scholarly journals Prediction Scores for Acute Kidney Injury following Adult Cardiac Surgery

2020 ◽  
Author(s):  
Yu Tian ◽  
Wei Zhao ◽  
Yuefu Wang ◽  
Chunrong Wang ◽  
Xiaolin Diao ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Prediction Model ◽  
Prediction Models ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Scoring Systems ◽  
Multivariable Logistic Regression Analysis ◽  
Derivation Cohort ◽  
Associated Risk Factors

Abstract Background In the development of scoring systems for acute kidney injury (AKI) following cardiac surgery, previous investigations have primarily and solely attached importance to preoperative associated risk factors without any consideration for surgery-derived physiopathology. We sought to internally derive and then validate risk score systems using pre- and intraoperative variables to predict the occurrence of any-stage (stage 1-3) and stage-3 AKI within 7 days.Methods Patients undergoing cardiac surgery from Jan 1, 2012, to Jan 1, 2019, were enrolled in our retrospective study. The clinical data were divided into a derivation cohort (n= 43799) and a validation cohort (n= 14600). Multivariable logistic regression analysis was used to develop the prediction models.Results The overall prevalence of any-stage and stage-3 AKI after cardiac surgery was 34.3% and 1.7%, respectively. Any-stage AKI prediction-model discrimination measured by the area under the curve (AUC) was acceptable (AUC = 0.69, 95% CI: 0.68, 0.69), and the prediction model calibration measured by the Hosmer-Lemshow test was good (P = 0.95). The stage-3 AKI prediction model had an AUC of 0.84 (95% CI 0.83, 0.85) and good calibration according to the Hosmer-Lemshow test (P = 0.73).Conclusions Using pre- and intraoperative data, we developed two scoring systems for any-stage AKI and stage-3 AKI in a cardiac surgery population. These scoring systems can potentially be adopted clinically in the field of AKI recognition and therapeutic intervention.

scholarly journals Neutrophil gelatinase-associated lipocalin as a biomarker for acute kidney injury in children after cardiac surgery

2016 ◽  
Vol 56 (4) ◽  
pp. 230
Author(s):  
Meta Herdiana Hanindita ◽  
Riskky Vitria Prasetyo ◽  
Ninik Asmaningsih Soemyarso ◽  
I Ketut Alit Utamayasa ◽  
Paul Tahalele
Keyword(s):  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Creatinine Clearance ◽  
Sensitivity And Specificity ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Schwartz Formula ◽  
Neutrophil Gelatinase Associated Lipocalin ◽  
Plasma Ngal ◽  
Neutrophil Gelatinase

Background Acute kidney injury (AKI) is still diagnosed by measuring the estimated creatinine clearance (eCCl), despite the fact that it may not change until 50% or more of kidney function has been lost. AKI after cardiac surgery is related to prolonged intensive care, decreased quality of life, and increased long term mortality. Neutrophil gelatinase-associated lipocalin (NGAL) represents an early biomarker of AKI, which may be useful for assessing AKI in cardiac patients.Objective To determine the validity of urinary and plasma NGAL as biomarkers for AKI in children after cardiac surgery.Methods Subjects were children who underwent cardiac surgery in Dr. Soetomo Hospital, Surabaya, Indonesia from August 2013 to January 2014. Serial urine and blood samples were analyzed for NGAL before surgery, as well as at 2h, 4h, 12h, and 24h after surgery. The AKI was established based on pRIFLE criteria. Estimated creatinine clearance (eCCl) was calculated from the estimated glomerular filtration rate (eGFR), according to age by the traditional Schwartz formula. Serum creatinine was assayed by the Jaffe method before surgery, as well as at 12h, 24h, 48h, and 72h after surgery.Results Of 20 subjects, 5 developed AKI. Urinary and plasma NGAL increased markedly at 2h postoperatively, as compared to eGFR which showed a rise at 12-48 h after cardiac surgery. Analysis of 2h post-operative urinary NGAL at a cut off value of 11.270ng/mL yielded an area under the curve (AUC) of 1.00 (95%CI 2.63 to 12.13), with sensitivity and specificity of 100% each for AKI. In addition, 2h post-operative plasma NGAL at a cut off value of 8.385 ng/mL yielded an AUC of 1.00 (95%CI 3.71 to 12.15) with sensitivity and specificity of 100% each for AKI.Conclusion Urinary and plasma NGAL are valid as early biomarkers for AKI in children after cardiac surgery.

