Injury and Subsequent Adverse Events After Cardiac Surgery: A Multicenter Cohort Study.

Authors:  Hang Zhang; Min Yu; Rui Wang; Rui Fan; Ke Zhang; Wen Chen; Xin Chen
Journal:  Int J Gen Med       Date:  2022-10-10
  6 in total

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