scholarly journals Intraoperative Hepatic Blood Inflow Can Predict Early Acute Kidney Injury following DCD Liver Transplantation: A Retrospective Observational Study

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Ao Jiao ◽  
Qingpeng Liu ◽  
Feng Li ◽  
Rui Guo ◽  
Bowen Wang ◽  
...  
Keyword(s):  
Liver Transplantation ◽  
Acute Kidney Injury ◽  
Prediction Model ◽  
Prediction Models ◽  
Validation Cohort ◽  
Kidney Injury ◽  
Clinical Usefulness ◽  
Anhepatic Phase ◽  
Blood Inflow ◽  
Ctp Score

Purpose. Acute kidney injury (AKI) is a major and severe complication following donation-after-circulatory-death (DCD) liver transplantation (LT) and is associated with increased postoperative morbidity and mortality. However, the risk factors and the prognosis factors of AKI still need to be further explored, and the relativity of intraoperative hepatic blood inflow (HBI) and AKI following LT has not been discussed yet. The purpose of this study was to investigate the correlation between HBI and AKI and to construct a prediction model of early acute kidney injury (EAKI) following DCD LT with the combination of HBI and other clinical parameters. Methods. Clinical data of 132 patients who underwent DCD liver transplantation at the first hospital of China Medical University from April 2005 to March 2017 were analyzed. Data of 105 patients (the first ten years of patients) were used to develop the prediction model. Then we assessed the clinical usefulness of the prediction models in the validation cohort (27 patients). EAKI according to Kidney Disease Improving Global Outcomes (KDIGO) criteria based on serum creatinine increase during 7-day of postoperative follow-up. Results. After Least Absolute Shrinkage and Selection Operator (LASSO) regression and simplification, a simplified prediction model consisting of the Child-Turcotte-Pugh (CTP) score (p=0.033), anhepatic phase (p=0.014), packed red blood cell (pRBC) transfusion (p=0.027), and the HBI indexed by height (HBI/h) (p=0.002) was established. The C-indexes of the model in the development and validation cohort were 0.823 [95% CI, 0.738-0.908] and 0.921 [95% CI, 0.816-1.000], respectively. Conclusions. In this study, we demonstrated the utility of HBI/h as a predictor for EAKI following DCD LT, as well as the clinical usefulness of the prediction model through the combination of the CTP score, anhepatic phase, pRBC transfusion and HBI/h.

scholarly journals Multi-perspective predictive modeling for acute kidney injury in general hospital populations using electronic medical records

JAMIA Open ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Jianqin He ◽  
Yong Hu ◽  
Xiangzhou Zhang ◽  
Lijuan Wu ◽  
Lemuel R Waitman ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Clinical Application ◽  
Lead Time ◽  
Model Building ◽  
Prediction Models ◽  
Tertiary Care ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Multiple Perspectives ◽  
Future Health

Abstract Objectives Acute kidney injury (AKI) in hospitalized patients puts them at much higher risk for developing future health problems such as chronic kidney disease, stroke, and heart disease. Accurate AKI prediction would allow timely prevention and intervention. However, current AKI prediction researches pay less attention to model building strategies that meet complex clinical application scenario. This study aims to build and evaluate AKI prediction models from multiple perspectives that reflect different clinical applications. Materials and Methods A retrospective cohort of 76 957 encounters and relevant clinical variables were extracted from a tertiary care, academic hospital electronic medical record (EMR) system between November 2007 and December 2016. Five machine learning methods were used to build prediction models. Prediction tasks from 4 clinical perspectives with different modeling and evaluation strategies were designed to build and evaluate the models. Results Experimental analysis of the AKI prediction models built from 4 different clinical perspectives suggest a realistic prediction performance in cross-validated area under the curve ranging from 0.720 to 0.764. Discussion Results show that models built at admission is effective for predicting AKI events in the next day; models built using data with a fixed lead time to AKI onset is still effective in the dynamic clinical application scenario in which each patient’s lead time to AKI onset is different. Conclusion To our best knowledge, this is the first systematic study to explore multiple clinical perspectives in building predictive models for AKI in the general inpatient population to reflect real performance in clinical application.

Perioperative Hemodynamic Instability and Fluid Overload are Associated with Increasing Acute Kidney Injury Severity and Worse Outcome after Cardiac Surgery

2017 ◽  
Vol 43 (4) ◽  
pp. 298-308 ◽  
Author(s):  
Anja Haase-Fielitz ◽  
Michael Haase ◽  
Rinaldo Bellomo ◽  
Paolo Calzavacca ◽  
Anke Spura ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Hospital Mortality ◽  
Fluid Balance ◽  
Injury Severity ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Chronic Obstructive ◽  
Hemodynamic Management ◽  
Physiological Variables

Purpose: The study aimed to investigate patients' characteristics, fluid and hemodynamic management, and outcomes according to the severity of cardiac surgery-associated acute kidney injury (CSA-AKI). Methods: In a single-center, prospective cohort study, we enrolled 282 adult cardiac surgical patients. In a secondary analysis, we assessed preoperative patients' characteristics, physiological variables, and medication for intra- and postoperative fluid and hemodynamic management and outcomes according to CSA-AKI stages by the Renal risk, Injury, Failure, Loss, End-stage renal disease (RIFLE) classification. Variables of fluid and hemodynamic management were further assessed with regard to the need for postoperative renal replacement therapy (RRT) and in-hospital mortality by the area under the curve for the receiver operating characteristic (AUC-ROC) and multivariate regression analysis. Results: Patients with worsening RIFLE stage, were significantly older, had lower estimated glomerular filtration rate and higher body mass index, more peripheral vascular and chronic obstructive pulmonary disease, atrial fibrillation, and prolonged duration of cardiopulmonary bypass (all p < 0.01). Patients with more severe AKI stage stayed longer in the intensive care and hospital, had higher in-hospital mortality, and requirement for RRT (all p < 0.001). Also, with worsening RIFLE stage, patients had lower intraoperative mean arterial pressure (MAP); p = 0.047, despite higher doses of norepinephrine (p < 0.001). The intraoperative MAP showed the best discriminatory ability (AUC-ROC: >0.8) for and was independently associated with RRT and in-hospital mortality. Moreover, with increasing AKI severity, patients received significantly more fluid infusion, and required higher dose of furosemide; nonetheless, they had increased postoperative fluid balance. Conclusions: In this cohort, reduced MAP and increased fluid balance were independently associated with increased mortality and need for RRT after cardiac surgery.

scholarly journals A Validation Study Comparing Existing Prediction Models of Acute Kidney Injury in Patients with Acute Heart Failure: A Multi-Institution Database Study in Taiwan

2020 ◽  
Author(s):  
Tao Han Lee ◽  
Pei-Chun Fan ◽  
Jia-Jin Chen ◽  
Victor Chien‐Chia Wu ◽  
Cheng-Chia Lee ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Kidney Injury ◽  
Prediction Model ◽  
Acute Heart Failure ◽  
Risk Score ◽  
Prediction Models ◽  
Discrimination Performance ◽  
Kidney Injury ◽  
Research Database ◽  
Readmission Rates

Abstract Background:Acute kidney injury (AKI) is a common complication in hospitalized acute heart failure (AHF) patients and is associated with prolonged hospitalization, increased readmission rates, and mortality. The aim of this study was to externally validate existing prediction models of AKI in patients with AHF.Methods:A total of 10,364 patients hospitalized for acute heart failure (AHF) between 2008 and 2018 were extracted from the Chang Gung Research Database and analyzed. The primary outcome of interest was AKI, defined according to the KDIGO definition. We also extended the existing prediction models to predict AKI stage 3 and dialysis. The area under the receiver operating characteristic (AUC) curve was used to assess the discrimination performance of each prediction model. Results:Five existing prediction models were externally validated, with the AUCs for AKI prediction ranging from 0.543 to 0.73. These prediction models also performed well in serious AKI event prediction, with AUCs of 0.565–0.858 for predicting AKI stage 3 and AUCs of 0.539–0.845 for predicting dialysis within 7 days. Among the five models, the Forman risk score and the prediction model reported by Wang et al. showed the most favorable discrimination and calibration performance. The Forman risk score had AUCs for discriminating AKI, AKI stage 3, and dialysis within 7 days of 0.696, 0.829, and 0.817, respectively. The Wang et al. model had AUCs for discriminating AKI, AKI stage 3, and dialysis within 7 days of 0.73, 0.858, and 0.845, respectively. Conclusion:The Forman risk score and the Wang et al. prediction model are simple and accurate tools for predicting AKI and serious AKI events in patients with AHF. They can aid clinicians in evaluating the risk of AKI in these patients and in planning and initiating adequate disease management in a timely manner.

scholarly journals Preoperative N-terminal pro-B-type natriuretic peptide for prediction of acute kidney injury after non-cardiac surgery: A retrospective cohort study

2020 ◽  
Author(s):  
Bingcheng Zhao ◽  
Pei-Pei Zhuang ◽  
Shao-Hui Lei ◽  
Shi-Da Qiu ◽  
Xiao Yang ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Natriuretic Peptide ◽  
Area Under The Curve ◽  
Kidney Injury ◽  
Clinical Variables ◽  
Net Reclassification Improvement ◽  
Predictive Role ◽  
Poor Outcomes ◽  
Integrated Discrimination Improvement

Abstract Background Acute kidney injury (AKI) is associated with poor outcomes after non-cardiac surgery. Whether preoperative N-terminal pro-B-type natriuretic peptide (NT-proBNP) predicts AKI after non-cardiac surgery is unclear. Methods We conducted a retrospective study on patients whose NT-proBNP concentrations were measured before non-cardiac surgery at a tertiary academic hospital between 2008 and 2018. Multivariable logistic regression was used to investigate the predictive role of preoperative NT-proBNP on postoperative AKI defined by the Kidney Disease: Improving Global Outcomes creatinine criteria. Results Some 6.1% (444 of 7248) of patients developed AKI within 1 week after surgery. Preoperative NT-proBNP was an independent predictor of AKI after adjustment for clinical variables (odd ratio comparing top to bottom quintiles 2.29, 95% confidence interval [CI] 1.47-3.65, p<0.001 for trend; odd ratio per 1-unit increment in natural log transformed NT-proBNP 1.27, 95% CI 1.16-1.39). Compared with clinical variables alone, the addition of NT-proBNP modestly improved the discrimination (change in area under the curve from 0.764 to 0.773, p=0.005) and reclassification (continuous net reclassification improvement 0.210, 95% CI 0.111-0.308; integrated discrimination improvement 0.0044, 95% CI 0.0016-0.0072) of AKI and non-AKI cases. Conclusions Preoperative NT-proBNP concentrations provided predictive information for AKI in a cohort of patients undergoing non-cardiac surgery, independent of and incremental to conventional risk factors. Prospective studies are required to confirm this finding and examine its clinical impact.

scholarly journals Cardiac surgery-associated acute kidney injury: risk factors analysis and comparison of prediction models

2015 ◽  
Vol 21 (3) ◽  
pp. 366-373 ◽  
Author(s):  
Darko Kristovic ◽  
Ivica Horvatic ◽  
Ino Husedzinovic ◽  
Zeljko Sutlic ◽  
Igor Rudez ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Injury Risk ◽  
Prediction Models ◽  
Kidney Injury ◽  
Factors Analysis ◽  
Injury Risk Factors

scholarly journals Intra-abdominal hypertension and increased acute kidney injury risk: a systematic review and meta-analysis

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110166
Author(s):  
Jing Sun ◽  
Hongjun Sun ◽  
Zhijian Sun ◽  
Xin Yang ◽  
Shuhua Zhou ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Acute Kidney Injury ◽  
Cardiac Surgery ◽  
Body Mass ◽  
Injury Risk ◽  
Meta Analysis ◽  
Kidney Injury ◽  
Search Terms ◽  
Abdominal Hypertension ◽  
Associated Risk Factors

Objective The present meta-analysis aimed to determine the relationship between intra-abdominal hypertension (IAH) and an increased prevalence of acute kidney injury (AKI) and identify the associated risk factors in various patient populations, regardless of whether they were admitted to an intensive care unit. Methods We used three databases for the following search terms: “IAH,” “abdominal compartment syndrome,” “AKI,” “acute kidney failure,” and others. The articles retrieved were compared to identify appropriate studies published until 7 May 2020. The main outcome was AKI. Results Six studies with 344 individuals were included. The patients were divided into two main groups: the IAH and non-IAH groups. Compared with patients without IAH, patients with IAH had a higher risk of AKI (odds ratio = 2.57, 95% confidence interval: 1.55–4.26). In the subgroup and meta-regression analyses, body mass index, age, the presence or absence of burns, and cardiac surgery did not affect the risk of AKI. Conclusion IAH was associated with AKI risk, and this association was not influenced by age, body mass index, the presence or absence of burns, or cardiac surgery.

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